# coding: utf-8
# (C) Copyright IBM Corp. 2026.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Watson OpenScale API Specification
"""
from datetime import datetime
from enum import Enum
from typing import BinaryIO, Dict, List, TextIO, Union
import json
from ibm_cloud_sdk_core import BaseService, DetailedResponse
from ibm_cloud_sdk_core.authenticators.authenticator import Authenticator
from ibm_cloud_sdk_core.get_authenticator import get_authenticator_from_environment
from ibm_cloud_sdk_core.utils import convert_list, convert_model, datetime_to_string, string_to_datetime
from .common import get_sdk_headers
##############################################################################
# Service
##############################################################################
class WatsonOpenScaleV2(BaseService):
"""The Watson OpenScale V2 service."""
DEFAULT_SERVICE_URL = None
DEFAULT_SERVICE_NAME = 'ai_openscale'
@classmethod
def new_instance(cls,
service_name: str = DEFAULT_SERVICE_NAME,
) -> 'WatsonOpenScaleV2':
"""
Return a new client for the Watson OpenScale service using the specified
parameters and external configuration.
"""
authenticator = get_authenticator_from_environment(service_name)
service = cls(
authenticator
)
service.configure_service(service_name)
return service
def __init__(self,
authenticator: Authenticator = None,
) -> None:
"""
Construct a new client for the Watson OpenScale service.
:param Authenticator authenticator: The authenticator specifies the authentication mechanism.
Get up to date information from https://github.com/IBM/python-sdk-core/blob/master/README.md
about initializing the authenticator of your choice.
"""
BaseService.__init__(self,
service_url=self.DEFAULT_SERVICE_URL,
authenticator=authenticator)
#########################
# Data Marts
#########################
class DataMarts:
"""
Data Marts
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a DataMarts client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def add(self,
*,
name: str = None,
description: str = None,
service_instance_crn: str = None,
internal_database: bool = None,
database_configuration: 'DatabaseConfigurationRequest' = None,
database_discovery: str = None,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Create a new data mart.
Create a new data mart with the given database connection.
:param str name: (optional) Name of the data mart.
:param str description: (optional) Description of the data mart.
:param str service_instance_crn: (optional) Can be omitted if user token is
used for authorization.
:param bool internal_database: (optional) If `true` the internal database
managed by AI OpenScale is provided for the user.
:param DatabaseConfigurationRequest database_configuration: (optional)
Database configuration ignored if internal database is requested
(`internal_database` is `true`).
:param str database_discovery: (optional) Indicates if the database was
discovered automatically or manually added by user through UI.
:param bool force: (optional) force update of metadata and db credentials
(assumption is that the new database is already prepared and populated).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataMartDatabaseResponse` result
"""
if database_configuration is not None:
database_configuration = convert_model(database_configuration)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_marts_add')
headers.update(sdk_headers)
params = {
'force': force
}
data = {
'name': name,
'description': description,
'service_instance_crn': service_instance_crn,
'internal_database': internal_database,
'database_configuration': database_configuration,
'database_discovery': database_discovery
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_marts'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(DataMartDatabaseResponse, 'from_dict'):
response.result = DataMartDatabaseResponse.from_dict(response.result)
return response
[docs]
def list(self,
**kwargs
) -> DetailedResponse:
"""
List all data marts.
The method returns the data mart configurations as an object.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataMartDatabaseResponseCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_marts_list')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_marts'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers)
response = self.watson_open_scale.send(request)
if hasattr(DataMartDatabaseResponseCollection, 'from_dict'):
response.result = DataMartDatabaseResponseCollection.from_dict(response.result)
return response
[docs]
def get(self,
data_mart_id: str,
**kwargs
) -> DetailedResponse:
"""
Get data mart with the given id.
:param str data_mart_id: ID of the data mart.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataMartDatabaseResponse` result
"""
if data_mart_id is None:
raise ValueError('data_mart_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_marts_get')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_marts/{0}'.format(
*self.watson_open_scale.encode_path_vars(data_mart_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers)
response = self.watson_open_scale.send(request)
if hasattr(DataMartDatabaseResponse, 'from_dict'):
response.result = DataMartDatabaseResponse.from_dict(response.result)
return response
[docs]
def patch(self,
data_mart_id: str,
json_patch_operation: List['JsonPatchOperation'],
**kwargs
) -> DetailedResponse:
"""
Update a data mart.
:param str data_mart_id: ID of the data mart.
:param List[JsonPatchOperation] json_patch_operation:
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataMartDatabaseResponse` result
"""
if data_mart_id is None:
raise ValueError('data_mart_id must be provided')
if json_patch_operation is None:
raise ValueError('json_patch_operation must be provided')
json_patch_operation = [convert_model(x) for x in json_patch_operation]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_marts_patch')
headers.update(sdk_headers)
data = json.dumps(json_patch_operation)
headers['content-type'] = 'application/json-patch+json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_marts/{0}'.format(
*self.watson_open_scale.encode_path_vars(data_mart_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(DataMartDatabaseResponse, 'from_dict'):
response.result = DataMartDatabaseResponse.from_dict(response.result)
return response
def delete(self,
data_mart_id: str,
*,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Delete a data mart.
:param str data_mart_id: ID of the data mart.
:param bool force: (optional) Force hard delete.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if data_mart_id is None:
raise ValueError('data_mart_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_marts_delete')
headers.update(sdk_headers)
params = {
'force': force
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/data_marts/{0}'.format(
*self.watson_open_scale.encode_path_vars(data_mart_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
#########################
# Service Providers
#########################
class ServiceProviders:
"""
Service Providers
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a ServiceProviders client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
[docs]
def list(self,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
show_deleted: bool = None,
service_type: str = None,
instance_id: str = None,
operational_space_id: str = None,
deployment_space_id: str = None,
integrated_project_id: str = None,
**kwargs
) -> DetailedResponse:
"""
List service providers.
List associated Machine Learning service instances.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool show_deleted: (optional) show also resources pending delete.
:param str service_type: (optional) Type of service.
:param str instance_id: (optional) comma-separated list of IDs.
:param str operational_space_id: (optional) comma-separated list of IDs.
:param str deployment_space_id: (optional) comma-separated list of IDs.
:param str integrated_project_id: (optional) comma-separated list of IDs.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `ServiceProviderResponseCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='service_providers_list')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'show_deleted': show_deleted,
'service_type': service_type,
'instance_id': instance_id,
'operational_space_id': operational_space_id,
'deployment_space_id': deployment_space_id,
'integrated_project_id': integrated_project_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/service_providers'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(ServiceProviderResponseCollection, 'from_dict'):
response.result = ServiceProviderResponseCollection.from_dict(response.result)
return response
def add(self,
name: str,
service_type: str,
credentials: 'MLCredentials',
*,
description: str = None,
request_headers: dict = None,
instance_id: str = None,
operational_space_id: str = None,
deployment_space_id: str = None,
integrated_project_id: str = None,
group_ids: List[str] = None,
user_ids: List[str] = None,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Add service provider.
Associate external Machine Learning service instance with the OpenScale DataMart.
:param str name: Name of the ML service instance.
:param str service_type: machine learning service type
(azure_machine_learning_studio is a preferred alias for
azure_machine_learning and should be used in new service bindings).
:param MLCredentials credentials:
:param str description: (optional)
:param dict request_headers: (optional) map header name to header value.
:param str instance_id: (optional) Reference to the linked service
instance.
- For **watson_machine_learning**: This can be discovered from the
`deployment_space_id` field.
- For ***wxo*** a.k.a watsonx orchestrate: This field is **mandatory**
and must be set to the correct service instance ID.
:param str operational_space_id: (optional) Reference to Operational Space.
:param str deployment_space_id: (optional) Reference to V2 Space ID.
:param str integrated_project_id: (optional) Project ID.
:param List[str] group_ids: (optional) Access control list of group id of
Cloud Pak for Data (Only available for OpenScale on Cloud Pak for Data >=
4.0.6 with ENABLE_GROUP_AUTH being true).
:param List[str] user_ids: (optional) Access control list of user id of
Cloud Pak for Data (Only available for OpenScale on Cloud Pak for Data >=
4.0.6 with ENABLE_GROUP_AUTH being true).
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `ServiceProviderResponse` result
"""
if name is None:
raise ValueError('name must be provided')
if service_type is None:
raise ValueError('service_type must be provided')
if credentials is None:
raise ValueError('credentials must be provided')
credentials = convert_model(credentials)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='service_providers_add')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = {
'name': name,
'service_type': service_type,
'credentials': credentials,
'description': description,
'request_headers': request_headers,
'instance_id': instance_id,
'operational_space_id': operational_space_id,
'deployment_space_id': deployment_space_id,
'integrated_project_id': integrated_project_id,
'group_ids': group_ids,
'user_ids': user_ids
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/service_providers'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(ServiceProviderResponse, 'from_dict'):
response.result = ServiceProviderResponse.from_dict(response.result)
return response
[docs]
def get(self,
service_provider_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get a specific service provider.
Get the associated Machine Learning service provider details.
:param str service_provider_id: ID of the ML service provider.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `ServiceProviderResponse` result
"""
if service_provider_id is None:
raise ValueError('service_provider_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='service_providers_get')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/service_providers/{0}'.format(
*self.watson_open_scale.encode_path_vars(service_provider_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(ServiceProviderResponse, 'from_dict'):
response.result = ServiceProviderResponse.from_dict(response.result)
return response
def delete(self,
service_provider_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Delete a service provider.
Detach Machine Learning service provider.
:param str service_provider_id: ID of the ML service provider.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool force: (optional) Force hard delete.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if service_provider_id is None:
raise ValueError('service_provider_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='service_providers_delete')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'force': force
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/service_providers/{0}'.format(
*self.watson_open_scale.encode_path_vars(service_provider_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
[docs]
def update(self,
service_provider_id: str,
patch_document: List['PatchDocument'],
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update a service provider.
Update existing service provider.
:param str service_provider_id: ID of the ML service provider.
:param List[PatchDocument] patch_document:
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `ServiceProviderResponse` result
"""
if service_provider_id is None:
raise ValueError('service_provider_id must be provided')
if patch_document is None:
raise ValueError('patch_document must be provided')
patch_document = [convert_model(x) for x in patch_document]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='service_providers_update')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(patch_document)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/service_providers/{0}'.format(
*self.watson_open_scale.encode_path_vars(service_provider_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(ServiceProviderResponse, 'from_dict'):
response.result = ServiceProviderResponse.from_dict(response.result)
return response
#########################
# Subscriptions
#########################
class Subscriptions:
"""
Subscriptions
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a Subscriptions client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
[docs]
def list(self,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
data_mart_id: str = None,
service_provider_id: str = None,
asset_asset_id: str = None,
asset_asset_type: str = None,
asset_foundational_model_id: str = None,
deployment_deployment_id: str = None,
deployment_deployment_type: str = None,
integration_reference_integrated_system_id: str = None,
integration_reference_external_id: str = None,
risk_evaluation_status_state: str = None,
service_provider_operational_space_id: str = None,
service_provider_deployment_space_id: str = None,
service_provider_integrated_project_id: str = None,
pre_production_reference_id: str = None,
**kwargs
) -> DetailedResponse:
"""
List subscriptions.
List subscriptions.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str data_mart_id: (optional) comma-separated list of IDs.
:param str service_provider_id: (optional) comma-separated list of IDs.
:param str asset_asset_id: (optional) comma-separated list of IDs.
:param str asset_asset_type: (optional) comma-separated list of types.
:param str asset_foundational_model_id: (optional) comma-separated list of
IDs.
:param str deployment_deployment_id: (optional) comma-separated list of
IDs.
:param str deployment_deployment_type: (optional) comma-separated list of
types.
:param str integration_reference_integrated_system_id: (optional)
comma-separated list of IDs.
:param str integration_reference_external_id: (optional) comma-separated
list of IDs.
:param str risk_evaluation_status_state: (optional) comma-separated list of
states.
:param str service_provider_operational_space_id: (optional)
comma-separated list of operational space ids (property of service provider
object).
:param str service_provider_deployment_space_id: (optional) comma-separated
list of deployment space ids (property of service provider object).
:param str service_provider_integrated_project_id: (optional)
comma-separated list of integrated project ids (property of service
provider object).
:param str pre_production_reference_id: (optional) comma-separated list of
IDs.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `SubscriptionResponseCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='subscriptions_list')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'data_mart_id': data_mart_id,
'service_provider_id': service_provider_id,
'asset.asset_id': asset_asset_id,
'asset.asset_type': asset_asset_type,
'asset.foundational_model_id': asset_foundational_model_id,
'deployment.deployment_id': deployment_deployment_id,
'deployment.deployment_type': deployment_deployment_type,
'integration_reference.integrated_system_id': integration_reference_integrated_system_id,
'integration_reference.external_id': integration_reference_external_id,
'risk_evaluation_status.state': risk_evaluation_status_state,
'service_provider.operational_space_id': service_provider_operational_space_id,
'service_provider.deployment_space_id': service_provider_deployment_space_id,
'service_provider.integrated_project_id': service_provider_integrated_project_id,
'pre_production_reference_id': pre_production_reference_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(SubscriptionResponseCollection, 'from_dict'):
response.result = SubscriptionResponseCollection.from_dict(response.result)
return response
def add(self,
data_mart_id: str,
service_provider_id: str,
asset: 'Asset',
deployment: 'AssetDeploymentRequest',
*,
asset_properties: 'AssetPropertiesRequest' = None,
risk_evaluation_status: 'RiskEvaluationStatus' = None,
analytics_engine: 'AnalyticsEngine' = None,
data_sources: List['DataSource'] = None,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Add a new subscription.
Add a new subscription to the model deployment.
:param str data_mart_id:
:param str service_provider_id:
:param Asset asset:
:param AssetDeploymentRequest deployment:
:param AssetPropertiesRequest asset_properties: (optional) Additional asset
properties (subject of discovery if not provided when creating the
subscription).
:param RiskEvaluationStatus risk_evaluation_status: (optional)
:param AnalyticsEngine analytics_engine: (optional)
:param List[DataSource] data_sources: (optional)
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `SubscriptionResponse` result
"""
if data_mart_id is None:
raise ValueError('data_mart_id must be provided')
if service_provider_id is None:
raise ValueError('service_provider_id must be provided')
if asset is None:
raise ValueError('asset must be provided')
if deployment is None:
raise ValueError('deployment must be provided')
asset = convert_model(asset)
deployment = convert_model(deployment)
if asset_properties is not None:
asset_properties = convert_model(asset_properties)
if risk_evaluation_status is not None:
risk_evaluation_status = convert_model(risk_evaluation_status)
if analytics_engine is not None:
analytics_engine = convert_model(analytics_engine)
if data_sources is not None:
data_sources = [convert_model(x) for x in data_sources]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='subscriptions_add')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = {
'data_mart_id': data_mart_id,
'service_provider_id': service_provider_id,
'asset': asset,
'deployment': deployment,
'asset_properties': asset_properties,
'risk_evaluation_status': risk_evaluation_status,
'analytics_engine': analytics_engine,
'data_sources': data_sources
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(SubscriptionResponse, 'from_dict'):
response.result = SubscriptionResponse.from_dict(response.result)
return response
[docs]
def get(self,
subscription_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get a specific subscription.
Get a specific subscription.
:param str subscription_id: Unique subscription ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `SubscriptionResponse` result
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='subscriptions_get')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions/{0}'.format(
*self.watson_open_scale.encode_path_vars(subscription_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(SubscriptionResponse, 'from_dict'):
response.result = SubscriptionResponse.from_dict(response.result)
return response
[docs]
def update(self,
subscription_id: str,
patch_document: List['PatchDocument'],
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update a subscription.
Update existing asset (from ML service instance) subscription.
:param str subscription_id: Unique subscription ID.
:param List[PatchDocument] patch_document:
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `SubscriptionResponse` result
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
if patch_document is None:
raise ValueError('patch_document must be provided')
patch_document = [convert_model(x) for x in patch_document]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='subscriptions_update')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(patch_document)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions/{0}'.format(
*self.watson_open_scale.encode_path_vars(subscription_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(SubscriptionResponse, 'from_dict'):
response.result = SubscriptionResponse.from_dict(response.result)
return response
def delete(self,
subscription_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Delete a subscription.
Delete a subscription.
:param str subscription_id: Unique subscription ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool force: (optional) Force hard delete. All data for records and
metrics associated to the subscription will be deleted.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='subscriptions_delete')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'force': force
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/subscriptions/{0}'.format(
*self.watson_open_scale.encode_path_vars(subscription_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
[docs]
def schemas(self,
subscription_id: str,
*,
input_data: List['ScoreData'] = None,
training_data_reference: 'InputDataReference' = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Derive model schemas from the training data.
Derive model schemas from the training data. Only "structured" input data type is
supported. If the input_data_type field in the subscription (subscription ->
entity -> asset -> input_data_type) is not "structured", an error will be
returned.
:param str subscription_id: Unique subscription ID.
:param List[ScoreData] input_data: (optional) Array of score data object.
If multiple score data objects are included, the "fields" array (if any)
for score purposes will always be taken from the first score data object.
:param InputDataReference training_data_reference: (optional)
InputDataReference is the same as TrainingDataReference except that neither
location nor connection is required. This is needed for the Schemas API and
to avoid updating existing APIs.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `SchemaInferenceResponse` result
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
if input_data is not None:
input_data = [convert_model(x) for x in input_data]
if training_data_reference is not None:
training_data_reference = convert_model(training_data_reference)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='subscriptions_schemas')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = {
'input_data': input_data,
'training_data_reference': training_data_reference
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions/{0}/schemas'.format(
*self.watson_open_scale.encode_path_vars(subscription_id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(SchemaInferenceResponse, 'from_dict'):
response.result = SchemaInferenceResponse.from_dict(response.result)
return response
[docs]
def tables(self,
subscription_id: str,
dataset_type: str,
unknown_base_type: object,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Create a table for specified data set type.
Current supported dataset_type is feedback. The body of request should be json
object (an empty object `{}` is fine).
:param str subscription_id: Unique subscription ID.
:param str dataset_type: data set type of subscription.
:param UNKNOWN_BASE_TYPE unknown_base_type:
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataSetResponse` result
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
if dataset_type is None:
raise ValueError('dataset_type must be provided')
if unknown_base_type is None:
raise ValueError('unknown_base_type must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='subscriptions_tables')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(unknown_base_type)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions/{0}/tables/{1}'.format(
*self.watson_open_scale.encode_path_vars(subscription_id, dataset_type))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(DataSetResponse, 'from_dict'):
response.result = DataSetResponse.from_dict(response.result)
return response
[docs]
def configuration_synchrozation_get(self,
subscription_id: str,
**kwargs
) -> DetailedResponse:
"""
Get status of triggered configuration synchronization.
:param str subscription_id: Unique subscription ID.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `ConfigurationSynchronization` result
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='get_configuration_synchrozation')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions/{0}/configuration_synchronization'.format(
*self.watson_open_scale.encode_path_vars(subscription_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers)
response = self.watson_open_scale.send(request)
if hasattr(ConfigurationSynchronization, 'from_dict'):
response.result = ConfigurationSynchronization.from_dict(response.result)
return response
[docs]
def trigger_configuration_synchrozation(self,
subscription_id: str,
*,
exclude_monitors: List[str] = None,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Trigger configuration synchronization from pre-production to production model.
Trigger configuration synchronization based on `pre_production_reference_id` in
`subscription`.
:param str subscription_id: Unique subscription ID.
:param List[str] exclude_monitors: (optional)
:param bool force: (optional) a flag to synchronize forcely.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `ConfigurationSynchronization` result
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='trigger_configuration_synchrozation')
headers.update(sdk_headers)
params = {
'force': force
}
data = {
'exclude_monitors': exclude_monitors
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions/{0}/configuration_synchronization'.format(
*self.watson_open_scale.encode_path_vars(subscription_id))
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(ConfigurationSynchronization, 'from_dict'):
response.result = ConfigurationSynchronization.from_dict(response.result)
return response
[docs]
def score(self,
subscription_id: str,
values: List[str],
*,
fields: List[str] = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Computes the bias mitigation/remediation for the specified model.
Computes the bias mitigation/remediation for the specified model. The fairness
monitoring debias request payload details must be valid.
:param str subscription_id: Unique subscription ID.
:param List[str] values: The values associated to the fields.
:param List[str] fields: (optional) The fields to process debias scoring.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `FairnessMonitoringRemediation` result
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
if values is None:
raise ValueError('values must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='subscriptions_score')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = {
'values': values,
'fields': fields
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions/{0}/predictions'.format(
*self.watson_open_scale.encode_path_vars(subscription_id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(FairnessMonitoringRemediation, 'from_dict'):
response.result = FairnessMonitoringRemediation.from_dict(response.result)
return response
#########################
# Data Sets
#########################
class DataSets:
"""
Data Sets
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a DataSets client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
[docs]
def list(self,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
target_target_id: str = None,
target_target_type: str = None,
type: str = None,
managed_by: str = None,
**kwargs
) -> DetailedResponse:
"""
List all data sets specified by the parameters.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str target_target_id: (optional) ID of the data set target (e.g.
subscription ID.. ).
:param str target_target_type: (optional) type of the target.
:param str type: (optional) type of the data set.
:param str managed_by: (optional) ID of the managing entity (e.g. data mart
id).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataSetResponseCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_sets_list')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'target.target_id': target_target_id,
'target.target_type': target_target_type,
'type': type,
'managed_by': managed_by
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(DataSetResponseCollection, 'from_dict'):
response.result = DataSetResponseCollection.from_dict(response.result)
return response
def add(self,
data_mart_id: str,
name: str,
type: str,
target: 'Target',
data_schema: 'SparkStruct',
*,
description: str = None,
schema_update_mode: str = None,
location: 'LocationTableName' = None,
managed_by: str = None,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Create a new data set.
Create a new data set.
:param str data_mart_id:
:param str name:
:param str type: type of a data set.
:param Target target:
:param SparkStruct data_schema:
:param str description: (optional)
:param str schema_update_mode: (optional)
:param LocationTableName location: (optional)
:param str managed_by: (optional)
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataSetResponse` result
"""
if data_mart_id is None:
raise ValueError('data_mart_id must be provided')
if name is None:
raise ValueError('name must be provided')
if type is None:
raise ValueError('type must be provided')
if target is None:
raise ValueError('target must be provided')
if data_schema is None:
raise ValueError('data_schema must be provided')
target = convert_model(target)
data_schema = convert_model(data_schema)
if location is not None:
location = convert_model(location)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_sets_add')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = {
'data_mart_id': data_mart_id,
'name': name,
'type': type,
'target': target,
'data_schema': data_schema,
'description': description,
'schema_update_mode': schema_update_mode,
'location': location,
'managed_by': managed_by
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(DataSetResponse, 'from_dict'):
response.result = DataSetResponse.from_dict(response.result)
return response
[docs]
def get(self,
data_set_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get data set with the given id.
:param str data_set_id: ID of the data set.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataSetResponse` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_sets_get')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}'.format(
*self.watson_open_scale.encode_path_vars(data_set_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(DataSetResponse, 'from_dict'):
response.result = DataSetResponse.from_dict(response.result)
return response
def delete(self,
data_set_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Delete a data set.
:param str data_set_id: ID of the data set.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool force: (optional) Force hard delete. Table associated with the
data set will be dropped.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_sets_delete')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'force': force
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/data_sets/{0}'.format(
*self.watson_open_scale.encode_path_vars(data_set_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
[docs]
def update(self,
data_set_id: str,
patch_document: List['PatchDocument'],
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update a data set.
Update the data set.
:param str data_set_id: ID of the data set.
:param List[PatchDocument] patch_document:
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataSetResponse` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
if patch_document is None:
raise ValueError('patch_document must be provided')
patch_document = [convert_model(x) for x in patch_document]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='data_sets_update')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(patch_document)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}'.format(
*self.watson_open_scale.encode_path_vars(data_set_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(DataSetResponse, 'from_dict'):
response.result = DataSetResponse.from_dict(response.result)
return response
#########################
# Records
#########################
class Records:
"""
Records
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a Records client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def add(self,
data_set_id: str,
request_body: Union[List[object], str, TextIO],
*,
content_type: str = None,
project_id: str = None,
space_id: str = None,
header: bool = None,
skip: int = None,
limit: int = None,
delimiter: str = None,
on_error: str = None,
csv_max_line_length: float = None,
is_historical_data: bool = None,
split_to_multi_req: bool = None,
**kwargs
) -> DetailedResponse:
"""
Add new data set records.
Add new data set records.
:param str data_set_id: ID of the data set.
:param List[object] request_body:
:param str content_type: (optional) The type of the input. A character
encoding can be specified by including a `charset` parameter. For example,
'text/csv;charset=utf-8'.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool header: (optional) if not provided service will attempt to
automatically detect header in the first line.
:param int skip: (optional) skip number of rows from input.
:param int limit: (optional) limit for number of processed input rows.
:param str delimiter: (optional) delimiter character for data provided as
csv.
:param str on_error: (optional) expected behaviour on error.
:param float csv_max_line_length: (optional) maximum length of single line
in bytes (default 10MB).
:param bool is_historical_data: (optional) specifies if the uploaded
records are part of historical data.
:param bool split_to_multi_req: (optional) when specified as true, splits
each row in CSV to multiple requests.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `Status` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
if request_body is None:
raise ValueError('request_body must be provided')
headers = {
'Content-Type': content_type
}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='records_add')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'header': header,
'skip': skip,
'limit': limit,
'delimiter': delimiter,
'on_error': on_error,
'csv_max_line_length': csv_max_line_length,
'is_historical_data': is_historical_data,
'split_to_multi_req': split_to_multi_req
}
if isinstance(request_body, list):
data = json.dumps(request_body)
if content_type is None:
headers['Content-Type'] = 'application/json'
else:
data = request_body
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}/records'.format(
*self.watson_open_scale.encode_path_vars(data_set_id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(Status, 'from_dict'):
response.result = Status.from_dict(response.result)
return response
def list(self,
data_set_id: str,
*,
project_id: str = None,
space_id: str = None,
start: datetime = None,
end: datetime = None,
limit: int = None,
offset: int = None,
includes: str = None,
annotations: List[str] = None,
exclude_annotations: bool = None,
filter: str = None,
include_total_count: bool = None,
order: str = None,
seed: float = None,
format: str = None,
binary_format: str = None,
**kwargs
) -> DetailedResponse:
"""
List data set records.
List data set records.
:param str data_set_id: ID of the data set.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param datetime start: (optional) return records with timestamp greater
then or equal to `start` parameter.
:param datetime end: (optional) return records with timestamp lower then
`end` parameter.
:param int limit: (optional) limit for number of returned records. If the
value is greater than 1000 than it will be truncated.
:param int offset: (optional) offset of returned records.
:param str includes: (optional) return records with only specified columns.
Parameter must be specified as comma separated string.
:param List[str] annotations: (optional) return record annotations with
given names.
:param bool exclude_annotations: (optional) If there is no need to fetch
annotations at all, set this parameter as true. There should be better
performance.
:param str filter: (optional) Only return records that match given filters.
There are two types of filters, separated by commas:
* normal filter (multiple are possible), {field_name}:{op}:{value} —
filter records directly
* joining filter (only a single one is possible),
{data_set_id}.{field_name}:{op}:{value} —
join a data set by transaction_id (the user must ensure it's
provided!)
and filter by this data set's records' field.
Will fail if the user hasn't provided transaction_id for both data
sets' records. Filters of different types can be mixed. They are partly
compatible with the ones in POST /v2/data_sets/{data_set_id}/distributions.
Available operators:
| op | meaning | example | code
equivalent |
|:----:|:---------------------------:|:------------------:|:------------------------:|
| eq | equality | field:eq:value | field ==
value |
| gt | greater than | field:gt:value | field >
value |
| gte | greater or equal | field:gte:value | field >=
value |
| lt | less than | field:lt:value | field <
value |
| lte | less or equal | field:lte:value | field <=
value |
| like | matching a simple pattern* | field:like:pattern |
pattern.match(field) |
| in | is contained in list | field:in:a;b;c |
[a,b,c].contains(field) |
| null | is null | field:null | field value
== null |
| nonnull | is not null | field:nonnull | field value
!= null |
* - "%" means "one or more character", "_" means "any single character",
other characters have their usual,
literal meaning (e.g. "|" means character "|").
:param bool include_total_count: (optional) If total_count should be
included. It can have performance impact if total_count is calculated.
:param str order: (optional) return records in order specified. There are
two patterns. The first is random sampling, the other is sorting per
column.
:param float seed: (optional) return repeatable result for random sampling.
Value must be between 0.0 and 1.0, inclusive. Also you can get sampled
records in pagination manner by specifying `limit` and `offset`.
:param str format: (optional) What JSON format to use on output.
:param str binary_format: (optional) Binary data presentation format. By
default, the binary field value is encoded to base64 string. If _reference_
is chosen, every binary field is moved to the _references_ section with
value set to an uri to the particular field within the record that can be
GET in a separate request.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `RecordsListResponse` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='records_list')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'start': start,
'end': end,
'limit': limit,
'offset': offset,
'includes': includes,
'annotations': convert_list(annotations),
'exclude_annotations': exclude_annotations,
'filter': filter,
'include_total_count': include_total_count,
'order': order,
'seed': seed,
'format': format,
'binary_format': binary_format
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}/records'.format(
*self.watson_open_scale.encode_path_vars(data_set_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(RecordsListResponse, 'from_dict'):
response.result = RecordsListResponse.from_dict(response.result)
return response
def patch(self,
data_set_id: str,
patch_document: List['PatchDocument'],
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update data set records.
Update data set records.
:param str data_set_id: ID of the data set.
:param List[PatchDocument] patch_document:
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `Status` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
if patch_document is None:
raise ValueError('patch_document must be provided')
patch_document = [convert_model(x) for x in patch_document]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='records_patch')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(patch_document)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}/records'.format(
*self.watson_open_scale.encode_path_vars(data_set_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(Status, 'from_dict'):
response.result = Status.from_dict(response.result)
return response
def get(self,
data_set_id: str,
record_id: str,
*,
binary_format: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get a specific data set record with the given id.
Get a specific record in a data set.
:param str data_set_id: ID of the data set.
:param str record_id: ID of the record.
:param str binary_format: (optional) Binary data presentation format. By
default, the binary field value is encoded to base64 string. If _reference_
is chosen, every binary field is moved to the _references_ section with
value set to an uri to the particular field within the record that can be
GET in a separate request.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataRecordResponse` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
if record_id is None:
raise ValueError('record_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='records_get')
headers.update(sdk_headers)
params = {
'binary_format': binary_format,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}/records/{1}'.format(
*self.watson_open_scale.encode_path_vars(data_set_id, record_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(DataRecordResponse, 'from_dict'):
response.result = DataRecordResponse.from_dict(response.result)
return response
def update(self,
data_set_id: str,
record_id: str,
patch_document: List['PatchDocument'],
*,
binary_format: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update a specific record in a data set.
Update a specific record in a data set.
:param str data_set_id: ID of the data set.
:param str record_id: ID of the record.
:param List[PatchDocument] patch_document:
:param str binary_format: (optional) Binary data presentation format. By
default, the binary field value is encoded to base64 string. If _reference_
is chosen, every binary field is moved to the _references_ section with
value set to an uri to the particular field within the record that can be
GET in a separate request.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataRecordResponse` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
if record_id is None:
raise ValueError('record_id must be provided')
if patch_document is None:
raise ValueError('patch_document must be provided')
patch_document = [convert_model(x) for x in patch_document]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='records_update')
headers.update(sdk_headers)
params = {
'binary_format': binary_format,
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(patch_document)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}/records/{1}'.format(
*self.watson_open_scale.encode_path_vars(data_set_id, record_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(DataRecordResponse, 'from_dict'):
response.result = DataRecordResponse.from_dict(response.result)
return response
def field(self,
data_set_id: str,
record_id: str,
field_name: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get value of a field in a given record.
Get value of a field in a given record.
:param str data_set_id: ID of the data set.
:param str record_id: ID of the record.
:param str field_name: field_name should map to db column name which value
is to be retrieved.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
if record_id is None:
raise ValueError('record_id must be provided')
if field_name is None:
raise ValueError('field_name must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='records_field')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/data_sets/{0}/records/{1}/{2}'.format(
*self.watson_open_scale.encode_path_vars(data_set_id, record_id, field_name))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
def query(self,
data_set_type: str,
*,
project_id: str = None,
space_id: str = None,
record_id: List[str] = None,
transaction_id: List[str] = None,
start: datetime = None,
end: datetime = None,
offset: int = None,
limit: int = None,
**kwargs
) -> DetailedResponse:
"""
Get data set records using record_id or transaction_id.
Get data set records with specific record_id or transaction_id.
:param str data_set_type: a (single) data set type.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param List[str] record_id: (optional) one or more record id values that
should be matched.
:param List[str] transaction_id: (optional) one or more transaction id
values that should be matched.
:param datetime start: (optional) beginning of the time range.
:param datetime end: (optional) end of the time range.
:param int offset: (optional) offset of returned explanations.
:param int limit: (optional) Maximum number of elements returned.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataSetRecords` result
"""
if data_set_type is None:
raise ValueError('data_set_type must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='records_query')
headers.update(sdk_headers)
params = {
'data_set_type': data_set_type,
'project_id': project_id,
'space_id': space_id,
'record_id': convert_list(record_id),
'transaction_id': convert_list(transaction_id),
'start': start,
'end': end,
'offset': offset,
'limit': limit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_set_records'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(DataSetRecords, 'from_dict'):
response.result = DataSetRecords.from_dict(response.result)
return response
#########################
# Requests
#########################
class Requests:
"""
Requests
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a Requests client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def get(self,
data_set_id: str,
request_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get status of a specific request.
Get status of a specific request.
:param str data_set_id: ID of the data set.
:param str request_id: ID of the request.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `Status` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
if request_id is None:
raise ValueError('request_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='requests_get')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}/requests/{1}'.format(
*self.watson_open_scale.encode_path_vars(data_set_id, request_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(Status, 'from_dict'):
response.result = Status.from_dict(response.result)
return response
#########################
# Distributions
#########################
class Distributions:
"""
Distributions
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a Distributions client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def add(self,
data_set_id: str,
start: str,
end: str,
dataset: str,
group: List[str],
*,
limit: float = None,
filter: str = None,
agg: List[str] = None,
max_bins: float = None,
project_id: str = None,
space_id: str = None,
nocache: bool = None,
**kwargs
) -> DetailedResponse:
"""
add new data distributions.
add new data distributions.
:param str data_set_id: ID of the data set.
:param str start: start datetime in ISO format.
:param str end: end datetime in ISO format.
:param str dataset: type of a data set.
:param List[str] group: names of columns to be grouped.
:param float limit: (optional) limit for number of rows, by default it is
50,000 (max possible limit is 50,000).
:param str filter: (optional) Filters defined by user in format:
{field_name}:{op}:{value}. Partly compatible with filters in "filter"
parameter of GET /v2/data_sets/{data_set_id}/records.
Possible filter operators:
* eq - equals (numeric, string)
* gt - greater than (numeric)
* gte - greater than or equal (numeric)
* lt - lower than (numeric)
* lte - lower than or equal (numeric)
* in - value in a set (numeric, string)
* field:null (a no-argument filter) - value is null (any nullable)
* field:exists (a no-argument filter) - value is not null (any column).
:param List[str] agg: (optional) Definition of aggregations, by default
'count'.
Aggregations can be one of:
* count
* <column_name>:sum
* <column_name>:min
* <column_name>:max
* <column_name>:avg
* <column_name>:stddev.
:param float max_bins: (optional) max number of bins which will be
generated for data.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool nocache: (optional) force columns data refresh.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataDistributionResponse` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
if start is None:
raise ValueError('start must be provided')
if end is None:
raise ValueError('end must be provided')
if dataset is None:
raise ValueError('dataset must be provided')
if group is None:
raise ValueError('group must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='distributions_add')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'nocache': nocache
}
data = {
'start': start,
'end': end,
'dataset': dataset,
'group': group,
'limit': limit,
'filter': filter,
'agg': agg,
'max_bins': max_bins
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}/distributions'.format(
*self.watson_open_scale.encode_path_vars(data_set_id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(DataDistributionResponse, 'from_dict'):
response.result = DataDistributionResponse.from_dict(response.result)
return response
def delete(self,
data_set_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Delete data distributions.
Delete data distribution.
:param str data_set_id: ID of the data set.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='distributions_delete')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/data_sets/{0}/distributions'.format(
*self.watson_open_scale.encode_path_vars(data_set_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
def get(self,
data_set_id: str,
data_distribution_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get a specific data distribution.
Get a specific data distribution.
:param str data_set_id: ID of the data set.
:param str data_distribution_id: ID of the data distribution requested to
be calculated.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataDistributionResponse` result
"""
if data_set_id is None:
raise ValueError('data_set_id must be provided')
if data_distribution_id is None:
raise ValueError('data_distribution_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='distributions_get')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/data_sets/{0}/distributions/{1}'.format(
*self.watson_open_scale.encode_path_vars(data_set_id, data_distribution_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(DataDistributionResponse, 'from_dict'):
response.result = DataDistributionResponse.from_dict(response.result)
return response
#########################
# Monitors
#########################
class Monitors:
"""
Monitors
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a Monitors client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def list(self,
*,
name: str = None,
type: str = None,
**kwargs
) -> DetailedResponse:
"""
List available monitors.
List available monitors.
:param str name: (optional) comma-separated list of names.
:param str type: (optional) Either of `service` or `user` can be specified.
`service` is corresponding to monitor definitions managed by IBM, and
`user` is corresponding to those of managed by users.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorCollections` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='monitors_list')
headers.update(sdk_headers)
params = {
'name': name,
'type': type
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_definitions'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MonitorCollections, 'from_dict'):
response.result = MonitorCollections.from_dict(response.result)
return response
def add(self,
name: str,
metrics: List['MonitorMetricRequest'],
tags: List['MonitorTagRequest'],
*,
description: str = None,
applies_to: 'ApplicabilitySelection' = None,
parameters_schema: dict = None,
managed_by: str = None,
schedule: 'MonitorInstanceSchedule' = None,
schedules: 'MonitorInstanceScheduleCollection' = None,
monitor_runtime: 'MonitorRuntime' = None,
**kwargs
) -> DetailedResponse:
"""
Add custom monitor.
Add custom monitor.
:param str name: Monitor UI label (must be unique).
:param List[MonitorMetricRequest] metrics: A list of metric definition.
:param List[MonitorTagRequest] tags: Available tags.
:param str description: (optional) Long monitoring description presented in
monitoring catalog.
:param ApplicabilitySelection applies_to: (optional)
:param dict parameters_schema: (optional) JSON schema that will be used to
validate monitoring parameters when enabled.
:param str managed_by: (optional)
:param MonitorInstanceSchedule schedule: (optional) The schedule used to
control how frequently the target is monitored. The maximum frequency is
once every 30 minutes.
Defaults to once every hour if not specified.
:param MonitorInstanceScheduleCollection schedules: (optional) A set of
schedules of online and batch deployment type. If this field is set,
schedule field is ignored.
:param MonitorRuntime monitor_runtime: (optional) Field to specify if
scheduler should be created or not.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorDisplayForm` result
"""
if name is None:
raise ValueError('name must be provided')
if metrics is None:
raise ValueError('metrics must be provided')
if tags is None:
raise ValueError('tags must be provided')
metrics = [convert_model(x) for x in metrics]
tags = [convert_model(x) for x in tags]
if applies_to is not None:
applies_to = convert_model(applies_to)
if schedule is not None:
schedule = convert_model(schedule)
if schedules is not None:
schedules = convert_model(schedules)
if monitor_runtime is not None:
monitor_runtime = convert_model(monitor_runtime)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='monitors_add')
headers.update(sdk_headers)
data = {
'name': name,
'metrics': metrics,
'tags': tags,
'description': description,
'applies_to': applies_to,
'parameters_schema': parameters_schema,
'managed_by': managed_by,
'schedule': schedule,
'schedules': schedules,
'monitor_runtime': monitor_runtime
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_definitions'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(MonitorDisplayForm, 'from_dict'):
response.result = MonitorDisplayForm.from_dict(response.result)
return response
def get(self,
monitor_definition_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get a specific monitor definition.
Get a specific monitor definition.
:param str monitor_definition_id: Unique monitor definition ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorDisplayForm` result
"""
if monitor_definition_id is None:
raise ValueError('monitor_definition_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='monitors_get')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_definitions/{0}'.format(
*self.watson_open_scale.encode_path_vars(monitor_definition_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MonitorDisplayForm, 'from_dict'):
response.result = MonitorDisplayForm.from_dict(response.result)
return response
def update(self,
monitor_definition_id: str,
name: str,
metrics: List['MonitorMetricRequest'],
tags: List['MonitorTagRequest'],
*,
description: str = None,
applies_to: 'ApplicabilitySelection' = None,
parameters_schema: dict = None,
managed_by: str = None,
schedule: 'MonitorInstanceSchedule' = None,
schedules: 'MonitorInstanceScheduleCollection' = None,
monitor_runtime: 'MonitorRuntime' = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update the monitor definition.
Update a monitor definition.
:param str monitor_definition_id: Unique monitor definition ID.
:param str name: Monitor UI label (must be unique).
:param List[MonitorMetricRequest] metrics: A list of metric definition.
:param List[MonitorTagRequest] tags: Available tags.
:param str description: (optional) Long monitoring description presented in
monitoring catalog.
:param ApplicabilitySelection applies_to: (optional)
:param dict parameters_schema: (optional) JSON schema that will be used to
validate monitoring parameters when enabled.
:param str managed_by: (optional)
:param MonitorInstanceSchedule schedule: (optional) The schedule used to
control how frequently the target is monitored. The maximum frequency is
once every 30 minutes.
Defaults to once every hour if not specified.
:param MonitorInstanceScheduleCollection schedules: (optional) A set of
schedules of online and batch deployment type. If this field is set,
schedule field is ignored.
:param MonitorRuntime monitor_runtime: (optional) Field to specify if
scheduler should be created or not.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorDisplayForm` result
"""
if monitor_definition_id is None:
raise ValueError('monitor_definition_id must be provided')
if name is None:
raise ValueError('name must be provided')
if metrics is None:
raise ValueError('metrics must be provided')
if tags is None:
raise ValueError('tags must be provided')
metrics = [convert_model(x) for x in metrics]
tags = [convert_model(x) for x in tags]
if applies_to is not None:
applies_to = convert_model(applies_to)
if schedule is not None:
schedule = convert_model(schedule)
if schedules is not None:
schedules = convert_model(schedules)
if monitor_runtime is not None:
monitor_runtime = convert_model(monitor_runtime)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='monitors_update')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = {
'name': name,
'metrics': metrics,
'tags': tags,
'description': description,
'applies_to': applies_to,
'parameters_schema': parameters_schema,
'managed_by': managed_by,
'schedule': schedule,
'schedules': schedules,
'monitor_runtime': monitor_runtime
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_definitions/{0}'.format(
*self.watson_open_scale.encode_path_vars(monitor_definition_id))
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(MonitorDisplayForm, 'from_dict'):
response.result = MonitorDisplayForm.from_dict(response.result)
return response
def patch(self,
monitor_definition_id: str,
json_patch_operation: List['JsonPatchOperation'],
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update a monitor definition.
Update a monitor definition.
:param str monitor_definition_id: Unique monitor definition ID.
:param List[JsonPatchOperation] json_patch_operation:
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorDisplayForm` result
"""
if monitor_definition_id is None:
raise ValueError('monitor_definition_id must be provided')
if json_patch_operation is None:
raise ValueError('json_patch_operation must be provided')
json_patch_operation = [convert_model(x) for x in json_patch_operation]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='monitors_patch')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(json_patch_operation)
headers['content-type'] = 'application/json-patch+json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_definitions/{0}'.format(
*self.watson_open_scale.encode_path_vars(monitor_definition_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(MonitorDisplayForm, 'from_dict'):
response.result = MonitorDisplayForm.from_dict(response.result)
return response
def delete(self,
monitor_definition_id: str,
*,
project_id: str = None,
space_id: str = None,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Delete a monitor definition.
Delete a monitor definition, backing up table specific to monitor.
:param str monitor_definition_id: Unique monitor definition ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool force: (optional) Force hard delete. Table specific to this
monitor will be dropped from data mart.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if monitor_definition_id is None:
raise ValueError('monitor_definition_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='monitors_delete')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'force': force
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/monitor_definitions/{0}'.format(
*self.watson_open_scale.encode_path_vars(monitor_definition_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
#########################
# Instances
#########################
class Instances:
"""
Instances
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a Instances client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def list(self,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
data_mart_id: str = None,
monitor_definition_id: str = None,
target_target_id: str = None,
target_target_type: str = None,
**kwargs
) -> DetailedResponse:
"""
List monitor instances.
List monitor instances.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str data_mart_id: (optional) comma-separated list of IDs.
:param str monitor_definition_id: (optional) comma-separated list of IDs.
:param str target_target_id: (optional) comma-separated list of IDs.
:param str target_target_type: (optional) comma-separated list of types.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorInstanceCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='instances_list')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'data_mart_id': data_mart_id,
'monitor_definition_id': monitor_definition_id,
'target.target_id': target_target_id,
'target.target_type': target_target_type
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MonitorInstanceCollection, 'from_dict'):
response.result = MonitorInstanceCollection.from_dict(response.result)
return response
def add(self,
data_mart_id: str,
monitor_definition_id: str,
target: 'Target',
*,
parameters: dict = None,
thresholds: List['MetricThresholdOverride'] = None,
schedule: 'MonitorInstanceSchedule' = None,
schedule_id: str = None,
managed_by: str = None,
unprocessed_records: 'RecordsCountSummary' = None,
total_records: 'MonitorInstanceTotalRecords' = None,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
skip_scheduler: bool = None,
**kwargs
) -> DetailedResponse:
"""
Create a new monitor instance.
Create a new monitor instance.
:param str data_mart_id:
:param str monitor_definition_id:
:param Target target:
:param dict parameters: (optional) Monitoring parameters consistent with
the `parameters_schema` from the monitor definition.
:param List[MetricThresholdOverride] thresholds: (optional)
:param MonitorInstanceSchedule schedule: (optional) The schedule used to
control how frequently the target is monitored. The maximum frequency is
once every 30 minutes.
Defaults to once every hour if not specified.
:param str schedule_id: (optional)
:param str managed_by: (optional)
:param RecordsCountSummary unprocessed_records: (optional) Summary about
records count.
:param MonitorInstanceTotalRecords total_records: (optional) Summary about
records count.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool skip_scheduler: (optional) prevent schedule creation for this
monitor instance.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorInstanceResponse` result
"""
if data_mart_id is None:
raise ValueError('data_mart_id must be provided')
if monitor_definition_id is None:
raise ValueError('monitor_definition_id must be provided')
if target is None:
raise ValueError('target must be provided')
target = convert_model(target)
if thresholds is not None:
thresholds = [convert_model(x) for x in thresholds]
if schedule is not None:
schedule = convert_model(schedule)
if unprocessed_records is not None:
unprocessed_records = convert_model(unprocessed_records)
if total_records is not None:
total_records = convert_model(total_records)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='instances_add')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'skip_scheduler': skip_scheduler
}
data = {
'data_mart_id': data_mart_id,
'monitor_definition_id': monitor_definition_id,
'target': target,
'parameters': parameters,
'thresholds': thresholds,
'schedule': schedule,
'schedule_id': schedule_id,
'managed_by': managed_by,
'unprocessed_records': unprocessed_records,
'total_records': total_records
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(MonitorInstanceResponse, 'from_dict'):
response.result = MonitorInstanceResponse.from_dict(response.result)
return response
def get(self,
monitor_instance_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
expand: str = None,
**kwargs
) -> DetailedResponse:
"""
Get monitor instance details.
Get monitor instance details.
:param str monitor_instance_id: Unique monitor instance ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str expand: (optional) comma-separated list of fields (supported
fields are unprocessed_records and total_records).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorInstanceResponse` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='instances_get')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'expand': expand
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances/{0}'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MonitorInstanceResponse, 'from_dict'):
response.result = MonitorInstanceResponse.from_dict(response.result)
return response
def update(self,
monitor_instance_id: str,
patch_document: List['PatchDocument'],
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
update_metadata_only: bool = None,
**kwargs
) -> DetailedResponse:
"""
Update a monitor instance.
Update a monitor instance.
:param str monitor_instance_id: Unique monitor instance ID.
:param List[PatchDocument] patch_document:
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool update_metadata_only: (optional) Flag that allows to control if
the underlying actions related to the monitor reconfiguration should be
triggered.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorInstanceResponse` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if patch_document is None:
raise ValueError('patch_document must be provided')
patch_document = [convert_model(x) for x in patch_document]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='instances_update')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'update_metadata_only': update_metadata_only
}
data = json.dumps(patch_document)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances/{0}'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(MonitorInstanceResponse, 'from_dict'):
response.result = MonitorInstanceResponse.from_dict(response.result)
return response
def delete(self,
monitor_instance_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Delete a monitor instance.
Delete a monitor instance.
:param str monitor_instance_id: Unique monitor instance ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool force: (optional) Force hard delete. All metrics for this
monitor instance will be deleted from the data mart.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='instances_delete')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'force': force
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/monitor_instances/{0}'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
#########################
# Runs
#########################
class Runs:
"""
Runs
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a Runs client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def add(self,
monitor_instance_id: str,
*,
triggered_by: str = None,
parameters: dict = None,
expiration_date: datetime = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Trigger monitoring run.
Trigger monitoring run.
:param str monitor_instance_id: Unique monitor instance ID.
:param str triggered_by: (optional) An identifier representing the source
that triggered the run request (optional). One of: event, scheduler, user,
webhook.
:param dict parameters: (optional) Monitoring parameters consistent with
the `parameters_schema` from the monitor definition.
:param datetime expiration_date: (optional) The timestamp when the
monitoring run was created with expiry date (in the format
YYYY-MM-DDTHH:mm:ssZ or YYYY-MM-DDTHH:mm:ss.sssZ, matching the date-time
format as specified by RFC 3339).
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitoringRun` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if expiration_date is not None:
expiration_date = datetime_to_string(expiration_date)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='runs_add')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = {
'triggered_by': triggered_by,
'parameters': parameters,
'expiration_date': expiration_date
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances/{0}/runs'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(MonitoringRun, 'from_dict'):
response.result = MonitoringRun.from_dict(response.result)
return response
def list(self,
monitor_instance_id: str,
*,
project_id: str = None,
space_id: str = None,
start: str = None,
limit: int = None,
**kwargs
) -> DetailedResponse:
"""
List monitoring runs.
List monitoring runs.
:param str monitor_instance_id: Unique monitor instance ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str start: (optional) The page token indicating where to start
paging from.
:param int limit: (optional) The limit of the number of items to return,
for example limit=50. If not specified a default of 100 will be used.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitoringRunCollection` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='runs_list')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'start': start,
'limit': limit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances/{0}/runs'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MonitoringRunCollection, 'from_dict'):
response.result = MonitoringRunCollection.from_dict(response.result)
return response
def get(self,
monitor_instance_id: str,
monitoring_run_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get monitoring run details.
Get monitoring run details.
:param str monitor_instance_id: Unique monitor instance ID.
:param str monitoring_run_id: Unique monitoring run ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitoringRun` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if monitoring_run_id is None:
raise ValueError('monitoring_run_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='runs_get')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances/{0}/runs/{1}'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id, monitoring_run_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MonitoringRun, 'from_dict'):
response.result = MonitoringRun.from_dict(response.result)
return response
def update(self,
monitor_instance_id: str,
monitoring_run_id: str,
json_patch_operation: List['JsonPatchOperation'],
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update existing monitoring run details.
Update existing monitoring run details.
:param str monitor_instance_id: Unique monitor instance ID.
:param str monitoring_run_id: Unique monitoring run ID.
:param List[JsonPatchOperation] json_patch_operation:
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitoringRun` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if monitoring_run_id is None:
raise ValueError('monitoring_run_id must be provided')
if json_patch_operation is None:
raise ValueError('json_patch_operation must be provided')
json_patch_operation = [convert_model(x) for x in json_patch_operation]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='runs_update')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(json_patch_operation)
headers['content-type'] = 'application/json-patch+json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances/{0}/runs/{1}'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id, monitoring_run_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(MonitoringRun, 'from_dict'):
response.result = MonitoringRun.from_dict(response.result)
return response
#########################
# Measurements
#########################
class Measurements:
"""
Measurements
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a Measurements client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def add(self,
monitor_instance_id: str,
monitor_measurement_request: List['MonitorMeasurementRequest'],
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Publish measurement data to OpenScale.
Publish measurement data to OpenScale.
:param str monitor_instance_id: Unique monitor instance ID.
:param List[MonitorMeasurementRequest] monitor_measurement_request:
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if monitor_measurement_request is None:
raise ValueError('monitor_measurement_request must be provided')
monitor_measurement_request = [convert_model(x) for x in monitor_measurement_request]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='measurements_add')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(monitor_measurement_request)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/monitor_instances/{0}/measurements'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
return response
def list(self,
monitor_instance_id: str,
start: datetime,
end: datetime,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
run_id: str = None,
filter: str = None,
limit: int = None,
offset: int = None,
**kwargs
) -> DetailedResponse:
"""
Query measurements from OpenScale DataMart.
Query measurements from OpenScale DataMart. It is required to either provide a
`start end` or `run_id` parameter.
:param str monitor_instance_id: Unique monitor instance ID.
:param datetime start: Beginning of the time range.
:param datetime end: End of the time range.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str run_id: (optional) Comma delimited list of measurement run_id.
:param str filter: (optional) Filter expression can consist of any metric
tag or a common column of string type followed by filter name and
optionally a value, all delimited by colon. Supported filters are: `in`,
`eq`, `null` and `exists`. Sample filters are:
`filter=region:in:[us,pl],segment:eq:sales` or
`filter=region:null,segment:exists`.
:param int limit: (optional) Maximum number of measurements returned.
:param int offset: (optional) Offset of measurements returned.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorMeasurementResponseCollection` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if start is None:
raise ValueError('start must be provided')
if end is None:
raise ValueError('end must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='measurements_list')
headers.update(sdk_headers)
params = {
'start': start,
'end': end,
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'run_id': run_id,
'filter': filter,
'limit': limit,
'offset': offset
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances/{0}/measurements'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MonitorMeasurementResponseCollection, 'from_dict'):
response.result = MonitorMeasurementResponseCollection.from_dict(response.result)
return response
def get(self,
monitor_instance_id: str,
measurement_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
metric_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get measurement data from OpenScale DataMart.
Get measurement data from OpenScale DataMart. If metric_id is specified, sources
associated with given metric id are filtered.
:param str monitor_instance_id: Unique monitor instance ID.
:param str measurement_id: Unique measurement ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str metric_id: (optional) Comma delimited list of metric_id.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MonitorMeasurementResponse` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if measurement_id is None:
raise ValueError('measurement_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='measurements_get')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'metric_id': metric_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances/{0}/measurements/{1}'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id, measurement_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MonitorMeasurementResponse, 'from_dict'):
response.result = MonitorMeasurementResponse.from_dict(response.result)
return response
def query(self,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
target_id: str = None,
target_type: str = None,
monitor_definition_id: str = None,
filter: str = None,
recent_count: int = None,
format: str = None,
**kwargs
) -> DetailedResponse:
"""
Query for the recent measurement.
Query for the recent measurement grouped by the monitoring target (subscription).
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str target_id: (optional) Comma separated ID of the monitoring
target (subscription).
:param str target_type: (optional) Type of the monitoring target
(subscription).
:param str monitor_definition_id: (optional) Comma separated ID of the
monitor definition.
:param str filter: (optional) Filter expression can consist of any metric
tag or a common column of string type followed by filter name and
optionally a value, all delimited by colon and prepended with
`monitor_definition_id.` string. Supported filters are: `in`, `eq`, `null`
and `exists`. Sample filters are:
`monitor_definition_id.filter=region:in:[us,pl],monitor_definition_id.segment:eq:sales`
or
`filter=monitor_definition_id.region:null,monitor_definition_id.segment:exists`.
Every monitor_definition_id can have own set of filters.
:param int recent_count: (optional) Number of measurements (per target) to
be returned.
:param str format: (optional) Format of the returned data. `full` format
compared to `compact` is additive and contains `sources` part.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MeasurementsResponseCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='measurements_query')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'target_id': target_id,
'target_type': target_type,
'monitor_definition_id': monitor_definition_id,
'filter': filter,
'recent_count': recent_count,
'format': format
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/measurements'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MeasurementsResponseCollection, 'from_dict'):
response.result = MeasurementsResponseCollection.from_dict(response.result)
return response
#########################
# Metrics
#########################
class Metrics:
"""
Metrics
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a Metrics client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def list(self,
monitor_instance_id: str,
start: datetime,
end: datetime,
agg: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
interval: str = None,
filter: str = None,
group: str = None,
**kwargs
) -> DetailedResponse:
"""
Query monitor instance metrics from OpenScale DataMart.
Query monitor instance metrics from OpenScale DataMart. See <a
href="https://github.ibm.com/aiopenscale/aios-datamart-service-api/wiki/1.3.-Metrics-Query-Language">Metrics
Query Language documentation</a>.
:param str monitor_instance_id: Unique monitor instance ID.
:param datetime start: Calculations **inclusive**, internally floored to
achieve full interval. If interval is vulnerable to time zone, the
calculated value depends on a backend db engine: PostgreSQL respects time
zone and DB2 use UTC time. Calculated value is returned in response.
:param datetime end: Calculations **exclusive**, internally ceiled to
achieve full interval. If interval is vulnerable to time zone, the
calculated value depends on a backend db engine: PostgreSQL respects time
zone and DB2 use UTC time. Calculated value is returned in response.
:param str agg: Comma delimited function list constructed from metric name
and function, e.g. `agg=metric_name:count,:last` that defines aggregations.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str interval: (optional) Time unit in which metrics are grouped and
aggregated, interval by interval.
:param str filter: (optional) Filter expression can consist of any metric
tag or a common column of string type followed by filter name and
optionally a value, all delimited by colon. Supported filters are: `in`,
`eq`, `null` and `exists`. Sample filters are:
`filter=region:in:[us,pl],segment:eq:sales` or
`filter=region:null,segment:exists`.
:param str group: (optional) Comma delimited list constructed from metric
tags, e.g. `group=region,segment` to group metrics before aggregations.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DataMartGetMonitorInstanceMetrics` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if start is None:
raise ValueError('start must be provided')
if end is None:
raise ValueError('end must be provided')
if agg is None:
raise ValueError('agg must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='metrics_list')
headers.update(sdk_headers)
params = {
'start': start,
'end': end,
'agg': agg,
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'interval': interval,
'filter': filter,
'group': group
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitor_instances/{0}/metrics'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(DataMartGetMonitorInstanceMetrics, 'from_dict'):
response.result = DataMartGetMonitorInstanceMetrics.from_dict(response.result)
return response
#########################
# AI Decision Coordinations
#########################
class AIDecisionCoordinations:
"""
AI Decision Coordinations
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a AIDecisionCoordinations client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def list(self,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
service_provider_id: str = None,
service_provider_deployment_space_id: str = None,
service_provider_integrated_project_id: str = None,
**kwargs
) -> DetailedResponse:
"""
List AI Decision Coordination.
List AI Decision Coordination.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str service_provider_id: (optional) comma-separated list of IDs.
:param str service_provider_deployment_space_id: (optional) comma-separated
list of deployment space ids (property of service provider object).
:param str service_provider_integrated_project_id: (optional)
comma-separated list of integrated project ids (property of service
provider object).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `AIDecisionCoordinationCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='ai_decision_coordinations_list')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'service_provider_id': service_provider_id,
'service_provider.deployment_space_id': service_provider_deployment_space_id,
'service_provider.integrated_project_id': service_provider_integrated_project_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/ai_decision_coordinations'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(AIDecisionCoordinationCollection, 'from_dict'):
response.result = AIDecisionCoordinationCollection.from_dict(response.result)
return response
def add(self,
service_provider_id: str,
usecase_id: str,
asset: 'Asset',
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Create a new ai decision coordination.
Create a new ai decision coordination.
:param str service_provider_id: The GUID of the Service Provider.
:param str usecase_id: The GUID of the Usecase.
:param Asset asset: asset_type must be ai_decision_coordination.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `AIDecisionCoordinationResponse` result
"""
if service_provider_id is None:
raise ValueError('service_provider_id must be provided')
if usecase_id is None:
raise ValueError('usecase_id must be provided')
if asset is None:
raise ValueError('asset must be provided')
asset = convert_model(asset)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='ai_decision_coordinations_add')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = {
'service_provider_id': service_provider_id,
'usecase_id': usecase_id,
'asset': asset
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/ai_decision_coordinations'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(AIDecisionCoordinationResponse, 'from_dict'):
response.result = AIDecisionCoordinationResponse.from_dict(response.result)
return response
def get(self,
ai_decision_coordination_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get AI Decision Coordination details.
Get AI Decision Coordination details.
:param str ai_decision_coordination_id: Unique AI Decision Coordination ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `AIDecisionCoordinationResponse` result
"""
if ai_decision_coordination_id is None:
raise ValueError('ai_decision_coordination_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='ai_decision_coordinations_get')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/ai_decision_coordinations/{0}'.format(
*self.watson_open_scale.encode_path_vars(ai_decision_coordination_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(AIDecisionCoordinationResponse, 'from_dict'):
response.result = AIDecisionCoordinationResponse.from_dict(response.result)
return response
def update(self,
ai_decision_coordination_id: str,
patch_document: List['PatchDocument'],
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update AI Decision Coordination details.
Update AI Decision Coordination details.
:param str ai_decision_coordination_id: Unique AI Decision Coordination ID.
:param List[PatchDocument] patch_document:
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `AIDecisionCoordinationResponse` result
"""
if ai_decision_coordination_id is None:
raise ValueError('ai_decision_coordination_id must be provided')
if patch_document is None:
raise ValueError('patch_document must be provided')
patch_document = [convert_model(x) for x in patch_document]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='ai_decision_coordinations_update')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(patch_document)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/ai_decision_coordinations/{0}'.format(
*self.watson_open_scale.encode_path_vars(ai_decision_coordination_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(AIDecisionCoordinationResponse, 'from_dict'):
response.result = AIDecisionCoordinationResponse.from_dict(response.result)
return response
def delete(self,
ai_decision_coordination_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Delete AI Decision Coordination details.
Delete AI Decision Coordination details.
:param str ai_decision_coordination_id: Unique AI Decision Coordination ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool force: (optional) Force hard delete. All metrics for associated
monitor instance will be deleted from the data mart.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if ai_decision_coordination_id is None:
raise ValueError('ai_decision_coordination_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='ai_decision_coordinations_delete')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'force': force
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/ai_decision_coordinations/{0}'.format(
*self.watson_open_scale.encode_path_vars(ai_decision_coordination_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
#########################
# Gen AI App
#########################
class GenAiApp:
"""
Gen AI App
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a GenAiApp client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def gen_ai_apps_list(self,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
service_provider_id: str = None,
type: str = None,
asset_asset_id: str = None,
deployment_deployment_id: str = None,
service_provider_deployment_space_id: str = None,
service_provider_integrated_project_id: str = None,
**kwargs
) -> DetailedResponse:
"""
List Gen AI App.
List Gen AI App.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str service_provider_id: (optional) comma-separated list of IDs.
:param str type: (optional) comma-separated list of type.
:param str asset_asset_id: (optional) comma-separated list of asset IDs.
:param str deployment_deployment_id: (optional) comma-separated list of
deployment IDs.
:param str service_provider_deployment_space_id: (optional) comma-separated
list of deployment space ids (property of service provider object).
:param str service_provider_integrated_project_id: (optional)
comma-separated list of integrated project ids (property of service
provider object).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `GenAIAppCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='gen_ai_apps_list')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'service_provider_id': service_provider_id,
'type': type,
'asset.asset_id': asset_asset_id,
'deployment.deployment_id': deployment_deployment_id,
'service_provider.deployment_space_id': service_provider_deployment_space_id,
'service_provider.integrated_project_id': service_provider_integrated_project_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/gen_ai_apps'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(GenAIAppCollection, 'from_dict'):
response.result = GenAIAppCollection.from_dict(response.result)
return response
def gen_ai_apps_add(self,
service_provider_id: str,
type: str,
asset: 'GenAIAppAsset',
deployment: 'GenAIAppDeployment',
*,
agent_properties: 'GenAIAppAgentProperties' = None,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Create a new gen ai app.
Create a new Gen AI App.
:param str service_provider_id: The GUID of the Service Provider.
:param str type: Type of the application.
:param GenAIAppAsset asset:
:param GenAIAppDeployment deployment:
:param GenAIAppAgentProperties agent_properties: (optional) manages
parameters to represents agentic ai characteristics.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `GenAIAppResponse` result
"""
if service_provider_id is None:
raise ValueError('service_provider_id must be provided')
if type is None:
raise ValueError('type must be provided')
if asset is None:
raise ValueError('asset must be provided')
if deployment is None:
raise ValueError('deployment must be provided')
asset = convert_model(asset)
deployment = convert_model(deployment)
if agent_properties is not None:
agent_properties = convert_model(agent_properties)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='gen_ai_apps_add')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = {
'service_provider_id': service_provider_id,
'type': type,
'asset': asset,
'deployment': deployment,
'agent_properties': agent_properties
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/gen_ai_apps'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(GenAIAppResponse, 'from_dict'):
response.result = GenAIAppResponse.from_dict(response.result)
return response
def agentic_ai_apps_get(self,
gen_ai_app_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get Gen AI App details.
Get Gen AI App details.
:param str gen_ai_app_id: Unique Gen AI App ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `GenAIAppResponse` result
"""
if gen_ai_app_id is None:
raise ValueError('gen_ai_app_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='agentic_ai_apps_get')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/gen_ai_apps/{0}'.format(
*self.watson_open_scale.encode_path_vars(gen_ai_app_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(GenAIAppResponse, 'from_dict'):
response.result = GenAIAppResponse.from_dict(response.result)
return response
def agentic_ai_apps_update(self,
gen_ai_app_id: str,
patch_document: List['PatchDocument'],
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update Gen AI App details.
Update Gen AI App details.
:param str gen_ai_app_id: Unique Gen AI App ID.
:param List[PatchDocument] patch_document:
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `GenAIAppResponse` result
"""
if gen_ai_app_id is None:
raise ValueError('gen_ai_app_id must be provided')
if patch_document is None:
raise ValueError('patch_document must be provided')
patch_document = [convert_model(x) for x in patch_document]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='agentic_ai_apps_update')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(patch_document)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/gen_ai_apps/{0}'.format(
*self.watson_open_scale.encode_path_vars(gen_ai_app_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(GenAIAppResponse, 'from_dict'):
response.result = GenAIAppResponse.from_dict(response.result)
return response
def agentic_ai_apps_delete(self,
gen_ai_app_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
force: bool = None,
**kwargs
) -> DetailedResponse:
"""
Delete Gen AI App details.
Delete Gen AI App details.
:param str gen_ai_app_id: Unique Gen AI App ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param bool force: (optional) Force hard delete. All metrics for associated
monitor instance will be deleted from the data mart.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if gen_ai_app_id is None:
raise ValueError('gen_ai_app_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='agentic_ai_apps_delete')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'force': force
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/gen_ai_apps/{0}'.format(
*self.watson_open_scale.encode_path_vars(gen_ai_app_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
#########################
# Integrated Systems
#########################
class IntegratedSystems:
"""
Integrated Systems
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a IntegratedSystems client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
[docs]
def list(self,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
type: str = None,
service_provider_id: str = None,
**kwargs
) -> DetailedResponse:
"""
List integrated systems.
List integrated systems.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str type: (optional) comma-separated list of type for the integrated
system.
:param str service_provider_id: (optional) comma-separated list of IDs to
filter.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `IntegratedSystemCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='integrated_systems_list')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id,
'type': type,
'service_provider_id': service_provider_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/integrated_systems'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(IntegratedSystemCollection, 'from_dict'):
response.result = IntegratedSystemCollection.from_dict(response.result)
return response
def add(self,
name: str,
type: str,
description: str,
credentials: dict,
*,
connection: object = None,
service_provider_id: str = None,
group_ids: List[str] = None,
user_ids: List[str] = None,
parameters: object = None,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Create a new integrated system.
Create a new integrated system.
:param str name: The name of the Integrated System.
:param str type:
:param str description: The description of the Integrated System.
:param dict credentials: The credentials for the Integrated System.
:param object connection: (optional) The additional connection information
for the Integrated System.
:param str service_provider_id: (optional) The GUID of the Service
Provider. Should be specified when the integrated system should be managed
with access contorl over combination of container_id and container_type
query params.
:param List[str] group_ids: (optional) Access control list of group id of
Cloud Pak for Data (Only available for open_pages type and OpenScale on
Cloud Pak for Data >= 4.0.6 with ENABLE_GROUP_AUTH being true).
:param List[str] user_ids: (optional) Access control list of user id of
Cloud Pak for Data (Only available for open_pages type and OpenScale on
Cloud Pak for Data >= 4.0.6 with ENABLE_GROUP_AUTH being true).
:param object parameters: (optional) Additional parameters.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `IntegratedSystemResponse` result
"""
if name is None:
raise ValueError('name must be provided')
if type is None:
raise ValueError('type must be provided')
if description is None:
raise ValueError('description must be provided')
if credentials is None:
raise ValueError('credentials must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='integrated_systems_add')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = {
'name': name,
'type': type,
'description': description,
'credentials': credentials,
'connection': connection,
'service_provider_id': service_provider_id,
'group_ids': group_ids,
'user_ids': user_ids,
'parameters': parameters
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/integrated_systems'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(IntegratedSystemResponse, 'from_dict'):
response.result = IntegratedSystemResponse.from_dict(response.result)
return response
def get(self,
integrated_system_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get a specific integrated system.
Get a specific integrated system.
:param str integrated_system_id: Unique integrated system ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `IntegratedSystemResponse` result
"""
if integrated_system_id is None:
raise ValueError('integrated_system_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='integrated_systems_get')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/integrated_systems/{0}'.format(
*self.watson_open_scale.encode_path_vars(integrated_system_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(IntegratedSystemResponse, 'from_dict'):
response.result = IntegratedSystemResponse.from_dict(response.result)
return response
def update(self,
integrated_system_id: str,
json_patch_operation: List['JsonPatchOperation'],
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Update an integrated system.
Update an integrated system.
:param str integrated_system_id: Unique integrated system ID.
:param List[JsonPatchOperation] json_patch_operation:
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `IntegratedSystemResponse` result
"""
if integrated_system_id is None:
raise ValueError('integrated_system_id must be provided')
if json_patch_operation is None:
raise ValueError('json_patch_operation must be provided')
json_patch_operation = [convert_model(x) for x in json_patch_operation]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='integrated_systems_update')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
data = json.dumps(json_patch_operation)
headers['content-type'] = 'application/json-patch+json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/integrated_systems/{0}'.format(
*self.watson_open_scale.encode_path_vars(integrated_system_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(IntegratedSystemResponse, 'from_dict'):
response.result = IntegratedSystemResponse.from_dict(response.result)
return response
def delete(self,
integrated_system_id: str,
*,
container_type: str = None,
container_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Delete an integrated system.
Delete an integrated system.
:param str integrated_system_id: Unique integrated system ID.
:param str container_type: (optional) Type of container. One of project,
space and wxo. Must be used with `container_id` together.
:param str container_id: (optional) The GUID of the specified container.
Must be used with `container_type` together.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if integrated_system_id is None:
raise ValueError('integrated_system_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='integrated_systems_delete')
headers.update(sdk_headers)
params = {
'container_type': container_type,
'container_id': container_id,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/integrated_systems/{0}'.format(
*self.watson_open_scale.encode_path_vars(integrated_system_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
#########################
# Operational Spaces
#########################
class OperationalSpaces:
"""
Operational Spaces
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a OperationalSpaces client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def list(self,
**kwargs
) -> DetailedResponse:
"""
List Operational Spaces.
List Operational Spaces.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `OperationalSpaceCollection` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='operational_spaces_list')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/operational_spaces'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers)
response = self.watson_open_scale.send(request)
if hasattr(OperationalSpaceCollection, 'from_dict'):
response.result = OperationalSpaceCollection.from_dict(response.result)
return response
def add(self,
name: str,
*,
description: str = None,
**kwargs
) -> DetailedResponse:
"""
Create an operational space.
Create an operational space.
:param str name: The name of the Operational Space.
:param str description: (optional) The description of the Operational
Space.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `OperationalSpaceResponse` result
"""
if name is None:
raise ValueError('name must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='operational_spaces_add')
headers.update(sdk_headers)
data = {
'name': name,
'description': description
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/operational_spaces'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(OperationalSpaceResponse, 'from_dict'):
response.result = OperationalSpaceResponse.from_dict(response.result)
return response
def get(self,
operational_space_id: str,
**kwargs
) -> DetailedResponse:
"""
Get an operational space.
Get an operational space.
:param str operational_space_id: Unique Operational Space ID.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `OperationalSpaceResponse` result
"""
if operational_space_id is None:
raise ValueError('operational_space_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='operational_spaces_get')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/operational_spaces/{0}'.format(
*self.watson_open_scale.encode_path_vars(operational_space_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers)
response = self.watson_open_scale.send(request)
if hasattr(OperationalSpaceResponse, 'from_dict'):
response.result = OperationalSpaceResponse.from_dict(response.result)
return response
def update(self,
operational_space_id: str,
json_patch_operation: List['JsonPatchOperation'],
**kwargs
) -> DetailedResponse:
"""
Update an operational space.
Update an operational space.
:param str operational_space_id: Unique Operational Space ID.
:param List[JsonPatchOperation] json_patch_operation:
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `OperationalSpaceResponse` result
"""
if operational_space_id is None:
raise ValueError('operational_space_id must be provided')
if json_patch_operation is None:
raise ValueError('json_patch_operation must be provided')
json_patch_operation = [convert_model(x) for x in json_patch_operation]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='operational_spaces_update')
headers.update(sdk_headers)
data = json.dumps(json_patch_operation)
headers['content-type'] = 'application/json-patch+json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/operational_spaces/{0}'.format(
*self.watson_open_scale.encode_path_vars(operational_space_id))
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(OperationalSpaceResponse, 'from_dict'):
response.result = OperationalSpaceResponse.from_dict(response.result)
return response
def delete(self,
operational_space_id: str,
**kwargs
) -> DetailedResponse:
"""
Delete an operational space.
Delete an operational space.
:param str operational_space_id: Unique Operational Space ID.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if operational_space_id is None:
raise ValueError('operational_space_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='operational_spaces_delete')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/operational_spaces/{0}'.format(
*self.watson_open_scale.encode_path_vars(operational_space_id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers)
response = self.watson_open_scale.send(request)
return response
#########################
# User Preferences
#########################
class UserPreferences:
"""
User Preferences
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a UserPreferences client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def list(self,
**kwargs
) -> DetailedResponse:
"""
Get User Preferences.
Get User Preferences.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='user_preferences_list')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/user_preferences'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers)
response = self.watson_open_scale.send(request)
return response
def patch(self,
json_patch_operation: List['JsonPatchOperation'],
**kwargs
) -> DetailedResponse:
"""
Update User Preferences.
Update User Preferences.
:param List[JsonPatchOperation] json_patch_operation:
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if json_patch_operation is None:
raise ValueError('json_patch_operation must be provided')
json_patch_operation = [convert_model(x) for x in json_patch_operation]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='user_preferences_patch')
headers.update(sdk_headers)
data = json.dumps(json_patch_operation)
headers['content-type'] = 'application/json-patch+json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/user_preferences'
request = self.watson_open_scale.prepare_request(method='PATCH',
url=url,
headers=headers,
data=data)
response = self.watson_open_scale.send(request)
return response
def get(self,
user_preference_key: str,
**kwargs
) -> DetailedResponse:
"""
Get a specific user preference.
Get a specific user preference.
:param str user_preference_key: key in user preferences.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `UserPreferencesGetResponse` result
"""
if user_preference_key is None:
raise ValueError('user_preference_key must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='user_preferences_get')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/user_preferences/{0}'.format(
*self.watson_open_scale.encode_path_vars(user_preference_key))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers)
response = self.watson_open_scale.send(request)
if hasattr(UserPreferencesGetResponse, 'from_dict'):
response.result = UserPreferencesGetResponse.from_dict(response.result)
return response
def update(self,
user_preference_key: str,
user_preferences_update_request: 'UserPreferencesUpdateRequest',
**kwargs
) -> DetailedResponse:
"""
Update the user preference.
Update the user preference.
:param str user_preference_key: key in user preferences.
:param UserPreferencesUpdateRequest user_preferences_update_request:
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if user_preference_key is None:
raise ValueError('user_preference_key must be provided')
if user_preferences_update_request is None:
raise ValueError('user_preferences_update_request must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='user_preferences_update')
headers.update(sdk_headers)
data = json.dumps(user_preferences_update_request)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/user_preferences/{0}'.format(
*self.watson_open_scale.encode_path_vars(user_preference_key))
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
data=data)
response = self.watson_open_scale.send(request)
return response
def delete(self,
user_preference_key: str,
**kwargs
) -> DetailedResponse:
"""
Delete the user preference.
Delete the user preference.
:param str user_preference_key: key in user preferences.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if user_preference_key is None:
raise ValueError('user_preference_key must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='user_preferences_delete')
headers.update(sdk_headers)
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/user_preferences/{0}'.format(
*self.watson_open_scale.encode_path_vars(user_preference_key))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers)
response = self.watson_open_scale.send(request)
return response
#########################
# Explanation Tasks
#########################
class ExplanationTasks:
"""
Explanation Tasks
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a ExplanationTasks client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def add(self,
*,
scoring_ids: List[str] = None,
input_rows: List[dict] = None,
explanation_types: List[str] = None,
subscription_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Compute explanations.
Submit tasks for computing explanation of predictions.
:param List[str] scoring_ids: (optional) IDs of the scoring transaction.
:param List[dict] input_rows: (optional) List of scoring transactions.
:param List[str] explanation_types: (optional) Types of explanations to
generate.
:param str subscription_id: (optional) Unique subscription ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `PostExplanationTaskResponse` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='explanation_tasks_add')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = {
'scoring_ids': scoring_ids,
'input_rows': input_rows,
'explanation_types': explanation_types,
'subscription_id': subscription_id
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/explanation_tasks'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(PostExplanationTaskResponse, 'from_dict'):
response.result = PostExplanationTaskResponse.from_dict(response.result)
return response
def list(self,
subscription_id: str,
*,
project_id: str = None,
space_id: str = None,
offset: int = None,
limit: int = None,
scoring_id: str = None,
status: str = None,
**kwargs
) -> DetailedResponse:
"""
List all explanations.
List of all the computed explanations.
:param str subscription_id: Unique subscription ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param int offset: (optional) offset of the explanations to return.
:param int limit: (optional) Maximum number of explanations to return.
:param str scoring_id: (optional) ID of the scoring transaction.
:param str status: (optional) Status of the explanation task.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `GetExplanationTasksResponse` result
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='explanation_tasks_list')
headers.update(sdk_headers)
params = {
'subscription_id': subscription_id,
'project_id': project_id,
'space_id': space_id,
'offset': offset,
'limit': limit,
'scoring_id': scoring_id,
'status': status
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/explanation_tasks'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(GetExplanationTasksResponse, 'from_dict'):
response.result = GetExplanationTasksResponse.from_dict(response.result)
return response
def get(self,
explanation_task_id: str,
*,
subscription_id: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get explanation.
Get explanation for the given explanation task id.
:param str explanation_task_id: ID of the explanation task.
:param str subscription_id: (optional) Unique subscription ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `GetExplanationTaskResponse` result
"""
if explanation_task_id is None:
raise ValueError('explanation_task_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='explanation_tasks_get')
headers.update(sdk_headers)
params = {
'subscription_id': subscription_id,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/explanation_tasks/{0}'.format(
*self.watson_open_scale.encode_path_vars(explanation_task_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(GetExplanationTaskResponse, 'from_dict'):
response.result = GetExplanationTaskResponse.from_dict(response.result)
return response
#########################
# Drift v2 Service
#########################
class DriftV2Service:
"""
Drift v2 Service
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a DriftV2Service client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def download_drift_v2_archive_metadata(self,
subscription_id: str,
*,
project_id: str = None,
space_id: str = None,
archive_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get drift archive metadata for a given subscription.
:param str subscription_id: The id of the subscription.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str archive_id: (optional) The id of the archive to be downloaded.
It will download the latest baseline archive by default.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='download_drift_v2_archive_metadata')
headers.update(sdk_headers)
params = {
'subscription_id': subscription_id,
'project_id': project_id,
'space_id': space_id,
'archive_id': archive_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/monitoring_services/drift_v2/archives'
request = self.watson_open_scale.prepare_request(method='HEAD',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
def upload_drift_v2_archive(self,
subscription_id: str,
body: BinaryIO,
*,
project_id: str = None,
space_id: str = None,
archive_name: str = None,
**kwargs
) -> DetailedResponse:
"""
Upload drift_v2 archive for a given subscription.
This API is used to upload the drift_v2 archive necessary to configure the Drift
v2 monitor.
:param str subscription_id: The id of the subscription.
:param BinaryIO body:
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str archive_name: (optional) The name of the archive being uploaded.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
if body is None:
raise ValueError('body must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='upload_drift_v2_archive')
headers.update(sdk_headers)
params = {
'subscription_id': subscription_id,
'project_id': project_id,
'space_id': space_id,
'archive_name': archive_name
}
data = body
headers['content-type'] = 'application/octet-stream'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/monitoring_services/drift_v2/archives'
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
return response
def download_drift_v2_archive(self,
subscription_id: str,
*,
project_id: str = None,
space_id: str = None,
archive_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Get drift v2 archive for a given subscription.
This API is used to download the drift_v2 Archives.
:param str subscription_id: The id of the subscription.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str archive_id: (optional) The id of the archive to be downloaded.
It will download the latest baseline archive by default.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='download_drift_v2_archive')
headers.update(sdk_headers)
params = {
'subscription_id': subscription_id,
'project_id': project_id,
'space_id': space_id,
'archive_id': archive_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/octet-stream'
url = '/v2/monitoring_services/drift_v2/archives'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
#########################
# Drift Service
#########################
class DriftService:
"""
Drift Service
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a DriftService client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def drift_archive_head(self,
monitor_instance_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Retrieves the Drift archive metadata.
API to retrieve the Drift archive metadata.
:param str monitor_instance_id: Unique monitor instance ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='drift_archive_head')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/monitoring_services/drift/monitor_instances/{0}/archives'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='HEAD',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
def drift_archive_post(self,
data_mart_id: str,
subscription_id: str,
body: BinaryIO,
*,
project_id: str = None,
space_id: str = None,
archive_name: str = None,
enable_data_drift: bool = None,
enable_model_drift: bool = None,
**kwargs
) -> DetailedResponse:
"""
Upload Drift archives.
API to upload drift archive such as the Drift Detection Model.
:param str data_mart_id: ID of the data mart.
:param str subscription_id: Unique subscription ID.
:param BinaryIO body:
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str archive_name: (optional) The name of the archive being uploaded.
:param bool enable_data_drift: (optional) Flag to enable/disable data
drift.
:param bool enable_model_drift: (optional) Flag to enable/disable model
drift.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if data_mart_id is None:
raise ValueError('data_mart_id must be provided')
if subscription_id is None:
raise ValueError('subscription_id must be provided')
if body is None:
raise ValueError('body must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='drift_archive_post')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'archive_name': archive_name,
'enable_data_drift': enable_data_drift,
'enable_model_drift': enable_model_drift
}
data = body
headers['content-type'] = 'application/octet-stream'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/monitoring_services/drift/data_marts/{0}/subscriptions/{1}/archives'.format(
*self.watson_open_scale.encode_path_vars(data_mart_id, subscription_id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
return response
def drift_archive_get(self,
monitor_instance_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Retrieves the Drift archives.
API to retrieve the Drift archives.
:param str monitor_instance_id: Unique monitor instance ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='drift_archive_get')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/octet-stream'
url = '/v2/monitoring_services/drift/monitor_instances/{0}/archives'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
#########################
# Explainability Service
#########################
class ExplainabilityService:
"""
Explainability Service
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a ExplainabilityService client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def explainability_archive_put(self,
subscription_id: str,
body: BinaryIO,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Upload explainability configuration archive.
API to upload explainability configuration archive containing the explainability
artifacts. The api can also be used to update the archive.
:param str subscription_id: Unique subscription ID.
:param BinaryIO body:
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
if body is None:
raise ValueError('body must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='explainability_archive_put')
headers.update(sdk_headers)
params = {
'subscription_id': subscription_id,
'project_id': project_id,
'space_id': space_id
}
data = body
headers['content-type'] = 'application/octet-stream'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/monitoring_services/explainability/archives'
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
return response
def explainability_archive_post(self,
subscription_id: str,
body: BinaryIO,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Upload explainability configuration archive.
API to upload explainability configuration archive containing the explainability
artifacts. The api can also be used to update the archive.
:param str subscription_id: Unique subscription ID.
:param BinaryIO body:
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
if body is None:
raise ValueError('body must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='explainability_archive_post')
headers.update(sdk_headers)
params = {
'subscription_id': subscription_id,
'project_id': project_id,
'space_id': space_id
}
data = body
headers['content-type'] = 'application/octet-stream'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/monitoring_services/explainability/archives'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
return response
def explainability_archive_get(self,
subscription_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Download the Explainability configuration archive.
API to download the Explainability archive.
:param str subscription_id: Unique subscription ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='explainability_archive_get')
headers.update(sdk_headers)
params = {
'subscription_id': subscription_id,
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/octet-stream'
url = '/v2/monitoring_services/explainability/archives'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
#########################
# Schema Utility
#########################
class SchemaUtility:
"""
Schema Utility
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a SchemaUtility client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def spark_schemas_post(self,
body: Union[str, TextIO],
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Parse a given file and extract the schema in Spark StructType format.
API to consume a file such as CSV and returns the schema in Spark StructType
format.
:param str body:
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `SparkStruct` result
"""
if body is None:
raise ValueError('body must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='spark_schemas_post')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = body
headers['content-type'] = 'text/csv'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/spark_schemas'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(SparkStruct, 'from_dict'):
response.result = SparkStruct.from_dict(response.result)
return response
#########################
# Model Risk Management
#########################
class ModelRiskManagement:
"""
Model Risk Management
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a ModelRiskManagement client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
[docs]
def mrm_risk_evaluations(self,
monitor_instance_id: str,
*,
unknown_base_type: Union[object, str, TextIO] = None,
content_type: str = None,
project_id: str = None,
space_id: str = None,
test_data_set_name: str = None,
publish_metrics: str = None,
publish_lineage: str = None,
publish_fact: str = None,
includes_model_output: str = None,
delimiter: str = None,
evaluation_tests: str = None,
**kwargs
) -> DetailedResponse:
"""
Uploads the test data and triggers a monitor run for risk evaluation.
Uploads the test data and triggers a monitor run for risk evaluation.
:param str monitor_instance_id: The monitor instance ID.
:param UNKNOWN_BASE_TYPE unknown_base_type: (optional)
:param str content_type: (optional) The type of the input. A character
encoding can be specified by including a `charset` parameter. For example,
'text/csv;charset=utf-8'.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str test_data_set_name: (optional) The name of the test CSV file
being uploaded.
:param str publish_metrics: (optional) Flag to decide whether to send
evaluated metrics to OpenPages.
:param str publish_lineage: (optional) Flag to decide whether a lineage
event should be published to an integrated system.
:param str publish_fact: (optional) Flag to decide whether Fact metadata
should be published to an integrated system.
:param str includes_model_output: (optional) Boolean flag to indicate
whether the data being uploaded contains scored output or not.
:param str delimiter: (optional) The delimiter to be used for CSV/Dynamic
CSV files.
:param str evaluation_tests: (optional) Comma separated list of monitor
tests to run.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `PostRiskEvaluationsResponse` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {
'Content-Type': content_type
}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_risk_evaluations')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'test_data_set_name': test_data_set_name,
'publish_metrics': publish_metrics,
'publish_lineage': publish_lineage,
'publish_fact': publish_fact,
'includes_model_output': includes_model_output,
'delimiter': delimiter,
'evaluation_tests': evaluation_tests
}
if unknown_base_type is not None and isinstance(unknown_base_type, dict):
data = json.dumps(unknown_base_type)
if content_type is None:
headers['Content-Type'] = 'application/json'
else:
data = unknown_base_type
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitoring_services/mrm/monitor_instances/{0}/risk_evaluations'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(PostRiskEvaluationsResponse, 'from_dict'):
response.result = PostRiskEvaluationsResponse.from_dict(response.result)
return response
[docs]
def mrm_put_risk_evaluation(self,
monitor_instance_id: str,
*,
cancel_run: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Cancels the risk evaluations run.
Cancels the risk evaluations run.
:param str monitor_instance_id: The monitor instance ID.
:param str cancel_run: (optional)
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `RiskEvaluationResponse` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_put_risk_evaluation')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = {
'cancel_run': cancel_run
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitoring_services/mrm/monitor_instances/{0}/risk_evaluations'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(RiskEvaluationResponse, 'from_dict'):
response.result = RiskEvaluationResponse.from_dict(response.result)
return response
[docs]
def mrm_get_risk_evaluation(self,
monitor_instance_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Returns the status of the risk evaluation.
Returns the status of the risk evaluation.
:param str monitor_instance_id: The monitor instance ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `RiskEvaluationResponse` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_get_risk_evaluation')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitoring_services/mrm/monitor_instances/{0}/risk_evaluations'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(RiskEvaluationResponse, 'from_dict'):
response.result = RiskEvaluationResponse.from_dict(response.result)
return response
[docs]
def mrm_publish_metrics(self,
monitor_instance_id: str,
monitoring_run_id: str,
*,
metrics: List['IntegratedSystemMetricsArray'] = None,
send_report: bool = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Publishes the chosen metrics to the integrated system reference.
Publishes the chosen metrics to the integrated system reference.
:param str monitor_instance_id: The monitor instance ID.
:param str monitoring_run_id: The monitoring run ID.
:param List[IntegratedSystemMetricsArray] metrics: (optional)
:param bool send_report: (optional)
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if monitoring_run_id is None:
raise ValueError('monitoring_run_id must be provided')
if metrics is not None:
metrics = [convert_model(x) for x in metrics]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_publish_metrics')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = {
'metrics': metrics,
'send_report': send_report
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitoring_services/mrm/monitor_instances/{0}/runs/{1}/integrated_system_metrics'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id, monitoring_run_id))
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
return response
[docs]
def mrm_download_report(self,
monitor_instance_id: str,
monitoring_run_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Returns the risk evaluation report in a PDF format.
Returns the risk evaluation report in a PDF format.
:param str monitor_instance_id: The monitor instance ID.
:param str monitoring_run_id: The monitoring run ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `BinaryIO` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
if monitoring_run_id is None:
raise ValueError('monitoring_run_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_download_report')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/pdf'
url = '/v2/monitoring_services/mrm/monitor_instances/{0}/runs/{1}/risk_evaluation_report'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id, monitoring_run_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
[docs]
def mrm_get_all_sub_risk_evaluation_status(self,
*,
project_id: str = None,
space_id: str = None,
data_mart_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Returns the risk evaluation status of all subscriptions in a given service instance.
Returns the risk evaluation status of all subscriptions in a given service
instance.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str data_mart_id: (optional) The data mart ID.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `MrmGetRiskEvaluationStatusEntity` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_get_all_sub_risk_evaluation_status')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'data_mart_id': data_mart_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/subscriptions/risk_evaluation_status'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(MrmGetRiskEvaluationStatusEntity, 'from_dict'):
response.result = MrmGetRiskEvaluationStatusEntity.from_dict(response.result)
return response
[docs]
def mrm_update_risk_evaluation_status(self,
subscription_id: str,
*,
state: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Updates the risk evaluation status for the given subscription.
Updates the risk evaluation status for the given subscription.
:param str subscription_id: The subscription ID.
:param str state: (optional)
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_update_risk_evaluation_status')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = {
'state': state
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/subscriptions/{0}/risk_evaluation_status'.format(
*self.watson_open_scale.encode_path_vars(subscription_id))
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
return response
[docs]
def mrm_get_risk_evaluation_status(self,
subscription_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Gets risk evaluation status for the given subscription.
Gets risk evaluation status for the given subscription.
:param str subscription_id: The subscription ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if subscription_id is None:
raise ValueError('subscription_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_get_risk_evaluation_status')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/v2/subscriptions/{0}/risk_evaluation_status'.format(
*self.watson_open_scale.encode_path_vars(subscription_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
[docs]
def mrm_start_ai_setup(self,
operational_space_id: str,
*,
monitors: List['AISetupMonitor'] = None,
project_id: str = None,
space_id: str = None,
deployment_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Performs the setup activities in Watson X.Governance for a given AI service.
Performs the service provider creation, gen_ai_app creation, data model creation
and monitors configuration for the given AI service.
:param str operational_space_id: The rank of the environment in which the
monitoring is happening. Accepted values are `development`,
`pre_production`, and `production`.
:param List[AISetupMonitor] monitors: (optional) The list of monitors to be
configured for the AI service.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str deployment_id: (optional) The GUID of the deployment.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `AISetupResponse` result
"""
if operational_space_id is None:
raise ValueError('operational_space_id must be provided')
if monitors is not None:
monitors = [convert_model(x) for x in monitors]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_start_ai_setup')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'deployment_id': deployment_id
}
data = {
'operational_space_id': operational_space_id,
'monitors': monitors
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/ai_setup'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(AISetupResponse, 'from_dict'):
response.result = AISetupResponse.from_dict(response.result)
return response
[docs]
def mrm_get_ai_setup(self,
*,
project_id: str = None,
space_id: str = None,
deployment_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Gets the status of the AI setup for the given AI service.
Gets the status of the AI setup for the given AI service.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str deployment_id: (optional) The GUID of the deployment.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `AISetupResponse` result
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_get_ai_setup')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id,
'deployment_id': deployment_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/ai_setup'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(AISetupResponse, 'from_dict'):
response.result = AISetupResponse.from_dict(response.result)
return response
[docs]
def mrm_start_prompt_setup(self,
prompt_template_asset_id: str,
label_column: str,
operational_space_id: str,
problem_type: str,
input_data_type: str,
*,
data_input_locale: List[str] = None,
generated_output_locale: List[str] = None,
context_fields: List[str] = None,
question_field: str = None,
meta_fields: List['PromptSetupMetaField'] = None,
data_properties: List['PromptSetupDataProperties'] = None,
monitors: 'PromptSetupRequestMonitors' = None,
project_id: str = None,
space_id: str = None,
deployment_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Performs the setup activities in Openscale for a given prompt template asset.
Performs the service provider creation, subscription creation and monitors
configuration for the given prompt template asset.
:param str prompt_template_asset_id: The GUID of the prompt template asset.
:param str label_column: The name of the column containing the reference
output.
:param str operational_space_id: The rank of the environment in which the
monitoring is happening. Accepted values are `development`,
`pre_production`, `production`.
:param str problem_type: The task type to monitor for the given prompt
template asset.
:param str input_data_type: The input data type.
:param List[str] data_input_locale: (optional) represents a list of
language-code LLM can handle.
:param List[str] generated_output_locale: (optional) represents a list of
language-code LLM can handle.
:param List[str] context_fields: (optional) The list of prompt variables
containing the context. Applicable only for Retrieval-Augmented Generation
problem type.
:param str question_field: (optional) The prompt variable containing the
question. Applicable only for Retrieval-Augmented Generation problem type.
:param List[PromptSetupMetaField] meta_fields: (optional) The list of
meta-fields for the prompt.
:param List[PromptSetupDataProperties] data_properties: (optional) Contains
metadata about the data that will flow through the prompt template.
:param PromptSetupRequestMonitors monitors: (optional) The list of monitors
to be configured for the prompt template.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str deployment_id: (optional) The GUID of the deployment.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `PromptSetupResponse` result
"""
if prompt_template_asset_id is None:
raise ValueError('prompt_template_asset_id must be provided')
if label_column is None:
raise ValueError('label_column must be provided')
if operational_space_id is None:
raise ValueError('operational_space_id must be provided')
if problem_type is None:
raise ValueError('problem_type must be provided')
if input_data_type is None:
raise ValueError('input_data_type must be provided')
if meta_fields is not None:
meta_fields = [convert_model(x) for x in meta_fields]
if data_properties is not None:
data_properties = [convert_model(x) for x in data_properties]
if monitors is not None:
monitors = convert_model(monitors)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_start_prompt_setup')
headers.update(sdk_headers)
params = {
'prompt_template_asset_id': prompt_template_asset_id,
'project_id': project_id,
'space_id': space_id,
'deployment_id': deployment_id
}
data = {
'label_column': label_column,
'operational_space_id': operational_space_id,
'problem_type': problem_type,
'input_data_type': input_data_type,
'data_input_locale': data_input_locale,
'generated_output_locale': generated_output_locale,
'context_fields': context_fields,
'question_field': question_field,
'meta_fields': meta_fields,
'data_properties': data_properties,
'monitors': monitors
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/prompt_setup'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(PromptSetupResponse, 'from_dict'):
response.result = PromptSetupResponse.from_dict(response.result)
return response
[docs]
def mrm_get_prompt_setup(self,
prompt_template_asset_id: str,
*,
project_id: str = None,
space_id: str = None,
deployment_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Gets the status of the prompt setup for the given prompt template asset.
Gets the status of the prompt setup for the given prompt template asset.
:param str prompt_template_asset_id: The GUID of the prompt template asset.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param str deployment_id: (optional) The GUID of the deployment.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `PromptSetupResponse` result
"""
if prompt_template_asset_id is None:
raise ValueError('prompt_template_asset_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_get_prompt_setup')
headers.update(sdk_headers)
params = {
'prompt_template_asset_id': prompt_template_asset_id,
'project_id': project_id,
'space_id': space_id,
'deployment_id': deployment_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/prompt_setup'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(PromptSetupResponse, 'from_dict'):
response.result = PromptSetupResponse.from_dict(response.result)
return response
[docs]
def mrm_update_notification_preferences(self,
monitor_instance_id: str,
*,
notification_enabled: bool = None,
notification_frequency: str = None,
notification_emails: List[str] = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Sets the users email notification preference in the MRM monitor instance of a given model subscription.
Sets the users email notification preference in the MRM monitor instance of a
given model subscription.
:param str monitor_instance_id: The monitor instance ID.
:param bool notification_enabled: (optional)
:param str notification_frequency: (optional)
:param List[str] notification_emails: (optional)
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `RiskNotificationPreferencesResponse` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_update_notification_preferences')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
data = {
'notification_enabled': notification_enabled,
'notification_frequency': notification_frequency,
'notification_emails': notification_emails
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitoring_services/mrm/monitor_instances/{0}/risk_notifications'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(RiskNotificationPreferencesResponse, 'from_dict'):
response.result = RiskNotificationPreferencesResponse.from_dict(response.result)
return response
[docs]
def mrm_get_notification_preferences(self,
monitor_instance_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Gets the users email notification preferences for a given model subscription.
Gets the users email notification preferences for a given model subscription.
:param str monitor_instance_id: The monitor instance ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `RiskNotificationPreferencesResponse` result
"""
if monitor_instance_id is None:
raise ValueError('monitor_instance_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='mrm_get_notification_preferences')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/monitoring_services/mrm/monitor_instances/{0}/risk_notifications'.format(
*self.watson_open_scale.encode_path_vars(monitor_instance_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(RiskNotificationPreferencesResponse, 'from_dict'):
response.result = RiskNotificationPreferencesResponse.from_dict(response.result)
return response
#########################
# WX Agentic Service
#########################
class WXAgenticService:
"""
WX Agentic Service
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a WXAgenticService client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def post_upload_traces_for_gen_ai_app(self,
gen_ai_app_id: str,
*,
traces_file: BinaryIO = None,
traces_file_content_type: str = None,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Uploads the traces given in the archive to the respective data-sets after processing them.
Accepts an archive containing JSONs of traces in OTEL format.
:param str gen_ai_app_id: Unique Gen AI App ID.
:param BinaryIO traces_file: (optional)
:param str traces_file_content_type: (optional) The content type of
traces_file.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `UploadTracesGenAIAppResponse` result
"""
if gen_ai_app_id is None:
raise ValueError('gen_ai_app_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='post_upload_traces_for_gen_ai_app')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
form_data = []
if traces_file:
form_data.append(('traces_file', (None, traces_file, traces_file_content_type or 'application/octet-stream')))
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/gen_ai_apps/{0}/traces'.format(
*self.watson_open_scale.encode_path_vars(gen_ai_app_id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
files=form_data)
response = self.watson_open_scale.send(request)
if hasattr(UploadTracesGenAIAppResponse, 'from_dict'):
response.result = UploadTracesGenAIAppResponse.from_dict(response.result)
return response
def upload_traces_for_gen_ai_app_get(self,
gen_ai_app_id: str,
*,
project_id: str = None,
space_id: str = None,
**kwargs
) -> DetailedResponse:
"""
Gets the status of the traces upload.
Gets the status of the traces upload.
:param str gen_ai_app_id: Unique Gen AI App ID.
:param str project_id: (optional) The GUID of the project. Please specify a
combination of `?container_type=project&container_id=<id of the project>`.
:param str space_id: (optional) The GUID of the space. Please specify a
combination of `?container_type=space&container_id=<id of the space>`.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `UploadTracesGenAIAppResponse` result
"""
if gen_ai_app_id is None:
raise ValueError('gen_ai_app_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='get_upload_traces_for_gen_ai_app')
headers.update(sdk_headers)
params = {
'project_id': project_id,
'space_id': space_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v2/gen_ai_apps/{0}/traces'.format(
*self.watson_open_scale.encode_path_vars(gen_ai_app_id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(UploadTracesGenAIAppResponse, 'from_dict'):
response.result = UploadTracesGenAIAppResponse.from_dict(response.result)
return response
#########################
# Guardrails Manager
#########################
class GuardrailsManager:
"""
Guardrails Manager
"""
def __init__(self, watson_open_scale: WatsonOpenScaleV2) -> None:
"""
Construct a GuardrailsManager client for the Watson OpenScale service.
:param WatsonOpenScaleV2 watson_open_scale: client for the Watson OpenScale service.
"""
self.watson_open_scale = watson_open_scale
def detectors_list(self,
x_governance_instance_id: str,
inventory_id: str,
**kwargs
) -> DetailedResponse:
"""
Get all detectors.
Retrieves all detectors including both built-in detectors (from
detector_template.json) and custom detectors (from CAMs).
:param str x_governance_instance_id: Service instance ID (also known as
Governance Instance ID or instance GUID).
:param str inventory_id: CAMS inventory ID (UUID format).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `ListDetectorsResponse` result
"""
if x_governance_instance_id is None:
raise ValueError('x_governance_instance_id must be provided')
if inventory_id is None:
raise ValueError('inventory_id must be provided')
headers = {
'X-Governance-Instance-Id': x_governance_instance_id
}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='list_detectors')
headers.update(sdk_headers)
params = {
'inventory_id': inventory_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/guardrails_manager/v2/detectors'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(ListDetectorsResponse, 'from_dict'):
response.result = ListDetectorsResponse.from_dict(response.result)
return response
def detector_create(self,
x_governance_instance_id: str,
inventory_id: str,
name: str,
url: str,
api_key: str,
direction: List[str],
*,
description: str = None,
detector_properties: List['DetectorProperty'] = None,
parameters: List['DetectorParameter'] = None,
**kwargs
) -> DetailedResponse:
"""
Create a detector.
Creates a new detector with custom endpoint URL and configuration.
:param str x_governance_instance_id: Service instance ID (also known as
Governance Instance ID or instance GUID).
:param str inventory_id: CAMS inventory ID (UUID format).
:param str name: Name of the detector.
:param str url: URL endpoint for the detector.
:param str api_key: API key for authenticating with the detector endpoint.
:param List[str] direction: Direction(s) where the detector applies (input,
output, or both).
:param str description: (optional) Description of the detector.
:param List[DetectorProperty] detector_properties: (optional) Configurable
properties for the detector.
:param List[DetectorParameter] parameters: (optional) Parameters that can
be passed to the detector.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DetectorResponse` result
"""
if x_governance_instance_id is None:
raise ValueError('x_governance_instance_id must be provided')
if inventory_id is None:
raise ValueError('inventory_id must be provided')
if name is None:
raise ValueError('name must be provided')
if url is None:
raise ValueError('url must be provided')
if api_key is None:
raise ValueError('api_key must be provided')
if direction is None:
raise ValueError('direction must be provided')
if detector_properties is not None:
detector_properties = [convert_model(x) for x in detector_properties]
if parameters is not None:
parameters = [convert_model(x) for x in parameters]
headers = {
'X-Governance-Instance-Id': x_governance_instance_id
}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='create_detector')
headers.update(sdk_headers)
params = {
'inventory_id': inventory_id
}
data = {
'name': name,
'url': url,
'api_key': api_key,
'direction': direction,
'description': description,
'detector_properties': detector_properties,
'parameters': parameters
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/guardrails_manager/v2/detectors'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(DetectorResponse, 'from_dict'):
response.result = DetectorResponse.from_dict(response.result)
return response
def detector_get(self,
id: str,
x_governance_instance_id: str,
inventory_id: str,
**kwargs
) -> DetailedResponse:
"""
Get a detector by ID.
Retrieves a specific custom detector by its ID.
:param str id: The UUID of the detector to retrieve.
:param str x_governance_instance_id: Service instance ID (also known as
Governance Instance ID or instance GUID).
:param str inventory_id: CAMS inventory ID (UUID format).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `DetectorResponse` result
"""
if id is None:
raise ValueError('id must be provided')
if x_governance_instance_id is None:
raise ValueError('x_governance_instance_id must be provided')
if inventory_id is None:
raise ValueError('inventory_id must be provided')
headers = {
'X-Governance-Instance-Id': x_governance_instance_id
}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='get_detector')
headers.update(sdk_headers)
params = {
'inventory_id': inventory_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/guardrails_manager/v2/detectors/{0}'.format(
*self.watson_open_scale.encode_path_vars(id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(DetectorResponse, 'from_dict'):
response.result = DetectorResponse.from_dict(response.result)
return response
def enforce_create(self,
id: str,
x_governance_instance_id: str,
inventory_id: str,
text: str,
direction: str,
detectors_properties: dict,
*,
detectors: List[str] = None,
**kwargs
) -> DetailedResponse:
"""
Enforce a policy.
Executes a policy by ID to detect and apply actions on the provided text based on
configured detectors.
:param str id: The UUID of the policy to enforce.
:param str x_governance_instance_id: Service instance ID (also known as
Governance Instance ID or instance GUID).
:param str inventory_id: CAMS inventory ID (UUID format).
:param str text: The text content to be analyzed by the policy detectors.
:param str direction: Direction of the text flow (input or output).
:param dict detectors_properties: Optional properties for detectors, keyed
by detector name.
:param List[str] detectors: (optional) Optional list of specific detector
names to run (if not provided, all policy detectors will run).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `EnforceResponse` result
"""
if id is None:
raise ValueError('id must be provided')
if x_governance_instance_id is None:
raise ValueError('x_governance_instance_id must be provided')
if inventory_id is None:
raise ValueError('inventory_id must be provided')
if text is None:
raise ValueError('text must be provided')
if direction is None:
raise ValueError('direction must be provided')
if detectors_properties is None:
raise ValueError('detectors_properties must be provided')
headers = {
'X-Governance-Instance-Id': x_governance_instance_id
}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='create_enforce')
headers.update(sdk_headers)
params = {
'inventory_id': inventory_id
}
data = {
'text': text,
'direction': direction,
'detectors_properties': detectors_properties,
'detectors': detectors
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/guardrails_manager/v2/enforce/{0}'.format(
*self.watson_open_scale.encode_path_vars(id))
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(EnforceResponse, 'from_dict'):
response.result = EnforceResponse.from_dict(response.result)
return response
def policies_list(self,
inventory_id: str,
policytype: str,
*,
search: str = None,
**kwargs
) -> DetailedResponse:
"""
Get all policies.
Retrieves a list of all policies with optional search and filtering by policy
type.
:param str inventory_id: CAMS inventory ID (UUID format).
:param str policytype: Filter policies by type (publish for active, draft
for inactive, false for all).
:param str search: (optional) Search term to filter policies by name or
description.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `PolicyResponseCollection` result
"""
if inventory_id is None:
raise ValueError('inventory_id must be provided')
if policytype is None:
raise ValueError('policytype must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='list_policies')
headers.update(sdk_headers)
params = {
'inventory_id': inventory_id,
'policytype': policytype,
'search': search
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/guardrails_manager/v2/policies'
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(PolicyResponseCollection, 'from_dict'):
response.result = PolicyResponseCollection.from_dict(response.result)
return response
def policy_create(self,
inventory_id: str,
name: str,
input: List['PolicyDetectorConfig'],
output: List['PolicyDetectorConfig'],
policy_status: str,
*,
description: str = None,
block_message: str = None,
mask_character: str = None,
tags: List[str] = None,
**kwargs
) -> DetailedResponse:
"""
Create a policy.
Creates a new policy with detector and action configurations for input and output
directions.
:param str inventory_id: CAMS inventory ID (UUID format).
:param str name: Name of the policy.
:param List[PolicyDetectorConfig] input: Detector configurations for input
direction.
:param List[PolicyDetectorConfig] output: Detector configurations for
output direction.
:param str policy_status: Status of the policy (publish for active, draft
for inactive).
:param str description: (optional) Description of the policy.
:param str block_message: (optional) Message to display when content is
blocked.
:param str mask_character: (optional) Character to use for masking (e.g.,
"*").
:param List[str] tags: (optional) Tags for categorizing the policy.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `PolicyResponse` result
"""
if inventory_id is None:
raise ValueError('inventory_id must be provided')
if name is None:
raise ValueError('name must be provided')
if input is None:
raise ValueError('input must be provided')
if output is None:
raise ValueError('output must be provided')
if policy_status is None:
raise ValueError('policy_status must be provided')
input = [convert_model(x) for x in input]
output = [convert_model(x) for x in output]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='create_policy')
headers.update(sdk_headers)
params = {
'inventory_id': inventory_id
}
data = {
'name': name,
'input': input,
'output': output,
'policy_status': policy_status,
'description': description,
'block_message': block_message,
'mask_character': mask_character,
'tags': tags
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/guardrails_manager/v2/policies'
request = self.watson_open_scale.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(PolicyResponse, 'from_dict'):
response.result = PolicyResponse.from_dict(response.result)
return response
def policy_get(self,
id: str,
inventory_id: str,
**kwargs
) -> DetailedResponse:
"""
Get a policy by ID.
Retrieves a specific policy by its unique identifier.
:param str id: Unique identifier for the policy (UUID format).
:param str inventory_id: CAMS inventory ID (UUID format).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `PolicyResponse` result
"""
if id is None:
raise ValueError('id must be provided')
if inventory_id is None:
raise ValueError('inventory_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='get_policy')
headers.update(sdk_headers)
params = {
'inventory_id': inventory_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/guardrails_manager/v2/policies/{0}'.format(
*self.watson_open_scale.encode_path_vars(id))
request = self.watson_open_scale.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
if hasattr(PolicyResponse, 'from_dict'):
response.result = PolicyResponse.from_dict(response.result)
return response
def policy_replace(self,
id: str,
inventory_id: str,
name: str,
input: List['PolicyDetectorConfig'],
output: List['PolicyDetectorConfig'],
policy_status: str,
*,
description: str = None,
block_message: str = None,
mask_character: str = None,
tags: List[str] = None,
**kwargs
) -> DetailedResponse:
"""
Update a policy.
Updates an existing policy with new detector and action configurations.
:param str id: Unique identifier for the policy (UUID format).
:param str inventory_id: CAMS inventory ID (UUID format).
:param str name: Name of the policy.
:param List[PolicyDetectorConfig] input: Detector configurations for input
direction.
:param List[PolicyDetectorConfig] output: Detector configurations for
output direction.
:param str policy_status: Status of the policy (publish for active, draft
for inactive).
:param str description: (optional) Description of the policy.
:param str block_message: (optional) Message to display when content is
blocked.
:param str mask_character: (optional) Character to use for masking (e.g.,
"*").
:param List[str] tags: (optional) Tags for categorizing the policy.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `PolicyResponse` result
"""
if id is None:
raise ValueError('id must be provided')
if inventory_id is None:
raise ValueError('inventory_id must be provided')
if name is None:
raise ValueError('name must be provided')
if input is None:
raise ValueError('input must be provided')
if output is None:
raise ValueError('output must be provided')
if policy_status is None:
raise ValueError('policy_status must be provided')
input = [convert_model(x) for x in input]
output = [convert_model(x) for x in output]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='replace_policy')
headers.update(sdk_headers)
params = {
'inventory_id': inventory_id
}
data = {
'name': name,
'input': input,
'output': output,
'policy_status': policy_status,
'description': description,
'block_message': block_message,
'mask_character': mask_character,
'tags': tags
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/guardrails_manager/v2/policies/{0}'.format(
*self.watson_open_scale.encode_path_vars(id))
request = self.watson_open_scale.prepare_request(method='PUT',
url=url,
headers=headers,
params=params,
data=data)
response = self.watson_open_scale.send(request)
if hasattr(PolicyResponse, 'from_dict'):
response.result = PolicyResponse.from_dict(response.result)
return response
def policy_delete(self,
id: str,
inventory_id: str,
**kwargs
) -> DetailedResponse:
"""
Delete a policy.
Deletes a policy by its unique identifier.
:param str id: Unique identifier for the policy (UUID format).
:param str inventory_id: CAMS inventory ID (UUID format).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if id is None:
raise ValueError('id must be provided')
if inventory_id is None:
raise ValueError('inventory_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.watson_open_scale.DEFAULT_SERVICE_NAME,
service_version='V2',
operation_id='delete_policy')
headers.update(sdk_headers)
params = {
'inventory_id': inventory_id
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
url = '/guardrails_manager/v2/policies/{0}'.format(
*self.watson_open_scale.encode_path_vars(id))
request = self.watson_open_scale.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.watson_open_scale.send(request)
return response
class ServiceProvidersListEnums:
"""
Enums for service_providers_list parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class ServiceProvidersAddEnums:
"""
Enums for service_providers_add parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class ServiceProvidersGetEnums:
"""
Enums for service_providers_get parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class ServiceProvidersDeleteEnums:
"""
Enums for service_providers_delete parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class ServiceProvidersUpdateEnums:
"""
Enums for service_providers_update parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class SubscriptionsListEnums:
"""
Enums for subscriptions_list parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class SubscriptionsAddEnums:
"""
Enums for subscriptions_add parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class SubscriptionsGetEnums:
"""
Enums for subscriptions_get parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class SubscriptionsUpdateEnums:
"""
Enums for subscriptions_update parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class SubscriptionsDeleteEnums:
"""
Enums for subscriptions_delete parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class SubscriptionsTablesEnums:
"""
Enums for subscriptions_tables parameters.
"""
class DatasetType(str, Enum):
"""
data set type of subscription.
"""
FEEDBACK = 'feedback'
class DataSetsListEnums:
"""
Enums for data_sets_list parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class TargetTargetType(str, Enum):
"""
type of the target.
"""
SUBSCRIPTION = 'subscription'
INSTANCE = 'instance'
DATA_MART = 'data_mart'
PROJECT = 'project'
SPACE = 'space'
AI_DECISION_COORDINATION = 'ai_decision_coordination'
GEN_AI_APP = 'gen_ai_app'
WXO = 'wxo'
class Type(str, Enum):
"""
type of the data set.
"""
MANUAL_LABELING = 'manual_labeling'
PAYLOAD_LOGGING = 'payload_logging'
FEEDBACK = 'feedback'
BUSINESS_PAYLOAD = 'business_payload'
EXPLANATIONS = 'explanations'
EXPLANATIONS_WHATIF = 'explanations_whatif'
TRAINING = 'training'
PAYLOAD_LOGGING_ERROR = 'payload_logging_error'
MODEL_HEALTH = 'model_health'
DRIFT_STATS = 'drift_stats'
DRIFT_INTERVALS = 'drift_intervals'
DRIFT_INSIGHTS = 'drift_insights'
GEN_AI_QUALITY_METRICS = 'gen_ai_quality_metrics'
GEN_AI_SECURITY_METRICS = 'gen_ai_security_metrics'
DRIFT_SCORES = 'drift_scores'
AIDC_FEEDBACK = 'aidc_feedback'
CUSTOM = 'custom'
NODES_INFO = 'nodes_info'
EDGES_INFO = 'edges_info'
AGENTIC_APP_IO = 'agentic_app_io'
NODES_IO = 'nodes_io'
AGENTIC_APP_METRICS = 'agentic_app_metrics'
SPANS = 'spans'
class DataSetsAddEnums:
"""
Enums for data_sets_add parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class DataSetsGetEnums:
"""
Enums for data_sets_get parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class DataSetsDeleteEnums:
"""
Enums for data_sets_delete parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class DataSetsUpdateEnums:
"""
Enums for data_sets_update parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class RecordsAddEnums:
"""
Enums for records_add parameters.
"""
class ContentType(str, Enum):
"""
The type of the input. A character encoding can be specified by including a
`charset` parameter. For example, 'text/csv;charset=utf-8'.
"""
APPLICATION_JSON = 'application/json'
TEXT_CSV = 'text/csv'
class OnError(str, Enum):
"""
expected behaviour on error.
"""
STOP = 'stop'
CONTINUE = 'continue'
class RecordsListEnums:
"""
Enums for records_list parameters.
"""
class Format(str, Enum):
"""
What JSON format to use on output.
"""
DICT = 'dict'
LIST = 'list'
class BinaryFormat(str, Enum):
"""
Binary data presentation format. By default, the binary field value is encoded to
base64 string. If _reference_ is chosen, every binary field is moved to the
_references_ section with value set to an uri to the particular field within the
record that can be GET in a separate request.
"""
REFERENCE = 'reference'
class RecordsGetEnums:
"""
Enums for records_get parameters.
"""
class BinaryFormat(str, Enum):
"""
Binary data presentation format. By default, the binary field value is encoded to
base64 string. If _reference_ is chosen, every binary field is moved to the
_references_ section with value set to an uri to the particular field within the
record that can be GET in a separate request.
"""
REFERENCE = 'reference'
class RecordsUpdateEnums:
"""
Enums for records_update parameters.
"""
class BinaryFormat(str, Enum):
"""
Binary data presentation format. By default, the binary field value is encoded to
base64 string. If _reference_ is chosen, every binary field is moved to the
_references_ section with value set to an uri to the particular field within the
record that can be GET in a separate request.
"""
REFERENCE = 'reference'
class RecordsQueryEnums:
"""
Enums for records_query parameters.
"""
class DataSetType(str, Enum):
"""
a (single) data set type.
"""
MANUAL_LABELING = 'manual_labeling'
PAYLOAD_LOGGING = 'payload_logging'
FEEDBACK = 'feedback'
BUSINESS_PAYLOAD = 'business_payload'
EXPLANATIONS = 'explanations'
EXPLANATIONS_WHATIF = 'explanations_whatif'
TRAINING = 'training'
PAYLOAD_LOGGING_ERROR = 'payload_logging_error'
MODEL_HEALTH = 'model_health'
DRIFT_STATS = 'drift_stats'
DRIFT_INTERVALS = 'drift_intervals'
DRIFT_INSIGHTS = 'drift_insights'
GEN_AI_QUALITY_METRICS = 'gen_ai_quality_metrics'
GEN_AI_SECURITY_METRICS = 'gen_ai_security_metrics'
DRIFT_SCORES = 'drift_scores'
AIDC_FEEDBACK = 'aidc_feedback'
CUSTOM = 'custom'
NODES_INFO = 'nodes_info'
EDGES_INFO = 'edges_info'
AGENTIC_APP_IO = 'agentic_app_io'
NODES_IO = 'nodes_io'
AGENTIC_APP_METRICS = 'agentic_app_metrics'
SPANS = 'spans'
class InstancesListEnums:
"""
Enums for instances_list parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class InstancesAddEnums:
"""
Enums for instances_add parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class InstancesGetEnums:
"""
Enums for instances_get parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class InstancesUpdateEnums:
"""
Enums for instances_update parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class InstancesDeleteEnums:
"""
Enums for instances_delete parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class MeasurementsAddEnums:
"""
Enums for measurements_add parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class MeasurementsListEnums:
"""
Enums for measurements_list parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class MeasurementsGetEnums:
"""
Enums for measurements_get parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class MeasurementsQueryEnums:
"""
Enums for measurements_query parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class TargetType(str, Enum):
"""
Type of the monitoring target (subscription).
"""
SUBSCRIPTION = 'subscription'
INSTANCE = 'instance'
DATA_MART = 'data_mart'
PROJECT = 'project'
SPACE = 'space'
AI_DECISION_COORDINATION = 'ai_decision_coordination'
GEN_AI_APP = 'gen_ai_app'
WXO = 'wxo'
class Format(str, Enum):
"""
Format of the returned data. `full` format compared to `compact` is additive and
contains `sources` part.
"""
COMPACT = 'compact'
FULL = 'full'
class MetricsListEnums:
"""
Enums for metrics_list parameters.
"""
class Agg(str, Enum):
"""
Comma delimited function list constructed from metric name and function, e.g.
`agg=metric_name:count,:last` that defines aggregations.
"""
LAST = 'last'
FIRST = 'first'
MAX = 'max'
MIN = 'min'
SUM = 'sum'
AVG = 'avg'
COUNT = 'count'
STDDEV = 'stddev'
MEDIAN = 'median'
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class Interval(str, Enum):
"""
Time unit in which metrics are grouped and aggregated, interval by interval.
"""
MINUTE = 'minute'
HOUR = 'hour'
DAY = 'day'
WEEK = 'week'
MONTH = 'month'
YEAR = 'year'
class AiDecisionCoordinationsListEnums:
"""
Enums for ai_decision_coordinations_list parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class AiDecisionCoordinationsAddEnums:
"""
Enums for ai_decision_coordinations_add parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class AiDecisionCoordinationsGetEnums:
"""
Enums for ai_decision_coordinations_get parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class AiDecisionCoordinationsUpdateEnums:
"""
Enums for ai_decision_coordinations_update parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class AiDecisionCoordinationsDeleteEnums:
"""
Enums for ai_decision_coordinations_delete parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class GenAiAppsListEnums:
"""
Enums for gen_ai_apps_list parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class GenAiAppsAddEnums:
"""
Enums for gen_ai_apps_add parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class AgenticAiAppsGetEnums:
"""
Enums for agentic_ai_apps_get parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class AgenticAiAppsUpdateEnums:
"""
Enums for agentic_ai_apps_update parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class AgenticAiAppsDeleteEnums:
"""
Enums for agentic_ai_apps_delete parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class IntegratedSystemsListEnums:
"""
Enums for integrated_systems_list parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class Type(str, Enum):
"""
comma-separated list of type for the integrated system.
"""
OPEN_PAGES = 'open_pages'
SLACK = 'slack'
WEBHOOK = 'webhook'
HIVE = 'hive'
SPARK = 'spark'
JDBC = 'jdbc'
CUSTOM_METRICS_PROVIDER = 'custom_metrics_provider'
WATSON_KNOWLEDGE_CATALOG = 'watson_knowledge_catalog'
GENERATIVE_AI_EVALUATOR = 'generative_ai_evaluator'
EMBEDDINGS_PROVIDER = 'embeddings_provider'
class IntegratedSystemsAddEnums:
"""
Enums for integrated_systems_add parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class IntegratedSystemsGetEnums:
"""
Enums for integrated_systems_get parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class IntegratedSystemsUpdateEnums:
"""
Enums for integrated_systems_update parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class IntegratedSystemsDeleteEnums:
"""
Enums for integrated_systems_delete parameters.
"""
class ContainerType(str, Enum):
"""
Type of container. One of project, space and wxo. Must be used with `container_id`
together.
"""
PROJECT = 'project'
SPACE = 'space'
WXO = 'wxo'
class ExplanationTasksListEnums:
"""
Enums for explanation_tasks_list parameters.
"""
class Status(str, Enum):
"""
Status of the explanation task.
"""
IN_PROGRESS = 'in_progress'
FINISHED = 'finished'
ERROR = 'error'
class MrmRiskEvaluationsEnums:
"""
Enums for mrm_risk_evaluations parameters.
"""
class ContentType(str, Enum):
"""
The type of the input. A character encoding can be specified by including a
`charset` parameter. For example, 'text/csv;charset=utf-8'.
"""
APPLICATION_JSON = 'application/json'
TEXT_CSV = 'text/csv'
class EvaluationTests(str, Enum):
"""
Comma separated list of monitor tests to run.
"""
DRIFT = 'drift'
FAIRNESS = 'fairness'
QUALITY = 'quality'
EXPLAINABILITY = 'explainability'
class ListPoliciesEnums:
"""
Enums for list_policies parameters.
"""
class Policytype(str, Enum):
"""
Filter policies by type (publish for active, draft for inactive, false for all).
"""
PUBLISH = 'publish'
DRAFT = 'draft'
FALSE = 'false'
##############################################################################
# Models
##############################################################################
class AIDecisionCoordinationCollection():
"""
AIDecisionCoordinationCollection.
:attr List[AIDecisionCoordinationResponse] ai_decision_coordinations:
"""
def __init__(self,
ai_decision_coordinations: List['AIDecisionCoordinationResponse']) -> None:
"""
Initialize a AIDecisionCoordinationCollection object.
:param List[AIDecisionCoordinationResponse] ai_decision_coordinations:
"""
self.ai_decision_coordinations = ai_decision_coordinations
@classmethod
def from_dict(cls, _dict: Dict) -> 'AIDecisionCoordinationCollection':
"""Initialize a AIDecisionCoordinationCollection object from a json dictionary."""
args = {}
if 'ai_decision_coordinations' in _dict:
args['ai_decision_coordinations'] = [AIDecisionCoordinationResponse.from_dict(x) for x in _dict.get('ai_decision_coordinations')]
else:
raise ValueError('Required property \'ai_decision_coordinations\' not present in AIDecisionCoordinationCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AIDecisionCoordinationCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'ai_decision_coordinations') and self.ai_decision_coordinations is not None:
_dict['ai_decision_coordinations'] = [x.to_dict() for x in self.ai_decision_coordinations]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AIDecisionCoordinationCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AIDecisionCoordinationCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AIDecisionCoordinationCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class AIDecisionCoordinationEntity():
"""
AI Decision Coordination definition.
:attr str service_provider_id: The GUID of the Service Provider.
:attr str usecase_id: The GUID of the Usecase.
:attr Asset asset: asset_type must be ai_decision_coordination.
:attr Status status: (optional)
"""
def __init__(self,
service_provider_id: str,
usecase_id: str,
asset: 'Asset',
*,
status: 'Status' = None) -> None:
"""
Initialize a AIDecisionCoordinationEntity object.
:param str service_provider_id: The GUID of the Service Provider.
:param str usecase_id: The GUID of the Usecase.
:param Asset asset: asset_type must be ai_decision_coordination.
:param Status status: (optional)
"""
self.service_provider_id = service_provider_id
self.usecase_id = usecase_id
self.asset = asset
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'AIDecisionCoordinationEntity':
"""Initialize a AIDecisionCoordinationEntity object from a json dictionary."""
args = {}
if 'service_provider_id' in _dict:
args['service_provider_id'] = _dict.get('service_provider_id')
else:
raise ValueError('Required property \'service_provider_id\' not present in AIDecisionCoordinationEntity JSON')
if 'usecase_id' in _dict:
args['usecase_id'] = _dict.get('usecase_id')
else:
raise ValueError('Required property \'usecase_id\' not present in AIDecisionCoordinationEntity JSON')
if 'asset' in _dict:
args['asset'] = Asset.from_dict(_dict.get('asset'))
else:
raise ValueError('Required property \'asset\' not present in AIDecisionCoordinationEntity JSON')
if 'status' in _dict:
args['status'] = Status.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AIDecisionCoordinationEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'service_provider_id') and self.service_provider_id is not None:
_dict['service_provider_id'] = self.service_provider_id
if hasattr(self, 'usecase_id') and self.usecase_id is not None:
_dict['usecase_id'] = self.usecase_id
if hasattr(self, 'asset') and self.asset is not None:
_dict['asset'] = self.asset.to_dict()
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AIDecisionCoordinationEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AIDecisionCoordinationEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AIDecisionCoordinationEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class AIDecisionCoordinationResponse():
"""
AIDecisionCoordinationResponse.
:attr Metadata metadata: (optional)
:attr AIDecisionCoordinationEntity entity: (optional) AI Decision Coordination
definition.
"""
def __init__(self,
*,
metadata: 'Metadata' = None,
entity: 'AIDecisionCoordinationEntity' = None) -> None:
"""
Initialize a AIDecisionCoordinationResponse object.
:param Metadata metadata: (optional)
:param AIDecisionCoordinationEntity entity: (optional) AI Decision
Coordination definition.
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'AIDecisionCoordinationResponse':
"""Initialize a AIDecisionCoordinationResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
if 'entity' in _dict:
args['entity'] = AIDecisionCoordinationEntity.from_dict(_dict.get('entity'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AIDecisionCoordinationResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AIDecisionCoordinationResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AIDecisionCoordinationResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AIDecisionCoordinationResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class AISetupDataSetResponse():
"""
The data-set details in the AI setup response.
:attr str data_set_type: (optional) type of a data set.
:attr str data_set_id: (optional) Unique identifier of the data set (like
scoring or feedback).
"""
def __init__(self,
*,
data_set_type: str = None,
data_set_id: str = None) -> None:
"""
Initialize a AISetupDataSetResponse object.
:param str data_set_type: (optional) type of a data set.
:param str data_set_id: (optional) Unique identifier of the data set (like
scoring or feedback).
"""
self.data_set_type = data_set_type
self.data_set_id = data_set_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'AISetupDataSetResponse':
"""Initialize a AISetupDataSetResponse object from a json dictionary."""
args = {}
if 'data_set_type' in _dict:
args['data_set_type'] = _dict.get('data_set_type')
if 'data_set_id' in _dict:
args['data_set_id'] = _dict.get('data_set_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AISetupDataSetResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'data_set_type') and self.data_set_type is not None:
_dict['data_set_type'] = self.data_set_type
if hasattr(self, 'data_set_id') and self.data_set_id is not None:
_dict['data_set_id'] = self.data_set_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AISetupDataSetResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AISetupDataSetResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AISetupDataSetResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSetTypeEnum(str, Enum):
"""
type of a data set.
"""
MANUAL_LABELING = 'manual_labeling'
PAYLOAD_LOGGING = 'payload_logging'
FEEDBACK = 'feedback'
BUSINESS_PAYLOAD = 'business_payload'
EXPLANATIONS = 'explanations'
EXPLANATIONS_WHATIF = 'explanations_whatif'
TRAINING = 'training'
PAYLOAD_LOGGING_ERROR = 'payload_logging_error'
MODEL_HEALTH = 'model_health'
DRIFT_STATS = 'drift_stats'
DRIFT_INTERVALS = 'drift_intervals'
DRIFT_INSIGHTS = 'drift_insights'
GEN_AI_QUALITY_METRICS = 'gen_ai_quality_metrics'
GEN_AI_SECURITY_METRICS = 'gen_ai_security_metrics'
DRIFT_SCORES = 'drift_scores'
AIDC_FEEDBACK = 'aidc_feedback'
CUSTOM = 'custom'
NODES_INFO = 'nodes_info'
EDGES_INFO = 'edges_info'
AGENTIC_APP_IO = 'agentic_app_io'
NODES_IO = 'nodes_io'
AGENTIC_APP_METRICS = 'agentic_app_metrics'
SPANS = 'spans'
class AISetupMonitor():
"""
Monitor object containing details about the monitor to be configured via AI setup.
:attr str monitor_definition_id: (optional) The monitor definition ID of the
monitor to be configured.
:attr object parameters: (optional) The parameters for the monitor to be
configured.
:attr List[MetricThreshold] thresholds: (optional) The list of thresholds for
the monitor to be configured.
"""
def __init__(self,
*,
monitor_definition_id: str = None,
parameters: object = None,
thresholds: List['MetricThreshold'] = None) -> None:
"""
Initialize a AISetupMonitor object.
:param str monitor_definition_id: (optional) The monitor definition ID of
the monitor to be configured.
:param object parameters: (optional) The parameters for the monitor to be
configured.
:param List[MetricThreshold] thresholds: (optional) The list of thresholds
for the monitor to be configured.
"""
self.monitor_definition_id = monitor_definition_id
self.parameters = parameters
self.thresholds = thresholds
@classmethod
def from_dict(cls, _dict: Dict) -> 'AISetupMonitor':
"""Initialize a AISetupMonitor object from a json dictionary."""
args = {}
if 'monitor_definition_id' in _dict:
args['monitor_definition_id'] = _dict.get('monitor_definition_id')
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
if 'thresholds' in _dict:
args['thresholds'] = [MetricThreshold.from_dict(x) for x in _dict.get('thresholds')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AISetupMonitor object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'monitor_definition_id') and self.monitor_definition_id is not None:
_dict['monitor_definition_id'] = self.monitor_definition_id
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
if hasattr(self, 'thresholds') and self.thresholds is not None:
_dict['thresholds'] = [x.to_dict() for x in self.thresholds]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AISetupMonitor object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AISetupMonitor') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AISetupMonitor') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class AISetupMonitorResponse():
"""
The monitor details in the AI setup response.
:attr str monitor_definition_id: (optional)
:attr str monitor_instance_id: (optional)
"""
def __init__(self,
*,
monitor_definition_id: str = None,
monitor_instance_id: str = None) -> None:
"""
Initialize a AISetupMonitorResponse object.
:param str monitor_definition_id: (optional)
:param str monitor_instance_id: (optional)
"""
self.monitor_definition_id = monitor_definition_id
self.monitor_instance_id = monitor_instance_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'AISetupMonitorResponse':
"""Initialize a AISetupMonitorResponse object from a json dictionary."""
args = {}
if 'monitor_definition_id' in _dict:
args['monitor_definition_id'] = _dict.get('monitor_definition_id')
if 'monitor_instance_id' in _dict:
args['monitor_instance_id'] = _dict.get('monitor_instance_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AISetupMonitorResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'monitor_definition_id') and self.monitor_definition_id is not None:
_dict['monitor_definition_id'] = self.monitor_definition_id
if hasattr(self, 'monitor_instance_id') and self.monitor_instance_id is not None:
_dict['monitor_instance_id'] = self.monitor_instance_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AISetupMonitorResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AISetupMonitorResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AISetupMonitorResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class AISetupResponse():
"""
The AI setup response.
:attr str ai_service_id:
:attr str project_id: (optional)
:attr str space_id: (optional)
:attr str deployment_id: (optional)
:attr str service_provider_id: (optional)
:attr str gen_ai_app_id: (optional) The ID (typically a UUID v4) which uniquely
identifies the resource.
:attr str start_time: The date-timestamp when the AI setup was started.
:attr str end_time: (optional) The date-timestamp when the AI setup ended.
:attr List[AISetupDataSetResponse] data_sets: (optional) The list of data-set
details in the AI setup response.
:attr List[AISetupMonitorResponse] monitors: (optional) The list of monitor
details in the AI setup response.
:attr AISetupResponseStatus status: (optional) The AI setup status.
:attr List[str] evaluation_tests: (optional) The evaluation tests to be executed
as part of the risk-evaluations.
"""
def __init__(self,
ai_service_id: str,
start_time: str,
*,
project_id: str = None,
space_id: str = None,
deployment_id: str = None,
service_provider_id: str = None,
gen_ai_app_id: str = None,
end_time: str = None,
data_sets: List['AISetupDataSetResponse'] = None,
monitors: List['AISetupMonitorResponse'] = None,
status: 'AISetupResponseStatus' = None,
evaluation_tests: List[str] = None) -> None:
"""
Initialize a AISetupResponse object.
:param str ai_service_id:
:param str start_time: The date-timestamp when the AI setup was started.
:param str project_id: (optional)
:param str space_id: (optional)
:param str deployment_id: (optional)
:param str service_provider_id: (optional)
:param str gen_ai_app_id: (optional) The ID (typically a UUID v4) which
uniquely identifies the resource.
:param str end_time: (optional) The date-timestamp when the AI setup ended.
:param List[AISetupDataSetResponse] data_sets: (optional) The list of
data-set details in the AI setup response.
:param List[AISetupMonitorResponse] monitors: (optional) The list of
monitor details in the AI setup response.
:param AISetupResponseStatus status: (optional) The AI setup status.
:param List[str] evaluation_tests: (optional) The evaluation tests to be
executed as part of the risk-evaluations.
"""
self.ai_service_id = ai_service_id
self.project_id = project_id
self.space_id = space_id
self.deployment_id = deployment_id
self.service_provider_id = service_provider_id
self.gen_ai_app_id = gen_ai_app_id
self.start_time = start_time
self.end_time = end_time
self.data_sets = data_sets
self.monitors = monitors
self.status = status
self.evaluation_tests = evaluation_tests
@classmethod
def from_dict(cls, _dict: Dict) -> 'AISetupResponse':
"""Initialize a AISetupResponse object from a json dictionary."""
args = {}
if 'ai_service_id' in _dict:
args['ai_service_id'] = _dict.get('ai_service_id')
else:
raise ValueError('Required property \'ai_service_id\' not present in AISetupResponse JSON')
if 'project_id' in _dict:
args['project_id'] = _dict.get('project_id')
if 'space_id' in _dict:
args['space_id'] = _dict.get('space_id')
if 'deployment_id' in _dict:
args['deployment_id'] = _dict.get('deployment_id')
if 'service_provider_id' in _dict:
args['service_provider_id'] = _dict.get('service_provider_id')
if 'gen_ai_app_id' in _dict:
args['gen_ai_app_id'] = _dict.get('gen_ai_app_id')
if 'start_time' in _dict:
args['start_time'] = _dict.get('start_time')
else:
raise ValueError('Required property \'start_time\' not present in AISetupResponse JSON')
if 'end_time' in _dict:
args['end_time'] = _dict.get('end_time')
if 'data_sets' in _dict:
args['data_sets'] = [AISetupDataSetResponse.from_dict(x) for x in _dict.get('data_sets')]
if 'monitors' in _dict:
args['monitors'] = [AISetupMonitorResponse.from_dict(x) for x in _dict.get('monitors')]
if 'status' in _dict:
args['status'] = AISetupResponseStatus.from_dict(_dict.get('status'))
if 'evaluation_tests' in _dict:
args['evaluation_tests'] = _dict.get('evaluation_tests')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AISetupResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'ai_service_id') and self.ai_service_id is not None:
_dict['ai_service_id'] = self.ai_service_id
if hasattr(self, 'project_id') and self.project_id is not None:
_dict['project_id'] = self.project_id
if hasattr(self, 'space_id') and self.space_id is not None:
_dict['space_id'] = self.space_id
if hasattr(self, 'deployment_id') and self.deployment_id is not None:
_dict['deployment_id'] = self.deployment_id
if hasattr(self, 'service_provider_id') and self.service_provider_id is not None:
_dict['service_provider_id'] = self.service_provider_id
if hasattr(self, 'gen_ai_app_id') and self.gen_ai_app_id is not None:
_dict['gen_ai_app_id'] = self.gen_ai_app_id
if hasattr(self, 'start_time') and self.start_time is not None:
_dict['start_time'] = self.start_time
if hasattr(self, 'end_time') and self.end_time is not None:
_dict['end_time'] = self.end_time
if hasattr(self, 'data_sets') and self.data_sets is not None:
_dict['data_sets'] = [x.to_dict() for x in self.data_sets]
if hasattr(self, 'monitors') and self.monitors is not None:
_dict['monitors'] = [x.to_dict() for x in self.monitors]
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
if hasattr(self, 'evaluation_tests') and self.evaluation_tests is not None:
_dict['evaluation_tests'] = self.evaluation_tests
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AISetupResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AISetupResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AISetupResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class AISetupResponseStatus():
"""
The AI setup status.
:attr str state: The AI setup state.
:attr GenericErrorResponse failure: (optional)
"""
def __init__(self,
state: str,
*,
failure: 'GenericErrorResponse' = None) -> None:
"""
Initialize a AISetupResponseStatus object.
:param str state: The AI setup state.
:param GenericErrorResponse failure: (optional)
"""
self.state = state
self.failure = failure
@classmethod
def from_dict(cls, _dict: Dict) -> 'AISetupResponseStatus':
"""Initialize a AISetupResponseStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
else:
raise ValueError('Required property \'state\' not present in AISetupResponseStatus JSON')
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AISetupResponseStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AISetupResponseStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AISetupResponseStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AISetupResponseStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
The AI setup state.
"""
RUNNING = 'RUNNING'
ERROR = 'ERROR'
FINISHED = 'FINISHED'
class AnalyticsEngine():
"""
AnalyticsEngine.
:attr str type: Type of analytics engine. e.g. spark.
:attr str integrated_system_id: (optional) id of the Integrated System.
:attr object credentials: (optional) Credentials to override credentials in
integration_reference.
:attr object parameters: (optional) Additional parameters (e.g.
max_num_executors, min_num_executors, executor_cores, executor_memory,
driver_cores, driver_memory).
"""
def __init__(self,
type: str,
*,
integrated_system_id: str = None,
credentials: object = None,
parameters: object = None) -> None:
"""
Initialize a AnalyticsEngine object.
:param str type: Type of analytics engine. e.g. spark.
:param str integrated_system_id: (optional) id of the Integrated System.
:param object credentials: (optional) Credentials to override credentials
in integration_reference.
:param object parameters: (optional) Additional parameters (e.g.
max_num_executors, min_num_executors, executor_cores, executor_memory,
driver_cores, driver_memory).
"""
self.type = type
self.integrated_system_id = integrated_system_id
self.credentials = credentials
self.parameters = parameters
@classmethod
def from_dict(cls, _dict: Dict) -> 'AnalyticsEngine':
"""Initialize a AnalyticsEngine object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in AnalyticsEngine JSON')
if 'integrated_system_id' in _dict:
args['integrated_system_id'] = _dict.get('integrated_system_id')
if 'credentials' in _dict:
args['credentials'] = _dict.get('credentials')
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AnalyticsEngine object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'integrated_system_id') and self.integrated_system_id is not None:
_dict['integrated_system_id'] = self.integrated_system_id
if hasattr(self, 'credentials') and self.credentials is not None:
_dict['credentials'] = self.credentials
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AnalyticsEngine object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AnalyticsEngine') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AnalyticsEngine') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ApplicabilitySelection():
"""
ApplicabilitySelection.
:attr List[str] input_data_type: (optional)
:attr List[str] problem_type: (optional)
:attr List[str] target_type: (optional)
"""
def __init__(self,
*,
input_data_type: List[str] = None,
problem_type: List[str] = None,
target_type: List[str] = None) -> None:
"""
Initialize a ApplicabilitySelection object.
:param List[str] input_data_type: (optional)
:param List[str] problem_type: (optional)
:param List[str] target_type: (optional)
"""
self.input_data_type = input_data_type
self.problem_type = problem_type
self.target_type = target_type
@classmethod
def from_dict(cls, _dict: Dict) -> 'ApplicabilitySelection':
"""Initialize a ApplicabilitySelection object from a json dictionary."""
args = {}
if 'input_data_type' in _dict:
args['input_data_type'] = _dict.get('input_data_type')
if 'problem_type' in _dict:
args['problem_type'] = _dict.get('problem_type')
if 'target_type' in _dict:
args['target_type'] = _dict.get('target_type')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ApplicabilitySelection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'input_data_type') and self.input_data_type is not None:
_dict['input_data_type'] = self.input_data_type
if hasattr(self, 'problem_type') and self.problem_type is not None:
_dict['problem_type'] = self.problem_type
if hasattr(self, 'target_type') and self.target_type is not None:
_dict['target_type'] = self.target_type
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ApplicabilitySelection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ApplicabilitySelection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ApplicabilitySelection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class InputDataTypeEnum(str, Enum):
"""
input_data_type.
"""
STRUCTURED = 'structured'
UNSTRUCTURED_IMAGE = 'unstructured_image'
UNSTRUCTURED_TEXT = 'unstructured_text'
CHAT = 'chat'
UNSTRUCTURED_VIDEO = 'unstructured_video'
UNSTRUCTURED_AUDIO = 'unstructured_audio'
class ProblemTypeEnum(str, Enum):
"""
problem_type.
"""
BINARY = 'binary'
REGRESSION = 'regression'
MULTICLASS = 'multiclass'
QUESTION_ANSWERING = 'question_answering'
RETRIEVAL_AUGMENTED_GENERATION = 'retrieval_augmented_generation'
SUMMARIZATION = 'summarization'
CLASSIFICATION = 'classification'
GENERATION = 'generation'
CODE = 'code'
EXTRACTION = 'extraction'
class TargetTypeEnum(str, Enum):
"""
Type of the target (e.g. subscription, ...).
"""
SUBSCRIPTION = 'subscription'
INSTANCE = 'instance'
DATA_MART = 'data_mart'
PROJECT = 'project'
SPACE = 'space'
AI_DECISION_COORDINATION = 'ai_decision_coordination'
GEN_AI_APP = 'gen_ai_app'
WXO = 'wxo'
[docs]
class Asset():
"""
Asset.
:attr str asset_id:
:attr str url: (optional)
:attr str name: (optional)
:attr str asset_type: ai_decision_coordination is limited for AI Decision
Coordination. agent is limited to Agentitc AI App.
:attr str asset_rn: (optional) Asset Resource Name (used for integration with
3rd party ML engines).
:attr str created_at: (optional)
:attr str problem_type: (optional)
:attr str model_type: (optional)
:attr str runtime_environment: (optional)
:attr str input_data_type: (optional)
:attr str foundational_model_id: (optional)
:attr AssetLocale locale: (optional) represents languages used in both input and
output of the model.
"""
def __init__(self,
asset_id: str,
asset_type: str,
*,
url: str = None,
name: str = None,
asset_rn: str = None,
created_at: str = None,
problem_type: str = None,
model_type: str = None,
runtime_environment: str = None,
input_data_type: str = None,
foundational_model_id: str = None,
locale: 'AssetLocale' = None) -> None:
"""
Initialize a Asset object.
:param str asset_id:
:param str asset_type: ai_decision_coordination is limited for AI Decision
Coordination. agent is limited to Agentitc AI App.
:param str url: (optional)
:param str name: (optional)
:param str asset_rn: (optional) Asset Resource Name (used for integration
with 3rd party ML engines).
:param str created_at: (optional)
:param str problem_type: (optional)
:param str model_type: (optional)
:param str runtime_environment: (optional)
:param str input_data_type: (optional)
:param str foundational_model_id: (optional)
:param AssetLocale locale: (optional) represents languages used in both
input and output of the model.
"""
self.asset_id = asset_id
self.url = url
self.name = name
self.asset_type = asset_type
self.asset_rn = asset_rn
self.created_at = created_at
self.problem_type = problem_type
self.model_type = model_type
self.runtime_environment = runtime_environment
self.input_data_type = input_data_type
self.foundational_model_id = foundational_model_id
self.locale = locale
@classmethod
def from_dict(cls, _dict: Dict) -> 'Asset':
"""Initialize a Asset object from a json dictionary."""
args = {}
if 'asset_id' in _dict:
args['asset_id'] = _dict.get('asset_id')
else:
raise ValueError('Required property \'asset_id\' not present in Asset JSON')
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'asset_type' in _dict:
args['asset_type'] = _dict.get('asset_type')
else:
raise ValueError('Required property \'asset_type\' not present in Asset JSON')
if 'asset_rn' in _dict:
args['asset_rn'] = _dict.get('asset_rn')
if 'created_at' in _dict:
args['created_at'] = _dict.get('created_at')
if 'problem_type' in _dict:
args['problem_type'] = _dict.get('problem_type')
if 'model_type' in _dict:
args['model_type'] = _dict.get('model_type')
if 'runtime_environment' in _dict:
args['runtime_environment'] = _dict.get('runtime_environment')
if 'input_data_type' in _dict:
args['input_data_type'] = _dict.get('input_data_type')
if 'foundational_model_id' in _dict:
args['foundational_model_id'] = _dict.get('foundational_model_id')
if 'locale' in _dict:
args['locale'] = AssetLocale.from_dict(_dict.get('locale'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Asset object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'asset_id') and self.asset_id is not None:
_dict['asset_id'] = self.asset_id
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'asset_type') and self.asset_type is not None:
_dict['asset_type'] = self.asset_type
if hasattr(self, 'asset_rn') and self.asset_rn is not None:
_dict['asset_rn'] = self.asset_rn
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = self.created_at
if hasattr(self, 'problem_type') and self.problem_type is not None:
_dict['problem_type'] = self.problem_type
if hasattr(self, 'model_type') and self.model_type is not None:
_dict['model_type'] = self.model_type
if hasattr(self, 'runtime_environment') and self.runtime_environment is not None:
_dict['runtime_environment'] = self.runtime_environment
if hasattr(self, 'input_data_type') and self.input_data_type is not None:
_dict['input_data_type'] = self.input_data_type
if hasattr(self, 'foundational_model_id') and self.foundational_model_id is not None:
_dict['foundational_model_id'] = self.foundational_model_id
if hasattr(self, 'locale') and self.locale is not None:
_dict['locale'] = self.locale.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Asset object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Asset') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Asset') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class AssetTypeEnum(str, Enum):
"""
ai_decision_coordination is limited for AI Decision Coordination. agent is limited
to Agentitc AI App.
"""
MODEL = 'model'
FUNCTION = 'function'
PROMPT = 'prompt'
AI_DECISION_COORDINATION = 'ai_decision_coordination'
AGENT = 'agent'
class ProblemTypeEnum(str, Enum):
"""
problem_type.
"""
BINARY = 'binary'
REGRESSION = 'regression'
MULTICLASS = 'multiclass'
QUESTION_ANSWERING = 'question_answering'
SUMMARIZATION = 'summarization'
RETRIEVAL_AUGMENTED_GENERATION = 'retrieval_augmented_generation'
CLASSIFICATION = 'classification'
GENERATION = 'generation'
CODE = 'code'
EXTRACTION = 'extraction'
class InputDataTypeEnum(str, Enum):
"""
input_data_type.
"""
STRUCTURED = 'structured'
UNSTRUCTURED_IMAGE = 'unstructured_image'
UNSTRUCTURED_TEXT = 'unstructured_text'
CHAT = 'chat'
UNSTRUCTURED_VIDEO = 'unstructured_video'
UNSTRUCTURED_AUDIO = 'unstructured_audio'
class AssetDeployment():
"""
AssetDeployment.
:attr str deployment_id: (optional)
:attr str deployment_rn: (optional) Deployment Resource Name (used for
integration with 3rd party ML engines).
:attr str url: (optional)
:attr str name: (optional)
:attr str description: (optional)
:attr str deployment_type: (optional) Deployment type.
:attr str created_at: (optional)
:attr ScoringEndpoint scoring_endpoint: (optional) Definition of scoring
endpoint in custom_machine_learning.
:attr List[InferenceEndpoint] inference_endpoint: (optional) inference endpoints
for the deployment at watsonx.ai. Either of `inference_endpoint` or
`scoring_endpoint` should be provided. If both given, underlying API will reject
the request.
"""
def __init__(self,
*,
deployment_id: str = None,
deployment_rn: str = None,
url: str = None,
name: str = None,
description: str = None,
deployment_type: str = None,
created_at: str = None,
scoring_endpoint: 'ScoringEndpoint' = None,
inference_endpoint: List['InferenceEndpoint'] = None) -> None:
"""
Initialize a AssetDeployment object.
:param str deployment_id: (optional)
:param str deployment_rn: (optional) Deployment Resource Name (used for
integration with 3rd party ML engines).
:param str url: (optional)
:param str name: (optional)
:param str description: (optional)
:param str deployment_type: (optional) Deployment type.
:param str created_at: (optional)
:param ScoringEndpoint scoring_endpoint: (optional) Definition of scoring
endpoint in custom_machine_learning.
:param List[InferenceEndpoint] inference_endpoint: (optional) inference
endpoints for the deployment at watsonx.ai. Either of `inference_endpoint`
or `scoring_endpoint` should be provided. If both given, underlying API
will reject the request.
"""
self.deployment_id = deployment_id
self.deployment_rn = deployment_rn
self.url = url
self.name = name
self.description = description
self.deployment_type = deployment_type
self.created_at = created_at
self.scoring_endpoint = scoring_endpoint
self.inference_endpoint = inference_endpoint
@classmethod
def from_dict(cls, _dict: Dict) -> 'AssetDeployment':
"""Initialize a AssetDeployment object from a json dictionary."""
args = {}
if 'deployment_id' in _dict:
args['deployment_id'] = _dict.get('deployment_id')
if 'deployment_rn' in _dict:
args['deployment_rn'] = _dict.get('deployment_rn')
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'deployment_type' in _dict:
args['deployment_type'] = _dict.get('deployment_type')
if 'created_at' in _dict:
args['created_at'] = _dict.get('created_at')
if 'scoring_endpoint' in _dict:
args['scoring_endpoint'] = ScoringEndpoint.from_dict(_dict.get('scoring_endpoint'))
if 'inference_endpoint' in _dict:
args['inference_endpoint'] = [InferenceEndpoint.from_dict(x) for x in _dict.get('inference_endpoint')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AssetDeployment object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'deployment_id') and self.deployment_id is not None:
_dict['deployment_id'] = self.deployment_id
if hasattr(self, 'deployment_rn') and self.deployment_rn is not None:
_dict['deployment_rn'] = self.deployment_rn
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'deployment_type') and self.deployment_type is not None:
_dict['deployment_type'] = self.deployment_type
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = self.created_at
if hasattr(self, 'scoring_endpoint') and self.scoring_endpoint is not None:
_dict['scoring_endpoint'] = self.scoring_endpoint.to_dict()
if hasattr(self, 'inference_endpoint') and self.inference_endpoint is not None:
_dict['inference_endpoint'] = [x.to_dict() for x in self.inference_endpoint]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AssetDeployment object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AssetDeployment') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AssetDeployment') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DeploymentTypeEnum(str, Enum):
"""
Deployment type.
"""
ONLINE = 'online'
BATCH = 'batch'
DETACHED = 'detached'
[docs]
class AssetDeploymentRequest():
"""
AssetDeploymentRequest.
:attr str deployment_id:
:attr str deployment_rn: (optional) Deployment Resource Name (used for
integration with 3rd party ML engines).
:attr str url: (optional)
:attr str name:
:attr str description: (optional)
:attr str deployment_type: Deployment type.
:attr str created_at: (optional)
:attr ScoringEndpointRequest scoring_endpoint: (optional) Definition of scoring
endpoint in custom_machine_learning.
"""
def __init__(self,
deployment_id: str,
name: str,
deployment_type: str,
*,
deployment_rn: str = None,
url: str = None,
description: str = None,
created_at: str = None,
scoring_endpoint: 'ScoringEndpointRequest' = None) -> None:
"""
Initialize a AssetDeploymentRequest object.
:param str deployment_id:
:param str name:
:param str deployment_type: Deployment type.
:param str deployment_rn: (optional) Deployment Resource Name (used for
integration with 3rd party ML engines).
:param str url: (optional)
:param str description: (optional)
:param str created_at: (optional)
:param ScoringEndpointRequest scoring_endpoint: (optional) Definition of
scoring endpoint in custom_machine_learning.
"""
self.deployment_id = deployment_id
self.deployment_rn = deployment_rn
self.url = url
self.name = name
self.description = description
self.deployment_type = deployment_type
self.created_at = created_at
self.scoring_endpoint = scoring_endpoint
@classmethod
def from_dict(cls, _dict: Dict) -> 'AssetDeploymentRequest':
"""Initialize a AssetDeploymentRequest object from a json dictionary."""
args = {}
if 'deployment_id' in _dict:
args['deployment_id'] = _dict.get('deployment_id')
else:
raise ValueError('Required property \'deployment_id\' not present in AssetDeploymentRequest JSON')
if 'deployment_rn' in _dict:
args['deployment_rn'] = _dict.get('deployment_rn')
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in AssetDeploymentRequest JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'deployment_type' in _dict:
args['deployment_type'] = _dict.get('deployment_type')
else:
raise ValueError('Required property \'deployment_type\' not present in AssetDeploymentRequest JSON')
if 'created_at' in _dict:
args['created_at'] = _dict.get('created_at')
if 'scoring_endpoint' in _dict:
args['scoring_endpoint'] = ScoringEndpointRequest.from_dict(_dict.get('scoring_endpoint'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AssetDeploymentRequest object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'deployment_id') and self.deployment_id is not None:
_dict['deployment_id'] = self.deployment_id
if hasattr(self, 'deployment_rn') and self.deployment_rn is not None:
_dict['deployment_rn'] = self.deployment_rn
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'deployment_type') and self.deployment_type is not None:
_dict['deployment_type'] = self.deployment_type
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = self.created_at
if hasattr(self, 'scoring_endpoint') and self.scoring_endpoint is not None:
_dict['scoring_endpoint'] = self.scoring_endpoint.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AssetDeploymentRequest object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AssetDeploymentRequest') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AssetDeploymentRequest') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class DeploymentTypeEnum(str, Enum):
"""
Deployment type.
"""
ONLINE = 'online'
BATCH = 'batch'
DETACHED = 'detached'
class AssetLocale():
"""
represents languages used in both input and output of the model.
:attr List[str] input: (optional) represents a list of language-code LLM can
handle.
:attr List[str] output: (optional) represents a list of language-code LLM can
handle.
"""
def __init__(self,
*,
input: List[str] = None,
output: List[str] = None) -> None:
"""
Initialize a AssetLocale object.
:param List[str] input: (optional) represents a list of language-code LLM
can handle.
:param List[str] output: (optional) represents a list of language-code LLM
can handle.
"""
self.input = input
self.output = output
@classmethod
def from_dict(cls, _dict: Dict) -> 'AssetLocale':
"""Initialize a AssetLocale object from a json dictionary."""
args = {}
if 'input' in _dict:
args['input'] = _dict.get('input')
if 'output' in _dict:
args['output'] = _dict.get('output')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AssetLocale object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'input') and self.input is not None:
_dict['input'] = self.input
if hasattr(self, 'output') and self.output is not None:
_dict['output'] = self.output
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AssetLocale object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AssetLocale') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AssetLocale') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class InputEnum(str, Enum):
"""
represents a language-code, which can include country/region potentially once they
are supported, e.g. en-US or pt-BR.
"""
EN = 'en'
JA = 'ja'
DE = 'de'
FR = 'fr'
ES = 'es'
AR = 'ar'
IT = 'it'
PT = 'pt'
KO = 'ko'
DA = 'da'
class OutputEnum(str, Enum):
"""
represents a language-code, which can include country/region potentially once they
are supported, e.g. en-US or pt-BR.
"""
EN = 'en'
JA = 'ja'
DE = 'de'
FR = 'fr'
ES = 'es'
AR = 'ar'
IT = 'it'
PT = 'pt'
KO = 'ko'
DA = 'da'
class AssetProperties():
"""
Additional asset properties (subject of discovery if not provided when creating the
subscription).
:attr SecretCleaned training_data_reference: (optional)
:attr SparkStruct training_data_schema: (optional)
:attr SparkStruct input_data_schema: (optional)
:attr SparkStruct output_data_schema: (optional)
:attr str input_token_count_field: (optional) Field with this name will be given
modeling_role `input-token-count`.
:attr str output_token_count_field: (optional) Field with this name will be
given modeling_role `output-token-count`.
:attr str label_column: (optional)
:attr List[str] labels: (optional)
:attr dict dashboard_configuration: (optional)
:attr str predicted_target_field: (optional) Field with this name will be given
modeling_role `decoded-target`.
:attr str prediction_field: (optional) Field with this name will be given
modeling_role `prediction`.
:attr str transaction_id_field: (optional) Field with this name will have
`transaction_id_key` metadata set to true.
:attr List[str] feature_fields: (optional) Fields to be given modeling_role
feature.
:attr List[str] categorical_fields: (optional) Fields to be given metadata
`measure` of value `discrete`.
:attr List[str] context_fields: (optional) Contexts fields with this name will
be given `prompt_role` as `context_field` used in Retrieval-Augmented
Generation.
:attr str question_field: (optional) Question field with this name will be given
`prompt_role` as `question_field` used in Retrieval-Augmented Generation.
:attr List[str] probability_fields: (optional) Fields to be given modeling_role
`class_probability` (for columns of double data type) or `probability` (for
column of array data type).
:attr List[str] prediction_names: (optional) Prediction names for multiple
output models.
"""
def __init__(self,
*,
training_data_reference: 'SecretCleaned' = None,
training_data_schema: 'SparkStruct' = None,
input_data_schema: 'SparkStruct' = None,
output_data_schema: 'SparkStruct' = None,
input_token_count_field: str = None,
output_token_count_field: str = None,
label_column: str = None,
labels: List[str] = None,
dashboard_configuration: dict = None,
predicted_target_field: str = None,
prediction_field: str = None,
transaction_id_field: str = None,
feature_fields: List[str] = None,
categorical_fields: List[str] = None,
context_fields: List[str] = None,
question_field: str = None,
probability_fields: List[str] = None,
prediction_names: List[str] = None) -> None:
"""
Initialize a AssetProperties object.
:param SecretCleaned training_data_reference: (optional)
:param SparkStruct training_data_schema: (optional)
:param SparkStruct input_data_schema: (optional)
:param SparkStruct output_data_schema: (optional)
:param str input_token_count_field: (optional) Field with this name will be
given modeling_role `input-token-count`.
:param str output_token_count_field: (optional) Field with this name will
be given modeling_role `output-token-count`.
:param str label_column: (optional)
:param List[str] labels: (optional)
:param dict dashboard_configuration: (optional)
:param str predicted_target_field: (optional) Field with this name will be
given modeling_role `decoded-target`.
:param str prediction_field: (optional) Field with this name will be given
modeling_role `prediction`.
:param str transaction_id_field: (optional) Field with this name will have
`transaction_id_key` metadata set to true.
:param List[str] feature_fields: (optional) Fields to be given
modeling_role feature.
:param List[str] categorical_fields: (optional) Fields to be given metadata
`measure` of value `discrete`.
:param List[str] context_fields: (optional) Contexts fields with this name
will be given `prompt_role` as `context_field` used in Retrieval-Augmented
Generation.
:param str question_field: (optional) Question field with this name will be
given `prompt_role` as `question_field` used in Retrieval-Augmented
Generation.
:param List[str] probability_fields: (optional) Fields to be given
modeling_role `class_probability` (for columns of double data type) or
`probability` (for column of array data type).
:param List[str] prediction_names: (optional) Prediction names for multiple
output models.
"""
self.training_data_reference = training_data_reference
self.training_data_schema = training_data_schema
self.input_data_schema = input_data_schema
self.output_data_schema = output_data_schema
self.input_token_count_field = input_token_count_field
self.output_token_count_field = output_token_count_field
self.label_column = label_column
self.labels = labels
self.dashboard_configuration = dashboard_configuration
self.predicted_target_field = predicted_target_field
self.prediction_field = prediction_field
self.transaction_id_field = transaction_id_field
self.feature_fields = feature_fields
self.categorical_fields = categorical_fields
self.context_fields = context_fields
self.question_field = question_field
self.probability_fields = probability_fields
self.prediction_names = prediction_names
@classmethod
def from_dict(cls, _dict: Dict) -> 'AssetProperties':
"""Initialize a AssetProperties object from a json dictionary."""
args = {}
if 'training_data_reference' in _dict:
args['training_data_reference'] = SecretCleaned.from_dict(_dict.get('training_data_reference'))
if 'training_data_schema' in _dict:
args['training_data_schema'] = SparkStruct.from_dict(_dict.get('training_data_schema'))
if 'input_data_schema' in _dict:
args['input_data_schema'] = SparkStruct.from_dict(_dict.get('input_data_schema'))
if 'output_data_schema' in _dict:
args['output_data_schema'] = SparkStruct.from_dict(_dict.get('output_data_schema'))
if 'input_token_count_field' in _dict:
args['input_token_count_field'] = _dict.get('input_token_count_field')
if 'output_token_count_field' in _dict:
args['output_token_count_field'] = _dict.get('output_token_count_field')
if 'label_column' in _dict:
args['label_column'] = _dict.get('label_column')
if 'labels' in _dict:
args['labels'] = _dict.get('labels')
if 'dashboard_configuration' in _dict:
args['dashboard_configuration'] = _dict.get('dashboard_configuration')
if 'predicted_target_field' in _dict:
args['predicted_target_field'] = _dict.get('predicted_target_field')
if 'prediction_field' in _dict:
args['prediction_field'] = _dict.get('prediction_field')
if 'transaction_id_field' in _dict:
args['transaction_id_field'] = _dict.get('transaction_id_field')
if 'feature_fields' in _dict:
args['feature_fields'] = _dict.get('feature_fields')
if 'categorical_fields' in _dict:
args['categorical_fields'] = _dict.get('categorical_fields')
if 'context_fields' in _dict:
args['context_fields'] = _dict.get('context_fields')
if 'question_field' in _dict:
args['question_field'] = _dict.get('question_field')
if 'probability_fields' in _dict:
args['probability_fields'] = _dict.get('probability_fields')
if 'prediction_names' in _dict:
args['prediction_names'] = _dict.get('prediction_names')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AssetProperties object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'training_data_reference') and self.training_data_reference is not None:
_dict['training_data_reference'] = self.training_data_reference.to_dict()
if hasattr(self, 'training_data_schema') and self.training_data_schema is not None:
_dict['training_data_schema'] = self.training_data_schema.to_dict()
if hasattr(self, 'input_data_schema') and self.input_data_schema is not None:
_dict['input_data_schema'] = self.input_data_schema.to_dict()
if hasattr(self, 'output_data_schema') and self.output_data_schema is not None:
_dict['output_data_schema'] = self.output_data_schema.to_dict()
if hasattr(self, 'input_token_count_field') and self.input_token_count_field is not None:
_dict['input_token_count_field'] = self.input_token_count_field
if hasattr(self, 'output_token_count_field') and self.output_token_count_field is not None:
_dict['output_token_count_field'] = self.output_token_count_field
if hasattr(self, 'label_column') and self.label_column is not None:
_dict['label_column'] = self.label_column
if hasattr(self, 'labels') and self.labels is not None:
_dict['labels'] = self.labels
if hasattr(self, 'dashboard_configuration') and self.dashboard_configuration is not None:
_dict['dashboard_configuration'] = self.dashboard_configuration
if hasattr(self, 'predicted_target_field') and self.predicted_target_field is not None:
_dict['predicted_target_field'] = self.predicted_target_field
if hasattr(self, 'prediction_field') and self.prediction_field is not None:
_dict['prediction_field'] = self.prediction_field
if hasattr(self, 'transaction_id_field') and self.transaction_id_field is not None:
_dict['transaction_id_field'] = self.transaction_id_field
if hasattr(self, 'feature_fields') and self.feature_fields is not None:
_dict['feature_fields'] = self.feature_fields
if hasattr(self, 'categorical_fields') and self.categorical_fields is not None:
_dict['categorical_fields'] = self.categorical_fields
if hasattr(self, 'context_fields') and self.context_fields is not None:
_dict['context_fields'] = self.context_fields
if hasattr(self, 'question_field') and self.question_field is not None:
_dict['question_field'] = self.question_field
if hasattr(self, 'probability_fields') and self.probability_fields is not None:
_dict['probability_fields'] = self.probability_fields
if hasattr(self, 'prediction_names') and self.prediction_names is not None:
_dict['prediction_names'] = self.prediction_names
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AssetProperties object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AssetProperties') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AssetProperties') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class AssetPropertiesRequest():
"""
Additional asset properties (subject of discovery if not provided when creating the
subscription).
:attr TrainingDataReference training_data_reference: (optional)
:attr SparkStruct training_data_schema: (optional)
:attr SparkStruct input_data_schema: (optional)
:attr SparkStruct output_data_schema: (optional)
:attr str input_token_count_field: (optional) Field with this name will be given
modeling_role `input-token-count`.
:attr str output_token_count_field: (optional) Field with this name will be
given modeling_role `output-token-count`.
:attr str label_column: (optional)
:attr List[str] labels: (optional)
:attr dict dashboard_configuration: (optional)
:attr str predicted_target_field: (optional) Field with this name will be given
modeling_role `decoded-target`.
:attr str prediction_field: (optional) Field with this name will be given
modeling_role `prediction`.
:attr str transaction_id_field: (optional) Field with this name will have
`transaction_id_key` metadata set to true.
:attr List[str] feature_fields: (optional) Fields to be given modeling_role
feature.
:attr List[str] categorical_fields: (optional) Fields to be given metadata
`measure` of value `discrete`.
:attr List[str] context_fields: (optional) Contexts fields with this name will
be given `prompt_role` as `context_field` used in Retrieval-Augmented
Generation.
:attr str question_field: (optional) Question field with this name will be given
`prompt_role` as `question_field` used in Retrieval-Augmented Generation.
:attr List[str] probability_fields: (optional) Fields to be given modeling_role
`class_probability` (for columns of double data type) or `probability` (for
column of array data type).
:attr List[str] prediction_names: (optional) Prediction names for multiple
output models.
"""
def __init__(self,
*,
training_data_reference: 'TrainingDataReference' = None,
training_data_schema: 'SparkStruct' = None,
input_data_schema: 'SparkStruct' = None,
output_data_schema: 'SparkStruct' = None,
input_token_count_field: str = None,
output_token_count_field: str = None,
label_column: str = None,
labels: List[str] = None,
dashboard_configuration: dict = None,
predicted_target_field: str = None,
prediction_field: str = None,
transaction_id_field: str = None,
feature_fields: List[str] = None,
categorical_fields: List[str] = None,
context_fields: List[str] = None,
question_field: str = None,
probability_fields: List[str] = None,
prediction_names: List[str] = None) -> None:
"""
Initialize a AssetPropertiesRequest object.
:param TrainingDataReference training_data_reference: (optional)
:param SparkStruct training_data_schema: (optional)
:param SparkStruct input_data_schema: (optional)
:param SparkStruct output_data_schema: (optional)
:param str input_token_count_field: (optional) Field with this name will be
given modeling_role `input-token-count`.
:param str output_token_count_field: (optional) Field with this name will
be given modeling_role `output-token-count`.
:param str label_column: (optional)
:param List[str] labels: (optional)
:param dict dashboard_configuration: (optional)
:param str predicted_target_field: (optional) Field with this name will be
given modeling_role `decoded-target`.
:param str prediction_field: (optional) Field with this name will be given
modeling_role `prediction`.
:param str transaction_id_field: (optional) Field with this name will have
`transaction_id_key` metadata set to true.
:param List[str] feature_fields: (optional) Fields to be given
modeling_role feature.
:param List[str] categorical_fields: (optional) Fields to be given metadata
`measure` of value `discrete`.
:param List[str] context_fields: (optional) Contexts fields with this name
will be given `prompt_role` as `context_field` used in Retrieval-Augmented
Generation.
:param str question_field: (optional) Question field with this name will be
given `prompt_role` as `question_field` used in Retrieval-Augmented
Generation.
:param List[str] probability_fields: (optional) Fields to be given
modeling_role `class_probability` (for columns of double data type) or
`probability` (for column of array data type).
:param List[str] prediction_names: (optional) Prediction names for multiple
output models.
"""
self.training_data_reference = training_data_reference
self.training_data_schema = training_data_schema
self.input_data_schema = input_data_schema
self.output_data_schema = output_data_schema
self.input_token_count_field = input_token_count_field
self.output_token_count_field = output_token_count_field
self.label_column = label_column
self.labels = labels
self.dashboard_configuration = dashboard_configuration
self.predicted_target_field = predicted_target_field
self.prediction_field = prediction_field
self.transaction_id_field = transaction_id_field
self.feature_fields = feature_fields
self.categorical_fields = categorical_fields
self.context_fields = context_fields
self.question_field = question_field
self.probability_fields = probability_fields
self.prediction_names = prediction_names
@classmethod
def from_dict(cls, _dict: Dict) -> 'AssetPropertiesRequest':
"""Initialize a AssetPropertiesRequest object from a json dictionary."""
args = {}
if 'training_data_reference' in _dict:
args['training_data_reference'] = TrainingDataReference.from_dict(_dict.get('training_data_reference'))
if 'training_data_schema' in _dict:
args['training_data_schema'] = SparkStruct.from_dict(_dict.get('training_data_schema'))
if 'input_data_schema' in _dict:
args['input_data_schema'] = SparkStruct.from_dict(_dict.get('input_data_schema'))
if 'output_data_schema' in _dict:
args['output_data_schema'] = SparkStruct.from_dict(_dict.get('output_data_schema'))
if 'input_token_count_field' in _dict:
args['input_token_count_field'] = _dict.get('input_token_count_field')
if 'output_token_count_field' in _dict:
args['output_token_count_field'] = _dict.get('output_token_count_field')
if 'label_column' in _dict:
args['label_column'] = _dict.get('label_column')
if 'labels' in _dict:
args['labels'] = _dict.get('labels')
if 'dashboard_configuration' in _dict:
args['dashboard_configuration'] = _dict.get('dashboard_configuration')
if 'predicted_target_field' in _dict:
args['predicted_target_field'] = _dict.get('predicted_target_field')
if 'prediction_field' in _dict:
args['prediction_field'] = _dict.get('prediction_field')
if 'transaction_id_field' in _dict:
args['transaction_id_field'] = _dict.get('transaction_id_field')
if 'feature_fields' in _dict:
args['feature_fields'] = _dict.get('feature_fields')
if 'categorical_fields' in _dict:
args['categorical_fields'] = _dict.get('categorical_fields')
if 'context_fields' in _dict:
args['context_fields'] = _dict.get('context_fields')
if 'question_field' in _dict:
args['question_field'] = _dict.get('question_field')
if 'probability_fields' in _dict:
args['probability_fields'] = _dict.get('probability_fields')
if 'prediction_names' in _dict:
args['prediction_names'] = _dict.get('prediction_names')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AssetPropertiesRequest object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'training_data_reference') and self.training_data_reference is not None:
_dict['training_data_reference'] = self.training_data_reference.to_dict()
if hasattr(self, 'training_data_schema') and self.training_data_schema is not None:
_dict['training_data_schema'] = self.training_data_schema.to_dict()
if hasattr(self, 'input_data_schema') and self.input_data_schema is not None:
_dict['input_data_schema'] = self.input_data_schema.to_dict()
if hasattr(self, 'output_data_schema') and self.output_data_schema is not None:
_dict['output_data_schema'] = self.output_data_schema.to_dict()
if hasattr(self, 'input_token_count_field') and self.input_token_count_field is not None:
_dict['input_token_count_field'] = self.input_token_count_field
if hasattr(self, 'output_token_count_field') and self.output_token_count_field is not None:
_dict['output_token_count_field'] = self.output_token_count_field
if hasattr(self, 'label_column') and self.label_column is not None:
_dict['label_column'] = self.label_column
if hasattr(self, 'labels') and self.labels is not None:
_dict['labels'] = self.labels
if hasattr(self, 'dashboard_configuration') and self.dashboard_configuration is not None:
_dict['dashboard_configuration'] = self.dashboard_configuration
if hasattr(self, 'predicted_target_field') and self.predicted_target_field is not None:
_dict['predicted_target_field'] = self.predicted_target_field
if hasattr(self, 'prediction_field') and self.prediction_field is not None:
_dict['prediction_field'] = self.prediction_field
if hasattr(self, 'transaction_id_field') and self.transaction_id_field is not None:
_dict['transaction_id_field'] = self.transaction_id_field
if hasattr(self, 'feature_fields') and self.feature_fields is not None:
_dict['feature_fields'] = self.feature_fields
if hasattr(self, 'categorical_fields') and self.categorical_fields is not None:
_dict['categorical_fields'] = self.categorical_fields
if hasattr(self, 'context_fields') and self.context_fields is not None:
_dict['context_fields'] = self.context_fields
if hasattr(self, 'question_field') and self.question_field is not None:
_dict['question_field'] = self.question_field
if hasattr(self, 'probability_fields') and self.probability_fields is not None:
_dict['probability_fields'] = self.probability_fields
if hasattr(self, 'prediction_names') and self.prediction_names is not None:
_dict['prediction_names'] = self.prediction_names
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AssetPropertiesRequest object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AssetPropertiesRequest') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AssetPropertiesRequest') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class AzureWorkspaceCredentials():
"""
AzureWorkspaceCredentials.
:attr str workspace_id:
:attr str token:
"""
def __init__(self,
workspace_id: str,
token: str) -> None:
"""
Initialize a AzureWorkspaceCredentials object.
:param str workspace_id:
:param str token:
"""
self.workspace_id = workspace_id
self.token = token
@classmethod
def from_dict(cls, _dict: Dict) -> 'AzureWorkspaceCredentials':
"""Initialize a AzureWorkspaceCredentials object from a json dictionary."""
args = {}
if 'workspace_id' in _dict:
args['workspace_id'] = _dict.get('workspace_id')
else:
raise ValueError('Required property \'workspace_id\' not present in AzureWorkspaceCredentials JSON')
if 'token' in _dict:
args['token'] = _dict.get('token')
else:
raise ValueError('Required property \'token\' not present in AzureWorkspaceCredentials JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AzureWorkspaceCredentials object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'workspace_id') and self.workspace_id is not None:
_dict['workspace_id'] = self.workspace_id
if hasattr(self, 'token') and self.token is not None:
_dict['token'] = self.token
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AzureWorkspaceCredentials object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AzureWorkspaceCredentials') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AzureWorkspaceCredentials') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class CollectionUrlModel():
"""
CollectionUrlModel.
:attr str url: URI of a resource.
"""
def __init__(self,
url: str) -> None:
"""
Initialize a CollectionUrlModel object.
:param str url: URI of a resource.
"""
self.url = url
@classmethod
def from_dict(cls, _dict: Dict) -> 'CollectionUrlModel':
"""Initialize a CollectionUrlModel object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
else:
raise ValueError('Required property \'url\' not present in CollectionUrlModel JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a CollectionUrlModel object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this CollectionUrlModel object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'CollectionUrlModel') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'CollectionUrlModel') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ConfigurationSynchronization():
"""
ConfigurationSynchronization.
:attr List[ConfigurationSynchronizationConfigurationsItem] configurations:
(optional)
"""
def __init__(self,
*,
configurations: List['ConfigurationSynchronizationConfigurationsItem'] = None) -> None:
"""
Initialize a ConfigurationSynchronization object.
:param List[ConfigurationSynchronizationConfigurationsItem] configurations:
(optional)
"""
self.configurations = configurations
@classmethod
def from_dict(cls, _dict: Dict) -> 'ConfigurationSynchronization':
"""Initialize a ConfigurationSynchronization object from a json dictionary."""
args = {}
if 'configurations' in _dict:
args['configurations'] = [ConfigurationSynchronizationConfigurationsItem.from_dict(x) for x in _dict.get('configurations')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ConfigurationSynchronization object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'configurations') and self.configurations is not None:
_dict['configurations'] = [x.to_dict() for x in self.configurations]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ConfigurationSynchronization object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ConfigurationSynchronization') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ConfigurationSynchronization') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ConfigurationSynchronizationConfigurationsItem():
"""
ConfigurationSynchronizationConfigurationsItem.
:attr str monitor_definition_id: (optional)
:attr str monitor_instance_id: (optional)
:attr str monitor_instance_status: (optional)
:attr GraphVertexProperties source_properties: (optional)
:attr str status: (optional)
:attr GraphVertexProperties target_properties: (optional)
"""
def __init__(self,
*,
monitor_definition_id: str = None,
monitor_instance_id: str = None,
monitor_instance_status: str = None,
source_properties: 'GraphVertexProperties' = None,
status: str = None,
target_properties: 'GraphVertexProperties' = None) -> None:
"""
Initialize a ConfigurationSynchronizationConfigurationsItem object.
:param str monitor_definition_id: (optional)
:param str monitor_instance_id: (optional)
:param str monitor_instance_status: (optional)
:param GraphVertexProperties source_properties: (optional)
:param str status: (optional)
:param GraphVertexProperties target_properties: (optional)
"""
self.monitor_definition_id = monitor_definition_id
self.monitor_instance_id = monitor_instance_id
self.monitor_instance_status = monitor_instance_status
self.source_properties = source_properties
self.status = status
self.target_properties = target_properties
@classmethod
def from_dict(cls, _dict: Dict) -> 'ConfigurationSynchronizationConfigurationsItem':
"""Initialize a ConfigurationSynchronizationConfigurationsItem object from a json dictionary."""
args = {}
if 'monitor_definition_id' in _dict:
args['monitor_definition_id'] = _dict.get('monitor_definition_id')
if 'monitor_instance_id' in _dict:
args['monitor_instance_id'] = _dict.get('monitor_instance_id')
if 'monitor_instance_status' in _dict:
args['monitor_instance_status'] = _dict.get('monitor_instance_status')
if 'source_properties' in _dict:
args['source_properties'] = GraphVertexProperties.from_dict(_dict.get('source_properties'))
if 'status' in _dict:
args['status'] = _dict.get('status')
if 'target_properties' in _dict:
args['target_properties'] = GraphVertexProperties.from_dict(_dict.get('target_properties'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ConfigurationSynchronizationConfigurationsItem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'monitor_definition_id') and self.monitor_definition_id is not None:
_dict['monitor_definition_id'] = self.monitor_definition_id
if hasattr(self, 'monitor_instance_id') and self.monitor_instance_id is not None:
_dict['monitor_instance_id'] = self.monitor_instance_id
if hasattr(self, 'monitor_instance_status') and self.monitor_instance_status is not None:
_dict['monitor_instance_status'] = self.monitor_instance_status
if hasattr(self, 'source_properties') and self.source_properties is not None:
_dict['source_properties'] = self.source_properties.to_dict()
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status
if hasattr(self, 'target_properties') and self.target_properties is not None:
_dict['target_properties'] = self.target_properties.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ConfigurationSynchronizationConfigurationsItem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ConfigurationSynchronizationConfigurationsItem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ConfigurationSynchronizationConfigurationsItem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataDistributionResponse():
"""
Data distribution details response.
:attr Metadata metadata:
:attr DataDistributionResponseEntity entity: The computed data distribution
against specified data set.
"""
def __init__(self,
metadata: 'Metadata',
entity: 'DataDistributionResponseEntity') -> None:
"""
Initialize a DataDistributionResponse object.
:param Metadata metadata:
:param DataDistributionResponseEntity entity: The computed data
distribution against specified data set.
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataDistributionResponse':
"""Initialize a DataDistributionResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in DataDistributionResponse JSON')
if 'entity' in _dict:
args['entity'] = DataDistributionResponseEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in DataDistributionResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataDistributionResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataDistributionResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataDistributionResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataDistributionResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataDistributionResponseEntity():
"""
The computed data distribution against specified data set.
:attr str start: start datetime in ISO format.
:attr str end: end datetime in ISO format.
:attr str dataset: type of a data set.
:attr float limit: (optional) limit for number of rows, by default it is 50,000
(max possible limit is 50,000).
:attr List[str] group: names of columns to be grouped.
:attr str filter: (optional) Filters defined by user in format:
{field_name}:{op}:{value}. Partly compatible with filters in "filter" parameter
of GET /v2/data_sets/{data_set_id}/records.
Possible filter operators:
* eq - equals (numeric, string)
* gt - greater than (numeric)
* gte - greater than or equal (numeric)
* lt - lower than (numeric)
* lte - lower than or equal (numeric)
* in - value in a set (numeric, string)
* field:null (a no-argument filter) - value is null (any nullable)
* field:exists (a no-argument filter) - value is not null (any column).
:attr List[str] agg: (optional) Definition of aggregations, by default 'count'.
Aggregations can be one of:
* count
* <column_name>:sum
* <column_name>:min
* <column_name>:max
* <column_name>:avg
* <column_name>:stddev.
:attr float max_bins: (optional) max number of bins which will be generated for
data.
:attr MonitoringRunStatus status: (optional) The status information for the
monitoring run.
:attr float processed_records: (optional) number of processed records.
:attr bool limited_data: (optional) was the limit used on data.
:attr DataDistributionResponseEntityDistribution distribution: (optional)
"""
def __init__(self,
start: str,
end: str,
dataset: str,
group: List[str],
*,
limit: float = None,
filter: str = None,
agg: List[str] = None,
max_bins: float = None,
status: 'MonitoringRunStatus' = None,
processed_records: float = None,
limited_data: bool = None,
distribution: 'DataDistributionResponseEntityDistribution' = None) -> None:
"""
Initialize a DataDistributionResponseEntity object.
:param str start: start datetime in ISO format.
:param str end: end datetime in ISO format.
:param str dataset: type of a data set.
:param List[str] group: names of columns to be grouped.
:param float limit: (optional) limit for number of rows, by default it is
50,000 (max possible limit is 50,000).
:param str filter: (optional) Filters defined by user in format:
{field_name}:{op}:{value}. Partly compatible with filters in "filter"
parameter of GET /v2/data_sets/{data_set_id}/records.
Possible filter operators:
* eq - equals (numeric, string)
* gt - greater than (numeric)
* gte - greater than or equal (numeric)
* lt - lower than (numeric)
* lte - lower than or equal (numeric)
* in - value in a set (numeric, string)
* field:null (a no-argument filter) - value is null (any nullable)
* field:exists (a no-argument filter) - value is not null (any column).
:param List[str] agg: (optional) Definition of aggregations, by default
'count'.
Aggregations can be one of:
* count
* <column_name>:sum
* <column_name>:min
* <column_name>:max
* <column_name>:avg
* <column_name>:stddev.
:param float max_bins: (optional) max number of bins which will be
generated for data.
:param MonitoringRunStatus status: (optional) The status information for
the monitoring run.
:param float processed_records: (optional) number of processed records.
:param bool limited_data: (optional) was the limit used on data.
:param DataDistributionResponseEntityDistribution distribution: (optional)
"""
self.start = start
self.end = end
self.dataset = dataset
self.limit = limit
self.group = group
self.filter = filter
self.agg = agg
self.max_bins = max_bins
self.status = status
self.processed_records = processed_records
self.limited_data = limited_data
self.distribution = distribution
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataDistributionResponseEntity':
"""Initialize a DataDistributionResponseEntity object from a json dictionary."""
args = {}
if 'start' in _dict:
args['start'] = _dict.get('start')
else:
raise ValueError('Required property \'start\' not present in DataDistributionResponseEntity JSON')
if 'end' in _dict:
args['end'] = _dict.get('end')
else:
raise ValueError('Required property \'end\' not present in DataDistributionResponseEntity JSON')
if 'dataset' in _dict:
args['dataset'] = _dict.get('dataset')
else:
raise ValueError('Required property \'dataset\' not present in DataDistributionResponseEntity JSON')
if 'limit' in _dict:
args['limit'] = _dict.get('limit')
if 'group' in _dict:
args['group'] = _dict.get('group')
else:
raise ValueError('Required property \'group\' not present in DataDistributionResponseEntity JSON')
if 'filter' in _dict:
args['filter'] = _dict.get('filter')
if 'agg' in _dict:
args['agg'] = _dict.get('agg')
if 'max_bins' in _dict:
args['max_bins'] = _dict.get('max_bins')
if 'status' in _dict:
args['status'] = MonitoringRunStatus.from_dict(_dict.get('status'))
if 'processed_records' in _dict:
args['processed_records'] = _dict.get('processed_records')
if 'limited_data' in _dict:
args['limited_data'] = _dict.get('limited_data')
if 'distribution' in _dict:
args['distribution'] = DataDistributionResponseEntityDistribution.from_dict(_dict.get('distribution'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataDistributionResponseEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'start') and self.start is not None:
_dict['start'] = self.start
if hasattr(self, 'end') and self.end is not None:
_dict['end'] = self.end
if hasattr(self, 'dataset') and self.dataset is not None:
_dict['dataset'] = self.dataset
if hasattr(self, 'limit') and self.limit is not None:
_dict['limit'] = self.limit
if hasattr(self, 'group') and self.group is not None:
_dict['group'] = self.group
if hasattr(self, 'filter') and self.filter is not None:
_dict['filter'] = self.filter
if hasattr(self, 'agg') and self.agg is not None:
_dict['agg'] = self.agg
if hasattr(self, 'max_bins') and self.max_bins is not None:
_dict['max_bins'] = self.max_bins
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
if hasattr(self, 'processed_records') and self.processed_records is not None:
_dict['processed_records'] = self.processed_records
if hasattr(self, 'limited_data') and self.limited_data is not None:
_dict['limited_data'] = self.limited_data
if hasattr(self, 'distribution') and self.distribution is not None:
_dict['distribution'] = self.distribution.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataDistributionResponseEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataDistributionResponseEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataDistributionResponseEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DatasetEnum(str, Enum):
"""
type of a data set.
"""
MANUAL_LABELING = 'manual_labeling'
PAYLOAD_LOGGING = 'payload_logging'
FEEDBACK = 'feedback'
BUSINESS_PAYLOAD = 'business_payload'
EXPLANATIONS = 'explanations'
EXPLANATIONS_WHATIF = 'explanations_whatif'
TRAINING = 'training'
PAYLOAD_LOGGING_ERROR = 'payload_logging_error'
MODEL_HEALTH = 'model_health'
DRIFT_STATS = 'drift_stats'
DRIFT_INTERVALS = 'drift_intervals'
DRIFT_INSIGHTS = 'drift_insights'
GEN_AI_QUALITY_METRICS = 'gen_ai_quality_metrics'
GEN_AI_SECURITY_METRICS = 'gen_ai_security_metrics'
DRIFT_SCORES = 'drift_scores'
AIDC_FEEDBACK = 'aidc_feedback'
CUSTOM = 'custom'
NODES_INFO = 'nodes_info'
EDGES_INFO = 'edges_info'
AGENTIC_APP_IO = 'agentic_app_io'
NODES_IO = 'nodes_io'
AGENTIC_APP_METRICS = 'agentic_app_metrics'
SPANS = 'spans'
class DataDistributionResponseEntityDistribution():
"""
DataDistributionResponseEntityDistribution.
:attr List[str] fields: names of the data distribution fields.
:attr List[object] values: data distribution rows.
"""
def __init__(self,
fields: List[str],
values: List[object]) -> None:
"""
Initialize a DataDistributionResponseEntityDistribution object.
:param List[str] fields: names of the data distribution fields.
:param List[object] values: data distribution rows.
"""
self.fields = fields
self.values = values
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataDistributionResponseEntityDistribution':
"""Initialize a DataDistributionResponseEntityDistribution object from a json dictionary."""
args = {}
if 'fields' in _dict:
args['fields'] = _dict.get('fields')
else:
raise ValueError('Required property \'fields\' not present in DataDistributionResponseEntityDistribution JSON')
if 'values' in _dict:
args['values'] = _dict.get('values')
else:
raise ValueError('Required property \'values\' not present in DataDistributionResponseEntityDistribution JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataDistributionResponseEntityDistribution object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'fields') and self.fields is not None:
_dict['fields'] = self.fields
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = self.values
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataDistributionResponseEntityDistribution object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataDistributionResponseEntityDistribution') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataDistributionResponseEntityDistribution') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartDatabaseResponse():
"""
DataMartDatabaseResponse.
:attr Metadata metadata:
:attr DataMartDatabaseResponseEntity entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'DataMartDatabaseResponseEntity') -> None:
"""
Initialize a DataMartDatabaseResponse object.
:param Metadata metadata:
:param DataMartDatabaseResponseEntity entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartDatabaseResponse':
"""Initialize a DataMartDatabaseResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in DataMartDatabaseResponse JSON')
if 'entity' in _dict:
args['entity'] = DataMartDatabaseResponseEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in DataMartDatabaseResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartDatabaseResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartDatabaseResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartDatabaseResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartDatabaseResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartDatabaseResponseCollection():
"""
DataMartDatabaseResponseCollection.
:attr List[DataMartDatabaseResponse] data_marts:
"""
def __init__(self,
data_marts: List['DataMartDatabaseResponse']) -> None:
"""
Initialize a DataMartDatabaseResponseCollection object.
:param List[DataMartDatabaseResponse] data_marts:
"""
self.data_marts = data_marts
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartDatabaseResponseCollection':
"""Initialize a DataMartDatabaseResponseCollection object from a json dictionary."""
args = {}
if 'data_marts' in _dict:
args['data_marts'] = [DataMartDatabaseResponse.from_dict(x) for x in _dict.get('data_marts')]
else:
raise ValueError('Required property \'data_marts\' not present in DataMartDatabaseResponseCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartDatabaseResponseCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'data_marts') and self.data_marts is not None:
_dict['data_marts'] = [x.to_dict() for x in self.data_marts]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartDatabaseResponseCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartDatabaseResponseCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartDatabaseResponseCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartDatabaseResponseEntity():
"""
DataMartDatabaseResponseEntity.
:attr str name: (optional)
:attr str description: (optional)
:attr str service_instance_crn: (optional)
:attr bool internal_database: (optional) If `true` the internal database managed
by AI OpenScale is provided for the user.
:attr DatabaseConfiguration database_configuration: (optional) Database
configuration ignored if internal database is requested (`internal_database` is
`true`).
:attr str database_discovery: (optional) Used by UI to check if database
discovery was automatic or manual.
:attr Status status: (optional)
"""
def __init__(self,
*,
name: str = None,
description: str = None,
service_instance_crn: str = None,
internal_database: bool = None,
database_configuration: 'DatabaseConfiguration' = None,
database_discovery: str = None,
status: 'Status' = None) -> None:
"""
Initialize a DataMartDatabaseResponseEntity object.
:param str name: (optional)
:param str description: (optional)
:param str service_instance_crn: (optional)
:param bool internal_database: (optional) If `true` the internal database
managed by AI OpenScale is provided for the user.
:param DatabaseConfiguration database_configuration: (optional) Database
configuration ignored if internal database is requested
(`internal_database` is `true`).
:param str database_discovery: (optional) Used by UI to check if database
discovery was automatic or manual.
:param Status status: (optional)
"""
self.name = name
self.description = description
self.service_instance_crn = service_instance_crn
self.internal_database = internal_database
self.database_configuration = database_configuration
self.database_discovery = database_discovery
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartDatabaseResponseEntity':
"""Initialize a DataMartDatabaseResponseEntity object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'service_instance_crn' in _dict:
args['service_instance_crn'] = _dict.get('service_instance_crn')
if 'internal_database' in _dict:
args['internal_database'] = _dict.get('internal_database')
if 'database_configuration' in _dict:
args['database_configuration'] = DatabaseConfiguration.from_dict(_dict.get('database_configuration'))
if 'database_discovery' in _dict:
args['database_discovery'] = _dict.get('database_discovery')
if 'status' in _dict:
args['status'] = Status.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartDatabaseResponseEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'service_instance_crn') and self.service_instance_crn is not None:
_dict['service_instance_crn'] = self.service_instance_crn
if hasattr(self, 'internal_database') and self.internal_database is not None:
_dict['internal_database'] = self.internal_database
if hasattr(self, 'database_configuration') and self.database_configuration is not None:
_dict['database_configuration'] = self.database_configuration.to_dict()
if hasattr(self, 'database_discovery') and self.database_discovery is not None:
_dict['database_discovery'] = self.database_discovery
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartDatabaseResponseEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartDatabaseResponseEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartDatabaseResponseEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DatabaseDiscoveryEnum(str, Enum):
"""
Used by UI to check if database discovery was automatic or manual.
"""
AUTOMATIC = 'automatic'
MANUAL = 'manual'
class DataMartGetMonitorInstanceMetrics():
"""
DataMartGetMonitorInstanceMetrics.
:attr datetime start: (optional) Floored to full interval.
:attr datetime end: (optional) Ceiled to full interval.
:attr str interval: (optional)
:attr str monitor_definition_id: (optional)
:attr List[DataMartGetMonitorInstanceMetricsGroupsItem] groups: (optional)
"""
def __init__(self,
*,
start: datetime = None,
end: datetime = None,
interval: str = None,
monitor_definition_id: str = None,
groups: List['DataMartGetMonitorInstanceMetricsGroupsItem'] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetrics object.
:param datetime start: (optional) Floored to full interval.
:param datetime end: (optional) Ceiled to full interval.
:param str interval: (optional)
:param str monitor_definition_id: (optional)
:param List[DataMartGetMonitorInstanceMetricsGroupsItem] groups: (optional)
"""
self.start = start
self.end = end
self.interval = interval
self.monitor_definition_id = monitor_definition_id
self.groups = groups
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetrics':
"""Initialize a DataMartGetMonitorInstanceMetrics object from a json dictionary."""
args = {}
if 'start' in _dict:
args['start'] = string_to_datetime(_dict.get('start'))
if 'end' in _dict:
args['end'] = string_to_datetime(_dict.get('end'))
if 'interval' in _dict:
args['interval'] = _dict.get('interval')
if 'monitor_definition_id' in _dict:
args['monitor_definition_id'] = _dict.get('monitor_definition_id')
if 'groups' in _dict:
args['groups'] = [DataMartGetMonitorInstanceMetricsGroupsItem.from_dict(x) for x in _dict.get('groups')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetrics object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'start') and self.start is not None:
_dict['start'] = datetime_to_string(self.start)
if hasattr(self, 'end') and self.end is not None:
_dict['end'] = datetime_to_string(self.end)
if hasattr(self, 'interval') and self.interval is not None:
_dict['interval'] = self.interval
if hasattr(self, 'monitor_definition_id') and self.monitor_definition_id is not None:
_dict['monitor_definition_id'] = self.monitor_definition_id
if hasattr(self, 'groups') and self.groups is not None:
_dict['groups'] = [x.to_dict() for x in self.groups]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetrics object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetrics') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetrics') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItem():
"""
DataMartGetMonitorInstanceMetricsGroupsItem.
:attr List[DataMartGetMonitorInstanceMetricsGroupsItemTagsItem] tags: (optional)
:attr List[DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem] metrics:
(optional)
"""
def __init__(self,
*,
tags: List['DataMartGetMonitorInstanceMetricsGroupsItemTagsItem'] = None,
metrics: List['DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem'] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItem object.
:param List[DataMartGetMonitorInstanceMetricsGroupsItemTagsItem] tags:
(optional)
:param List[DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem]
metrics: (optional)
"""
self.tags = tags
self.metrics = metrics
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItem':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItem object from a json dictionary."""
args = {}
if 'tags' in _dict:
args['tags'] = [DataMartGetMonitorInstanceMetricsGroupsItemTagsItem.from_dict(x) for x in _dict.get('tags')]
if 'metrics' in _dict:
args['metrics'] = [DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem.from_dict(x) for x in _dict.get('metrics')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'tags') and self.tags is not None:
_dict['tags'] = [x.to_dict() for x in self.tags]
if hasattr(self, 'metrics') and self.metrics is not None:
_dict['metrics'] = [x.to_dict() for x in self.metrics]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem.
:attr str id:
:attr float lower_limit: (optional)
:attr float upper_limit: (optional)
:attr DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast last:
(optional)
:attr DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst first:
(optional)
:attr DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum sum: (optional)
:attr DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg avg: (optional)
:attr DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin min: (optional)
:attr DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax max: (optional)
:attr DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian median:
(optional)
:attr DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount count:
(optional)
:attr DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev stddev:
(optional)
"""
def __init__(self,
id: str,
*,
lower_limit: float = None,
upper_limit: float = None,
last: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast' = None,
first: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst' = None,
sum: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum' = None,
avg: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg' = None,
min: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin' = None,
max: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax' = None,
median: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian' = None,
count: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount' = None,
stddev: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev' = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem object.
:param str id:
:param float lower_limit: (optional)
:param float upper_limit: (optional)
:param DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast last:
(optional)
:param DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst first:
(optional)
:param DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum sum:
(optional)
:param DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg avg:
(optional)
:param DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin min:
(optional)
:param DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax max:
(optional)
:param DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian median:
(optional)
:param DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount count:
(optional)
:param DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev stddev:
(optional)
"""
self.id = id
self.lower_limit = lower_limit
self.upper_limit = upper_limit
self.last = last
self.first = first
self.sum = sum
self.avg = avg
self.min = min
self.max = max
self.median = median
self.count = count
self.stddev = stddev
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem JSON')
if 'lower_limit' in _dict:
args['lower_limit'] = _dict.get('lower_limit')
if 'upper_limit' in _dict:
args['upper_limit'] = _dict.get('upper_limit')
if 'last' in _dict:
args['last'] = DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast.from_dict(_dict.get('last'))
if 'first' in _dict:
args['first'] = DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst.from_dict(_dict.get('first'))
if 'sum' in _dict:
args['sum'] = DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum.from_dict(_dict.get('sum'))
if 'avg' in _dict:
args['avg'] = DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg.from_dict(_dict.get('avg'))
if 'min' in _dict:
args['min'] = DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin.from_dict(_dict.get('min'))
if 'max' in _dict:
args['max'] = DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax.from_dict(_dict.get('max'))
if 'median' in _dict:
args['median'] = DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian.from_dict(_dict.get('median'))
if 'count' in _dict:
args['count'] = DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount.from_dict(_dict.get('count'))
if 'stddev' in _dict:
args['stddev'] = DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev.from_dict(_dict.get('stddev'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'lower_limit') and self.lower_limit is not None:
_dict['lower_limit'] = self.lower_limit
if hasattr(self, 'upper_limit') and self.upper_limit is not None:
_dict['upper_limit'] = self.upper_limit
if hasattr(self, 'last') and self.last is not None:
_dict['last'] = self.last.to_dict()
if hasattr(self, 'first') and self.first is not None:
_dict['first'] = self.first.to_dict()
if hasattr(self, 'sum') and self.sum is not None:
_dict['sum'] = self.sum.to_dict()
if hasattr(self, 'avg') and self.avg is not None:
_dict['avg'] = self.avg.to_dict()
if hasattr(self, 'min') and self.min is not None:
_dict['min'] = self.min.to_dict()
if hasattr(self, 'max') and self.max is not None:
_dict['max'] = self.max.to_dict()
if hasattr(self, 'median') and self.median is not None:
_dict['median'] = self.median.to_dict()
if hasattr(self, 'count') and self.count is not None:
_dict['count'] = self.count.to_dict()
if hasattr(self, 'stddev') and self.stddev is not None:
_dict['stddev'] = self.stddev.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg.
:attr List[float] value: (optional)
"""
def __init__(self,
*,
value: List[float] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg object.
:param List[float] value: (optional)
"""
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemAvg') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount.
:attr List[float] value: (optional)
:attr List[str] measurement_id: (optional)
"""
def __init__(self,
*,
value: List[float] = None,
measurement_id: List[str] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount object.
:param List[float] value: (optional)
:param List[str] measurement_id: (optional)
"""
self.value = value
self.measurement_id = measurement_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
if 'measurement_id' in _dict:
args['measurement_id'] = _dict.get('measurement_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'measurement_id') and self.measurement_id is not None:
_dict['measurement_id'] = self.measurement_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemCount') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst.
:attr List[float] value: (optional)
:attr List[str] measurement_id: (optional)
"""
def __init__(self,
*,
value: List[float] = None,
measurement_id: List[str] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst object.
:param List[float] value: (optional)
:param List[str] measurement_id: (optional)
"""
self.value = value
self.measurement_id = measurement_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
if 'measurement_id' in _dict:
args['measurement_id'] = _dict.get('measurement_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'measurement_id') and self.measurement_id is not None:
_dict['measurement_id'] = self.measurement_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemFirst') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast.
:attr List[float] value: (optional)
:attr List[str] measurement_id: (optional)
"""
def __init__(self,
*,
value: List[float] = None,
measurement_id: List[str] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast object.
:param List[float] value: (optional)
:param List[str] measurement_id: (optional)
"""
self.value = value
self.measurement_id = measurement_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
if 'measurement_id' in _dict:
args['measurement_id'] = _dict.get('measurement_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'measurement_id') and self.measurement_id is not None:
_dict['measurement_id'] = self.measurement_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemLast') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax.
:attr List[float] value: (optional)
:attr List[str] measurement_id: (optional)
"""
def __init__(self,
*,
value: List[float] = None,
measurement_id: List[str] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax object.
:param List[float] value: (optional)
:param List[str] measurement_id: (optional)
"""
self.value = value
self.measurement_id = measurement_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
if 'measurement_id' in _dict:
args['measurement_id'] = _dict.get('measurement_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'measurement_id') and self.measurement_id is not None:
_dict['measurement_id'] = self.measurement_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMax') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian.
:attr List[float] value: (optional)
"""
def __init__(self,
*,
value: List[float] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian object.
:param List[float] value: (optional)
"""
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMedian') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin.
:attr List[float] value: (optional)
:attr List[str] measurement_id: (optional)
"""
def __init__(self,
*,
value: List[float] = None,
measurement_id: List[str] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin object.
:param List[float] value: (optional)
:param List[str] measurement_id: (optional)
"""
self.value = value
self.measurement_id = measurement_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
if 'measurement_id' in _dict:
args['measurement_id'] = _dict.get('measurement_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'measurement_id') and self.measurement_id is not None:
_dict['measurement_id'] = self.measurement_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemMin') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev.
:attr List[float] value: (optional)
"""
def __init__(self,
*,
value: List[float] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev object.
:param List[float] value: (optional)
"""
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemStddev') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum():
"""
DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum.
:attr List[float] value: (optional)
"""
def __init__(self,
*,
value: List[float] = None) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum object.
:param List[float] value: (optional)
"""
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemMetricsItemSum') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataMartGetMonitorInstanceMetricsGroupsItemTagsItem():
"""
DataMartGetMonitorInstanceMetricsGroupsItemTagsItem.
:attr str id:
:attr str value:
"""
def __init__(self,
id: str,
value: str) -> None:
"""
Initialize a DataMartGetMonitorInstanceMetricsGroupsItemTagsItem object.
:param str id:
:param str value:
"""
self.id = id
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataMartGetMonitorInstanceMetricsGroupsItemTagsItem':
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemTagsItem object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in DataMartGetMonitorInstanceMetricsGroupsItemTagsItem JSON')
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError('Required property \'value\' not present in DataMartGetMonitorInstanceMetricsGroupsItemTagsItem JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataMartGetMonitorInstanceMetricsGroupsItemTagsItem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataMartGetMonitorInstanceMetricsGroupsItemTagsItem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemTagsItem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataMartGetMonitorInstanceMetricsGroupsItemTagsItem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataRecord():
"""
DataRecord.
:attr object values: Fields and values of the entity matches JSON object's
fields and values.
:attr dict annotations: (optional) Any JSON object representing annotations.
"""
def __init__(self,
values: object,
*,
annotations: dict = None) -> None:
"""
Initialize a DataRecord object.
:param object values: Fields and values of the entity matches JSON object's
fields and values.
:param dict annotations: (optional) Any JSON object representing
annotations.
"""
self.values = values
self.annotations = annotations
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataRecord':
"""Initialize a DataRecord object from a json dictionary."""
args = {}
if 'values' in _dict:
args['values'] = _dict.get('values')
else:
raise ValueError('Required property \'values\' not present in DataRecord JSON')
if 'annotations' in _dict:
args['annotations'] = _dict.get('annotations')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataRecord object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = self.values
if hasattr(self, 'annotations') and self.annotations is not None:
_dict['annotations'] = self.annotations
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataRecord object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataRecord') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataRecord') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataRecordResponse():
"""
DataRecordResponse.
:attr Metadata metadata:
:attr DataRecord entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'DataRecord') -> None:
"""
Initialize a DataRecordResponse object.
:param Metadata metadata:
:param DataRecord entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataRecordResponse':
"""Initialize a DataRecordResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in DataRecordResponse JSON')
if 'entity' in _dict:
args['entity'] = DataRecord.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in DataRecordResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataRecordResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataRecordResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataRecordResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataRecordResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataRecordResponseList():
"""
DataRecordResponseList.
:attr List[str] fields: Fields' names are listed in order in 'fields'.
:attr List[List[object]] values: Rows organized per fields as described in
'fields'.
:attr List[dict] annotations: (optional) List of annotations objects.
"""
def __init__(self,
fields: List[str],
values: List[List[object]],
*,
annotations: List[dict] = None) -> None:
"""
Initialize a DataRecordResponseList object.
:param List[str] fields: Fields' names are listed in order in 'fields'.
:param List[List[object]] values: Rows organized per fields as described in
'fields'.
:param List[dict] annotations: (optional) List of annotations objects.
"""
self.fields = fields
self.values = values
self.annotations = annotations
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataRecordResponseList':
"""Initialize a DataRecordResponseList object from a json dictionary."""
args = {}
if 'fields' in _dict:
args['fields'] = _dict.get('fields')
else:
raise ValueError('Required property \'fields\' not present in DataRecordResponseList JSON')
if 'values' in _dict:
args['values'] = _dict.get('values')
else:
raise ValueError('Required property \'values\' not present in DataRecordResponseList JSON')
if 'annotations' in _dict:
args['annotations'] = _dict.get('annotations')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataRecordResponseList object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'fields') and self.fields is not None:
_dict['fields'] = self.fields
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = self.values
if hasattr(self, 'annotations') and self.annotations is not None:
_dict['annotations'] = self.annotations
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataRecordResponseList object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataRecordResponseList') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataRecordResponseList') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSetObject():
"""
DataSetObject.
:attr str data_mart_id:
:attr str name:
:attr str description: (optional)
:attr str type: type of a data set.
:attr Target target:
:attr str schema_update_mode: (optional)
:attr SparkStruct data_schema:
:attr LocationTableName location: (optional)
:attr str managed_by: (optional)
:attr Status status:
"""
def __init__(self,
data_mart_id: str,
name: str,
type: str,
target: 'Target',
data_schema: 'SparkStruct',
status: 'Status',
*,
description: str = None,
schema_update_mode: str = None,
location: 'LocationTableName' = None,
managed_by: str = None) -> None:
"""
Initialize a DataSetObject object.
:param str data_mart_id:
:param str name:
:param str type: type of a data set.
:param Target target:
:param SparkStruct data_schema:
:param Status status:
:param str description: (optional)
:param str schema_update_mode: (optional)
:param LocationTableName location: (optional)
:param str managed_by: (optional)
"""
self.data_mart_id = data_mart_id
self.name = name
self.description = description
self.type = type
self.target = target
self.schema_update_mode = schema_update_mode
self.data_schema = data_schema
self.location = location
self.managed_by = managed_by
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSetObject':
"""Initialize a DataSetObject object from a json dictionary."""
args = {}
if 'data_mart_id' in _dict:
args['data_mart_id'] = _dict.get('data_mart_id')
else:
raise ValueError('Required property \'data_mart_id\' not present in DataSetObject JSON')
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in DataSetObject JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in DataSetObject JSON')
if 'target' in _dict:
args['target'] = Target.from_dict(_dict.get('target'))
else:
raise ValueError('Required property \'target\' not present in DataSetObject JSON')
if 'schema_update_mode' in _dict:
args['schema_update_mode'] = _dict.get('schema_update_mode')
if 'data_schema' in _dict:
args['data_schema'] = SparkStruct.from_dict(_dict.get('data_schema'))
else:
raise ValueError('Required property \'data_schema\' not present in DataSetObject JSON')
if 'location' in _dict:
args['location'] = LocationTableName.from_dict(_dict.get('location'))
if 'managed_by' in _dict:
args['managed_by'] = _dict.get('managed_by')
if 'status' in _dict:
args['status'] = Status.from_dict(_dict.get('status'))
else:
raise ValueError('Required property \'status\' not present in DataSetObject JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSetObject object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'data_mart_id') and self.data_mart_id is not None:
_dict['data_mart_id'] = self.data_mart_id
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'target') and self.target is not None:
_dict['target'] = self.target.to_dict()
if hasattr(self, 'schema_update_mode') and self.schema_update_mode is not None:
_dict['schema_update_mode'] = self.schema_update_mode
if hasattr(self, 'data_schema') and self.data_schema is not None:
_dict['data_schema'] = self.data_schema.to_dict()
if hasattr(self, 'location') and self.location is not None:
_dict['location'] = self.location.to_dict()
if hasattr(self, 'managed_by') and self.managed_by is not None:
_dict['managed_by'] = self.managed_by
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSetObject object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSetObject') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSetObject') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
type of a data set.
"""
MANUAL_LABELING = 'manual_labeling'
PAYLOAD_LOGGING = 'payload_logging'
FEEDBACK = 'feedback'
BUSINESS_PAYLOAD = 'business_payload'
EXPLANATIONS = 'explanations'
EXPLANATIONS_WHATIF = 'explanations_whatif'
TRAINING = 'training'
PAYLOAD_LOGGING_ERROR = 'payload_logging_error'
MODEL_HEALTH = 'model_health'
DRIFT_STATS = 'drift_stats'
DRIFT_INTERVALS = 'drift_intervals'
DRIFT_INSIGHTS = 'drift_insights'
GEN_AI_QUALITY_METRICS = 'gen_ai_quality_metrics'
GEN_AI_SECURITY_METRICS = 'gen_ai_security_metrics'
DRIFT_SCORES = 'drift_scores'
AIDC_FEEDBACK = 'aidc_feedback'
CUSTOM = 'custom'
NODES_INFO = 'nodes_info'
EDGES_INFO = 'edges_info'
AGENTIC_APP_IO = 'agentic_app_io'
NODES_IO = 'nodes_io'
AGENTIC_APP_METRICS = 'agentic_app_metrics'
SPANS = 'spans'
class SchemaUpdateModeEnum(str, Enum):
"""
schema_update_mode.
"""
NONE = 'none'
AUTO = 'auto'
class DataSetRecords():
"""
DataSetRecords.
:attr List[DataSetRecordsDataSetRecordsItem] data_set_records:
"""
def __init__(self,
data_set_records: List['DataSetRecordsDataSetRecordsItem']) -> None:
"""
Initialize a DataSetRecords object.
:param List[DataSetRecordsDataSetRecordsItem] data_set_records:
"""
self.data_set_records = data_set_records
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSetRecords':
"""Initialize a DataSetRecords object from a json dictionary."""
args = {}
if 'data_set_records' in _dict:
args['data_set_records'] = [DataSetRecordsDataSetRecordsItem.from_dict(x) for x in _dict.get('data_set_records')]
else:
raise ValueError('Required property \'data_set_records\' not present in DataSetRecords JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSetRecords object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'data_set_records') and self.data_set_records is not None:
_dict['data_set_records'] = [x.to_dict() for x in self.data_set_records]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSetRecords object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSetRecords') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSetRecords') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSetRecordsDataSetRecordsItem():
"""
DataSetRecordsDataSetRecordsItem.
:attr DataSetRecordsDataSetRecordsItemDataSet data_set:
:attr DataSetRecordsDataSetRecordsItemRecords records:
"""
def __init__(self,
data_set: 'DataSetRecordsDataSetRecordsItemDataSet',
records: 'DataSetRecordsDataSetRecordsItemRecords') -> None:
"""
Initialize a DataSetRecordsDataSetRecordsItem object.
:param DataSetRecordsDataSetRecordsItemDataSet data_set:
:param DataSetRecordsDataSetRecordsItemRecords records:
"""
self.data_set = data_set
self.records = records
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSetRecordsDataSetRecordsItem':
"""Initialize a DataSetRecordsDataSetRecordsItem object from a json dictionary."""
args = {}
if 'data_set' in _dict:
args['data_set'] = DataSetRecordsDataSetRecordsItemDataSet.from_dict(_dict.get('data_set'))
else:
raise ValueError('Required property \'data_set\' not present in DataSetRecordsDataSetRecordsItem JSON')
if 'records' in _dict:
args['records'] = DataSetRecordsDataSetRecordsItemRecords.from_dict(_dict.get('records'))
else:
raise ValueError('Required property \'records\' not present in DataSetRecordsDataSetRecordsItem JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSetRecordsDataSetRecordsItem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'data_set') and self.data_set is not None:
_dict['data_set'] = self.data_set.to_dict()
if hasattr(self, 'records') and self.records is not None:
_dict['records'] = self.records.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSetRecordsDataSetRecordsItem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSetRecordsDataSetRecordsItem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSetRecordsDataSetRecordsItem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSetRecordsDataSetRecordsItemDataSet():
"""
DataSetRecordsDataSetRecordsItemDataSet.
:attr str data_mart_id:
:attr str type: type of a data set.
:attr Target target:
:attr SparkStruct data_schema:
"""
def __init__(self,
data_mart_id: str,
type: str,
target: 'Target',
data_schema: 'SparkStruct') -> None:
"""
Initialize a DataSetRecordsDataSetRecordsItemDataSet object.
:param str data_mart_id:
:param str type: type of a data set.
:param Target target:
:param SparkStruct data_schema:
"""
self.data_mart_id = data_mart_id
self.type = type
self.target = target
self.data_schema = data_schema
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSetRecordsDataSetRecordsItemDataSet':
"""Initialize a DataSetRecordsDataSetRecordsItemDataSet object from a json dictionary."""
args = {}
if 'data_mart_id' in _dict:
args['data_mart_id'] = _dict.get('data_mart_id')
else:
raise ValueError('Required property \'data_mart_id\' not present in DataSetRecordsDataSetRecordsItemDataSet JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in DataSetRecordsDataSetRecordsItemDataSet JSON')
if 'target' in _dict:
args['target'] = Target.from_dict(_dict.get('target'))
else:
raise ValueError('Required property \'target\' not present in DataSetRecordsDataSetRecordsItemDataSet JSON')
if 'data_schema' in _dict:
args['data_schema'] = SparkStruct.from_dict(_dict.get('data_schema'))
else:
raise ValueError('Required property \'data_schema\' not present in DataSetRecordsDataSetRecordsItemDataSet JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSetRecordsDataSetRecordsItemDataSet object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'data_mart_id') and self.data_mart_id is not None:
_dict['data_mart_id'] = self.data_mart_id
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'target') and self.target is not None:
_dict['target'] = self.target.to_dict()
if hasattr(self, 'data_schema') and self.data_schema is not None:
_dict['data_schema'] = self.data_schema.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSetRecordsDataSetRecordsItemDataSet object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSetRecordsDataSetRecordsItemDataSet') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSetRecordsDataSetRecordsItemDataSet') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
type of a data set.
"""
MANUAL_LABELING = 'manual_labeling'
PAYLOAD_LOGGING = 'payload_logging'
FEEDBACK = 'feedback'
BUSINESS_PAYLOAD = 'business_payload'
EXPLANATIONS = 'explanations'
EXPLANATIONS_WHATIF = 'explanations_whatif'
TRAINING = 'training'
PAYLOAD_LOGGING_ERROR = 'payload_logging_error'
MODEL_HEALTH = 'model_health'
DRIFT_STATS = 'drift_stats'
DRIFT_INTERVALS = 'drift_intervals'
DRIFT_INSIGHTS = 'drift_insights'
GEN_AI_QUALITY_METRICS = 'gen_ai_quality_metrics'
GEN_AI_SECURITY_METRICS = 'gen_ai_security_metrics'
DRIFT_SCORES = 'drift_scores'
AIDC_FEEDBACK = 'aidc_feedback'
CUSTOM = 'custom'
NODES_INFO = 'nodes_info'
EDGES_INFO = 'edges_info'
AGENTIC_APP_IO = 'agentic_app_io'
NODES_IO = 'nodes_io'
AGENTIC_APP_METRICS = 'agentic_app_metrics'
SPANS = 'spans'
class DataSetRecordsDataSetRecordsItemRecords():
"""
DataSetRecordsDataSetRecordsItemRecords.
:attr Metadata metadata:
:attr DataSetRecordsDataSetRecordsItemRecordsEntity entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'DataSetRecordsDataSetRecordsItemRecordsEntity') -> None:
"""
Initialize a DataSetRecordsDataSetRecordsItemRecords object.
:param Metadata metadata:
:param DataSetRecordsDataSetRecordsItemRecordsEntity entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSetRecordsDataSetRecordsItemRecords':
"""Initialize a DataSetRecordsDataSetRecordsItemRecords object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in DataSetRecordsDataSetRecordsItemRecords JSON')
if 'entity' in _dict:
args['entity'] = DataSetRecordsDataSetRecordsItemRecordsEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in DataSetRecordsDataSetRecordsItemRecords JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSetRecordsDataSetRecordsItemRecords object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSetRecordsDataSetRecordsItemRecords object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSetRecordsDataSetRecordsItemRecords') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSetRecordsDataSetRecordsItemRecords') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSetRecordsDataSetRecordsItemRecordsEntity():
"""
DataSetRecordsDataSetRecordsItemRecordsEntity.
:attr object values: Fields and values of the entity matches JSON object's
fields and values.
"""
def __init__(self,
values: object) -> None:
"""
Initialize a DataSetRecordsDataSetRecordsItemRecordsEntity object.
:param object values: Fields and values of the entity matches JSON object's
fields and values.
"""
self.values = values
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSetRecordsDataSetRecordsItemRecordsEntity':
"""Initialize a DataSetRecordsDataSetRecordsItemRecordsEntity object from a json dictionary."""
args = {}
if 'values' in _dict:
args['values'] = _dict.get('values')
else:
raise ValueError('Required property \'values\' not present in DataSetRecordsDataSetRecordsItemRecordsEntity JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSetRecordsDataSetRecordsItemRecordsEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = self.values
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSetRecordsDataSetRecordsItemRecordsEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSetRecordsDataSetRecordsItemRecordsEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSetRecordsDataSetRecordsItemRecordsEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSetResponse():
"""
DataSetResponse.
:attr Metadata metadata:
:attr DataSetObject entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'DataSetObject') -> None:
"""
Initialize a DataSetResponse object.
:param Metadata metadata:
:param DataSetObject entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSetResponse':
"""Initialize a DataSetResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in DataSetResponse JSON')
if 'entity' in _dict:
args['entity'] = DataSetObject.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in DataSetResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSetResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSetResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSetResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSetResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSetResponseCollection():
"""
DataSetResponseCollection.
:attr List[DataSetResponse] data_sets:
"""
def __init__(self,
data_sets: List['DataSetResponse']) -> None:
"""
Initialize a DataSetResponseCollection object.
:param List[DataSetResponse] data_sets:
"""
self.data_sets = data_sets
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSetResponseCollection':
"""Initialize a DataSetResponseCollection object from a json dictionary."""
args = {}
if 'data_sets' in _dict:
args['data_sets'] = [DataSetResponse.from_dict(x) for x in _dict.get('data_sets')]
else:
raise ValueError('Required property \'data_sets\' not present in DataSetResponseCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSetResponseCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'data_sets') and self.data_sets is not None:
_dict['data_sets'] = [x.to_dict() for x in self.data_sets]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSetResponseCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSetResponseCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSetResponseCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSource():
"""
DataSource.
:attr str type: (optional) Type of data source. e.g. payload, feedback,
drift,explain.
:attr DataSourceConnection connection: (optional)
:attr str database_name: (optional) database name.
:attr str schema_name: (optional) schema name.
:attr str table_name: (optional) table name.
:attr DataSourceEndpoint endpoint: (optional)
:attr object parameters: (optional) Additional parameters.
:attr bool auto_create: (optional) Set true for automatically creating the
table.
:attr DataSourceStatus status: (optional)
"""
def __init__(self,
*,
type: str = None,
connection: 'DataSourceConnection' = None,
database_name: str = None,
schema_name: str = None,
table_name: str = None,
endpoint: 'DataSourceEndpoint' = None,
parameters: object = None,
auto_create: bool = None,
status: 'DataSourceStatus' = None) -> None:
"""
Initialize a DataSource object.
:param str type: (optional) Type of data source. e.g. payload, feedback,
drift,explain.
:param DataSourceConnection connection: (optional)
:param str database_name: (optional) database name.
:param str schema_name: (optional) schema name.
:param str table_name: (optional) table name.
:param DataSourceEndpoint endpoint: (optional)
:param object parameters: (optional) Additional parameters.
:param bool auto_create: (optional) Set true for automatically creating the
table.
:param DataSourceStatus status: (optional)
"""
self.type = type
self.connection = connection
self.database_name = database_name
self.schema_name = schema_name
self.table_name = table_name
self.endpoint = endpoint
self.parameters = parameters
self.auto_create = auto_create
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSource':
"""Initialize a DataSource object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
if 'connection' in _dict:
args['connection'] = DataSourceConnection.from_dict(_dict.get('connection'))
if 'database_name' in _dict:
args['database_name'] = _dict.get('database_name')
if 'schema_name' in _dict:
args['schema_name'] = _dict.get('schema_name')
if 'table_name' in _dict:
args['table_name'] = _dict.get('table_name')
if 'endpoint' in _dict:
args['endpoint'] = DataSourceEndpoint.from_dict(_dict.get('endpoint'))
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
if 'auto_create' in _dict:
args['auto_create'] = _dict.get('auto_create')
if 'status' in _dict:
args['status'] = DataSourceStatus.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSource object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'connection') and self.connection is not None:
_dict['connection'] = self.connection.to_dict()
if hasattr(self, 'database_name') and self.database_name is not None:
_dict['database_name'] = self.database_name
if hasattr(self, 'schema_name') and self.schema_name is not None:
_dict['schema_name'] = self.schema_name
if hasattr(self, 'table_name') and self.table_name is not None:
_dict['table_name'] = self.table_name
if hasattr(self, 'endpoint') and self.endpoint is not None:
_dict['endpoint'] = self.endpoint.to_dict()
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
if hasattr(self, 'auto_create') and self.auto_create is not None:
_dict['auto_create'] = self.auto_create
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSource object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSource') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSource') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSourceConnection():
"""
DataSourceConnection.
:attr str type: (optional) Type of integrated system, e.g. hive, jdbc.
:attr str integrated_system_id: (optional) id of the integrated system.
:attr object parameters: (optional) Additional parameters.
"""
def __init__(self,
*,
type: str = None,
integrated_system_id: str = None,
parameters: object = None) -> None:
"""
Initialize a DataSourceConnection object.
:param str type: (optional) Type of integrated system, e.g. hive, jdbc.
:param str integrated_system_id: (optional) id of the integrated system.
:param object parameters: (optional) Additional parameters.
"""
self.type = type
self.integrated_system_id = integrated_system_id
self.parameters = parameters
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSourceConnection':
"""Initialize a DataSourceConnection object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
if 'integrated_system_id' in _dict:
args['integrated_system_id'] = _dict.get('integrated_system_id')
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSourceConnection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'integrated_system_id') and self.integrated_system_id is not None:
_dict['integrated_system_id'] = self.integrated_system_id
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSourceConnection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSourceConnection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSourceConnection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSourceEndpoint():
"""
DataSourceEndpoint.
:attr str url: Url of the endpoint.
:attr object credentials: (optional) Credentials for the endpoint.
"""
def __init__(self,
url: str,
*,
credentials: object = None) -> None:
"""
Initialize a DataSourceEndpoint object.
:param str url: Url of the endpoint.
:param object credentials: (optional) Credentials for the endpoint.
"""
self.url = url
self.credentials = credentials
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSourceEndpoint':
"""Initialize a DataSourceEndpoint object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
else:
raise ValueError('Required property \'url\' not present in DataSourceEndpoint JSON')
if 'credentials' in _dict:
args['credentials'] = _dict.get('credentials')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSourceEndpoint object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'credentials') and self.credentials is not None:
_dict['credentials'] = self.credentials
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSourceEndpoint object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSourceEndpoint') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSourceEndpoint') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DataSourceStatus():
"""
DataSourceStatus.
:attr str state:
:attr GenericErrorResponse failure: (optional)
"""
def __init__(self,
state: str,
*,
failure: 'GenericErrorResponse' = None) -> None:
"""
Initialize a DataSourceStatus object.
:param str state:
:param GenericErrorResponse failure: (optional)
"""
self.state = state
self.failure = failure
@classmethod
def from_dict(cls, _dict: Dict) -> 'DataSourceStatus':
"""Initialize a DataSourceStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
else:
raise ValueError('Required property \'state\' not present in DataSourceStatus JSON')
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DataSourceStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DataSourceStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DataSourceStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DataSourceStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
state.
"""
NEW = 'new'
PREPARING = 'preparing'
ACTIVE = 'active'
ERROR = 'error'
[docs]
class DatabaseConfiguration():
"""
Database configuration ignored if internal database is requested (`internal_database`
is `true`).
:attr str database_type:
:attr str instance_id: (optional)
:attr str name: (optional)
:attr SecretCleaned credentials:
:attr LocationSchemaName location: (optional)
"""
def __init__(self,
database_type: str,
credentials: 'SecretCleaned',
*,
instance_id: str = None,
name: str = None,
location: 'LocationSchemaName' = None) -> None:
"""
Initialize a DatabaseConfiguration object.
:param str database_type:
:param SecretCleaned credentials:
:param str instance_id: (optional)
:param str name: (optional)
:param LocationSchemaName location: (optional)
"""
self.database_type = database_type
self.instance_id = instance_id
self.name = name
self.credentials = credentials
self.location = location
@classmethod
def from_dict(cls, _dict: Dict) -> 'DatabaseConfiguration':
"""Initialize a DatabaseConfiguration object from a json dictionary."""
args = {}
if 'database_type' in _dict:
args['database_type'] = _dict.get('database_type')
else:
raise ValueError('Required property \'database_type\' not present in DatabaseConfiguration JSON')
if 'instance_id' in _dict:
args['instance_id'] = _dict.get('instance_id')
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'credentials' in _dict:
args['credentials'] = SecretCleaned.from_dict(_dict.get('credentials'))
else:
raise ValueError('Required property \'credentials\' not present in DatabaseConfiguration JSON')
if 'location' in _dict:
args['location'] = LocationSchemaName.from_dict(_dict.get('location'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DatabaseConfiguration object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'database_type') and self.database_type is not None:
_dict['database_type'] = self.database_type
if hasattr(self, 'instance_id') and self.instance_id is not None:
_dict['instance_id'] = self.instance_id
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'credentials') and self.credentials is not None:
_dict['credentials'] = self.credentials.to_dict()
if hasattr(self, 'location') and self.location is not None:
_dict['location'] = self.location.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DatabaseConfiguration object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DatabaseConfiguration') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DatabaseConfiguration') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class DatabaseTypeEnum(str, Enum):
"""
database_type.
"""
POSTGRESQL = 'postgresql'
DB2 = 'db2'
class DatabaseConfigurationRequest():
"""
Database configuration ignored if internal database is requested (`internal_database`
is `true`).
:attr str database_type:
:attr str name: (optional)
:attr str instance_id: (optional)
:attr PrimaryStorageCredentials credentials:
:attr LocationSchemaName location: (optional)
"""
def __init__(self,
database_type: str,
credentials: 'PrimaryStorageCredentials',
*,
name: str = None,
instance_id: str = None,
location: 'LocationSchemaName' = None) -> None:
"""
Initialize a DatabaseConfigurationRequest object.
:param str database_type:
:param PrimaryStorageCredentials credentials:
:param str name: (optional)
:param str instance_id: (optional)
:param LocationSchemaName location: (optional)
"""
self.database_type = database_type
self.name = name
self.instance_id = instance_id
self.credentials = credentials
self.location = location
@classmethod
def from_dict(cls, _dict: Dict) -> 'DatabaseConfigurationRequest':
"""Initialize a DatabaseConfigurationRequest object from a json dictionary."""
args = {}
if 'database_type' in _dict:
args['database_type'] = _dict.get('database_type')
else:
raise ValueError('Required property \'database_type\' not present in DatabaseConfigurationRequest JSON')
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'instance_id' in _dict:
args['instance_id'] = _dict.get('instance_id')
if 'credentials' in _dict:
args['credentials'] = _dict.get('credentials')
else:
raise ValueError('Required property \'credentials\' not present in DatabaseConfigurationRequest JSON')
if 'location' in _dict:
args['location'] = LocationSchemaName.from_dict(_dict.get('location'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DatabaseConfigurationRequest object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'database_type') and self.database_type is not None:
_dict['database_type'] = self.database_type
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'instance_id') and self.instance_id is not None:
_dict['instance_id'] = self.instance_id
if hasattr(self, 'credentials') and self.credentials is not None:
if isinstance(self.credentials, dict):
_dict['credentials'] = self.credentials
else:
_dict['credentials'] = self.credentials.to_dict()
if hasattr(self, 'location') and self.location is not None:
_dict['location'] = self.location.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DatabaseConfigurationRequest object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DatabaseConfigurationRequest') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DatabaseConfigurationRequest') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DatabaseTypeEnum(str, Enum):
"""
database_type.
"""
POSTGRESQL = 'postgresql'
DB2 = 'db2'
class Detector():
"""
A detector (either built-in or custom).
:attr str name: Name of the detector.
:attr str description: (optional) Description of what the detector does.
:attr bool is_text: (optional) Whether the detector accepts text properties.
:attr bool is_number: (optional) Whether the detector accepts number properties.
:attr bool is_multi_line: (optional) Whether the detector accepts multi-line
text.
:attr float min_number_value: (optional) Minimum value for number properties.
:attr float max_number_value: (optional) Maximum value for number properties.
:attr str property_text_name: (optional) Name of the text property field.
:attr str property_number_name: (optional) Name of the number property field.
:attr str id: (optional) Unique identifier (only for custom detectors).
:attr str inventory_id: (optional) CAMS inventory ID (only for custom
detectors).
:attr str url: (optional) URL endpoint (only for custom detectors).
:attr List[str] actions: List of supported actions (only for custom detectors).
:attr dict metadata: (optional) Additional metadata (only for custom detectors).
:attr List[DetectorProperty] detector_properties: Configurable properties for
the detector.
:attr List[DetectorParameter] parameters: Parameters that can be passed to the
detector (only for custom detectors).
:attr datetime created_at: (optional) Timestamp when the detector was created.
:attr datetime modified_at: (optional) Timestamp when the detector was last
modified.
:attr DetectorStatus status: (optional) Status information for the detector.
"""
def __init__(self,
name: str,
actions: List[str],
detector_properties: List['DetectorProperty'],
parameters: List['DetectorParameter'],
*,
description: str = None,
is_text: bool = None,
is_number: bool = None,
is_multi_line: bool = None,
min_number_value: float = None,
max_number_value: float = None,
property_text_name: str = None,
property_number_name: str = None,
id: str = None,
inventory_id: str = None,
url: str = None,
metadata: dict = None,
created_at: datetime = None,
modified_at: datetime = None,
status: 'DetectorStatus' = None) -> None:
"""
Initialize a Detector object.
:param str name: Name of the detector.
:param List[str] actions: List of supported actions (only for custom
detectors).
:param List[DetectorProperty] detector_properties: Configurable properties
for the detector.
:param List[DetectorParameter] parameters: Parameters that can be passed to
the detector (only for custom detectors).
:param str description: (optional) Description of what the detector does.
:param bool is_text: (optional) Whether the detector accepts text
properties.
:param bool is_number: (optional) Whether the detector accepts number
properties.
:param bool is_multi_line: (optional) Whether the detector accepts
multi-line text.
:param float min_number_value: (optional) Minimum value for number
properties.
:param float max_number_value: (optional) Maximum value for number
properties.
:param str property_text_name: (optional) Name of the text property field.
:param str property_number_name: (optional) Name of the number property
field.
:param str id: (optional) Unique identifier (only for custom detectors).
:param str inventory_id: (optional) CAMS inventory ID (only for custom
detectors).
:param str url: (optional) URL endpoint (only for custom detectors).
:param dict metadata: (optional) Additional metadata (only for custom
detectors).
:param datetime created_at: (optional) Timestamp when the detector was
created.
:param datetime modified_at: (optional) Timestamp when the detector was
last modified.
:param DetectorStatus status: (optional) Status information for the
detector.
"""
self.name = name
self.description = description
self.is_text = is_text
self.is_number = is_number
self.is_multi_line = is_multi_line
self.min_number_value = min_number_value
self.max_number_value = max_number_value
self.property_text_name = property_text_name
self.property_number_name = property_number_name
self.id = id
self.inventory_id = inventory_id
self.url = url
self.actions = actions
self.metadata = metadata
self.detector_properties = detector_properties
self.parameters = parameters
self.created_at = created_at
self.modified_at = modified_at
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'Detector':
"""Initialize a Detector object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in Detector JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'is_text' in _dict:
args['is_text'] = _dict.get('is_text')
if 'is_number' in _dict:
args['is_number'] = _dict.get('is_number')
if 'is_multi_line' in _dict:
args['is_multi_line'] = _dict.get('is_multi_line')
if 'min_number_value' in _dict:
args['min_number_value'] = _dict.get('min_number_value')
if 'max_number_value' in _dict:
args['max_number_value'] = _dict.get('max_number_value')
if 'property_text_name' in _dict:
args['property_text_name'] = _dict.get('property_text_name')
if 'property_number_name' in _dict:
args['property_number_name'] = _dict.get('property_number_name')
if 'id' in _dict:
args['id'] = _dict.get('id')
if 'inventory_id' in _dict:
args['inventory_id'] = _dict.get('inventory_id')
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'actions' in _dict:
args['actions'] = _dict.get('actions')
else:
raise ValueError('Required property \'actions\' not present in Detector JSON')
if 'metadata' in _dict:
args['metadata'] = _dict.get('metadata')
if 'detector_properties' in _dict:
args['detector_properties'] = [DetectorProperty.from_dict(x) for x in _dict.get('detector_properties')]
else:
raise ValueError('Required property \'detector_properties\' not present in Detector JSON')
if 'parameters' in _dict:
args['parameters'] = [DetectorParameter.from_dict(x) for x in _dict.get('parameters')]
else:
raise ValueError('Required property \'parameters\' not present in Detector JSON')
if 'created_at' in _dict:
args['created_at'] = string_to_datetime(_dict.get('created_at'))
if 'modified_at' in _dict:
args['modified_at'] = string_to_datetime(_dict.get('modified_at'))
if 'status' in _dict:
args['status'] = DetectorStatus.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Detector object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'is_text') and self.is_text is not None:
_dict['is_text'] = self.is_text
if hasattr(self, 'is_number') and self.is_number is not None:
_dict['is_number'] = self.is_number
if hasattr(self, 'is_multi_line') and self.is_multi_line is not None:
_dict['is_multi_line'] = self.is_multi_line
if hasattr(self, 'min_number_value') and self.min_number_value is not None:
_dict['min_number_value'] = self.min_number_value
if hasattr(self, 'max_number_value') and self.max_number_value is not None:
_dict['max_number_value'] = self.max_number_value
if hasattr(self, 'property_text_name') and self.property_text_name is not None:
_dict['property_text_name'] = self.property_text_name
if hasattr(self, 'property_number_name') and self.property_number_name is not None:
_dict['property_number_name'] = self.property_number_name
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'inventory_id') and self.inventory_id is not None:
_dict['inventory_id'] = self.inventory_id
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'actions') and self.actions is not None:
_dict['actions'] = self.actions
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata
if hasattr(self, 'detector_properties') and self.detector_properties is not None:
_dict['detector_properties'] = [x.to_dict() for x in self.detector_properties]
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = [x.to_dict() for x in self.parameters]
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = datetime_to_string(self.created_at)
if hasattr(self, 'modified_at') and self.modified_at is not None:
_dict['modified_at'] = datetime_to_string(self.modified_at)
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Detector object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Detector') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Detector') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DetectorParameter():
"""
A parameter that can be passed to a detector.
:attr str name: Name of the parameter.
:attr bool is_optional: (optional) Whether the parameter is optional.
"""
def __init__(self,
name: str,
*,
is_optional: bool = None) -> None:
"""
Initialize a DetectorParameter object.
:param str name: Name of the parameter.
:param bool is_optional: (optional) Whether the parameter is optional.
"""
self.name = name
self.is_optional = is_optional
@classmethod
def from_dict(cls, _dict: Dict) -> 'DetectorParameter':
"""Initialize a DetectorParameter object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in DetectorParameter JSON')
if 'is_optional' in _dict:
args['is_optional'] = _dict.get('is_optional')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DetectorParameter object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'is_optional') and self.is_optional is not None:
_dict['is_optional'] = self.is_optional
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DetectorParameter object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DetectorParameter') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DetectorParameter') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DetectorProperty():
"""
A configurable property for a detector.
:attr str name: Name of the property.
:attr str type: Data type of the property.
:attr float min: (optional) Minimum value (optional, for number type).
:attr float max: (optional) Maximum value (optional, for number type).
:attr DetectorPropertyDefaultValue default_value: (optional) Default value for
the property (optional, type depends on property type).
"""
def __init__(self,
name: str,
type: str,
*,
min: float = None,
max: float = None,
default_value: 'DetectorPropertyDefaultValue' = None) -> None:
"""
Initialize a DetectorProperty object.
:param str name: Name of the property.
:param str type: Data type of the property.
:param float min: (optional) Minimum value (optional, for number type).
:param float max: (optional) Maximum value (optional, for number type).
:param DetectorPropertyDefaultValue default_value: (optional) Default value
for the property (optional, type depends on property type).
"""
self.name = name
self.type = type
self.min = min
self.max = max
self.default_value = default_value
@classmethod
def from_dict(cls, _dict: Dict) -> 'DetectorProperty':
"""Initialize a DetectorProperty object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in DetectorProperty JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in DetectorProperty JSON')
if 'min' in _dict:
args['min'] = _dict.get('min')
if 'max' in _dict:
args['max'] = _dict.get('max')
if 'default_value' in _dict:
args['default_value'] = _dict.get('default_value')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DetectorProperty object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'min') and self.min is not None:
_dict['min'] = self.min
if hasattr(self, 'max') and self.max is not None:
_dict['max'] = self.max
if hasattr(self, 'default_value') and self.default_value is not None:
if isinstance(self.default_value, dict):
_dict['default_value'] = self.default_value
else:
_dict['default_value'] = self.default_value.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DetectorProperty object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DetectorProperty') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DetectorProperty') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
Data type of the property.
"""
NUMBER = 'number'
BOOL = 'bool'
TEXT = 'text'
class DetectorResponse():
"""
Response wrapper for detector operations.
:attr Detector entity: A detector (either built-in or custom).
:attr DetectorResponseMetadata metadata: Metadata about the response.
"""
def __init__(self,
entity: 'Detector',
metadata: 'DetectorResponseMetadata') -> None:
"""
Initialize a DetectorResponse object.
:param Detector entity: A detector (either built-in or custom).
:param DetectorResponseMetadata metadata: Metadata about the response.
"""
self.entity = entity
self.metadata = metadata
@classmethod
def from_dict(cls, _dict: Dict) -> 'DetectorResponse':
"""Initialize a DetectorResponse object from a json dictionary."""
args = {}
if 'entity' in _dict:
args['entity'] = Detector.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in DetectorResponse JSON')
if 'metadata' in _dict:
args['metadata'] = DetectorResponseMetadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in DetectorResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DetectorResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DetectorResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DetectorResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DetectorResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DetectorResponseMetadata():
"""
Metadata about the response.
:attr str id: (optional) ID of the detector.
:attr datetime created_at: (optional) Creation timestamp.
"""
def __init__(self,
*,
id: str = None,
created_at: datetime = None) -> None:
"""
Initialize a DetectorResponseMetadata object.
:param str id: (optional) ID of the detector.
:param datetime created_at: (optional) Creation timestamp.
"""
self.id = id
self.created_at = created_at
@classmethod
def from_dict(cls, _dict: Dict) -> 'DetectorResponseMetadata':
"""Initialize a DetectorResponseMetadata object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
if 'created_at' in _dict:
args['created_at'] = string_to_datetime(_dict.get('created_at'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DetectorResponseMetadata object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = datetime_to_string(self.created_at)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DetectorResponseMetadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DetectorResponseMetadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DetectorResponseMetadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DetectorStatus():
"""
Status information for the detector.
:attr str state: (optional) Current state of the detector.
"""
def __init__(self,
*,
state: str = None) -> None:
"""
Initialize a DetectorStatus object.
:param str state: (optional) Current state of the detector.
"""
self.state = state
@classmethod
def from_dict(cls, _dict: Dict) -> 'DetectorStatus':
"""Initialize a DetectorStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DetectorStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DetectorStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DetectorStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DetectorStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class EmbeddingsProvider():
"""
EmbeddingsProvider.
:attr str integrated_system_id: The ID (typically a UUID v4) which uniquely
identifies the resource.
"""
def __init__(self,
integrated_system_id: str) -> None:
"""
Initialize a EmbeddingsProvider object.
:param str integrated_system_id: The ID (typically a UUID v4) which
uniquely identifies the resource.
"""
self.integrated_system_id = integrated_system_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'EmbeddingsProvider':
"""Initialize a EmbeddingsProvider object from a json dictionary."""
args = {}
if 'integrated_system_id' in _dict:
args['integrated_system_id'] = _dict.get('integrated_system_id')
else:
raise ValueError('Required property \'integrated_system_id\' not present in EmbeddingsProvider JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a EmbeddingsProvider object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'integrated_system_id') and self.integrated_system_id is not None:
_dict['integrated_system_id'] = self.integrated_system_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this EmbeddingsProvider object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'EmbeddingsProvider') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'EmbeddingsProvider') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class EnforceResponse():
"""
Response wrapper for policy enforcement.
:attr EnforceResponseEntity entity: Entity containing the enforcement results.
:attr EnforceResponseMetadata metadata: Metadata about the enforcement.
"""
def __init__(self,
entity: 'EnforceResponseEntity',
metadata: 'EnforceResponseMetadata') -> None:
"""
Initialize a EnforceResponse object.
:param EnforceResponseEntity entity: Entity containing the enforcement
results.
:param EnforceResponseMetadata metadata: Metadata about the enforcement.
"""
self.entity = entity
self.metadata = metadata
@classmethod
def from_dict(cls, _dict: Dict) -> 'EnforceResponse':
"""Initialize a EnforceResponse object from a json dictionary."""
args = {}
if 'entity' in _dict:
args['entity'] = EnforceResponseEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in EnforceResponse JSON')
if 'metadata' in _dict:
args['metadata'] = EnforceResponseMetadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in EnforceResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a EnforceResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this EnforceResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'EnforceResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'EnforceResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class EnforceResponseEntity():
"""
Entity containing the enforcement results.
:attr str text: (optional) The processed text (may be modified if masking action
was applied).
:attr ExecutionStatus status: (optional) Detailed status information about the
execution.
"""
def __init__(self,
*,
text: str = None,
status: 'ExecutionStatus' = None) -> None:
"""
Initialize a EnforceResponseEntity object.
:param str text: (optional) The processed text (may be modified if masking
action was applied).
:param ExecutionStatus status: (optional) Detailed status information about
the execution.
"""
self.text = text
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'EnforceResponseEntity':
"""Initialize a EnforceResponseEntity object from a json dictionary."""
args = {}
if 'text' in _dict:
args['text'] = _dict.get('text')
if 'status' in _dict:
args['status'] = ExecutionStatus.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a EnforceResponseEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'text') and self.text is not None:
_dict['text'] = self.text
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this EnforceResponseEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'EnforceResponseEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'EnforceResponseEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class EnforceResponseMetadata():
"""
Metadata about the enforcement.
:attr str id: ID of the policy that was enforced.
"""
def __init__(self,
id: str) -> None:
"""
Initialize a EnforceResponseMetadata object.
:param str id: ID of the policy that was enforced.
"""
self.id = id
@classmethod
def from_dict(cls, _dict: Dict) -> 'EnforceResponseMetadata':
"""Initialize a EnforceResponseMetadata object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in EnforceResponseMetadata JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a EnforceResponseMetadata object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this EnforceResponseMetadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'EnforceResponseMetadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'EnforceResponseMetadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ExecutionStatus():
"""
Detailed status information about the execution.
:attr str overall: Overall execution status.
:attr ExecutionStatusSummary summary: Summary of detector execution results.
:attr ExecutionStatusDetails details: Detailed information about detector
execution.
"""
def __init__(self,
overall: str,
summary: 'ExecutionStatusSummary',
details: 'ExecutionStatusDetails') -> None:
"""
Initialize a ExecutionStatus object.
:param str overall: Overall execution status.
:param ExecutionStatusSummary summary: Summary of detector execution
results.
:param ExecutionStatusDetails details: Detailed information about detector
execution.
"""
self.overall = overall
self.summary = summary
self.details = details
@classmethod
def from_dict(cls, _dict: Dict) -> 'ExecutionStatus':
"""Initialize a ExecutionStatus object from a json dictionary."""
args = {}
if 'overall' in _dict:
args['overall'] = _dict.get('overall')
else:
raise ValueError('Required property \'overall\' not present in ExecutionStatus JSON')
if 'summary' in _dict:
args['summary'] = ExecutionStatusSummary.from_dict(_dict.get('summary'))
else:
raise ValueError('Required property \'summary\' not present in ExecutionStatus JSON')
if 'details' in _dict:
args['details'] = ExecutionStatusDetails.from_dict(_dict.get('details'))
else:
raise ValueError('Required property \'details\' not present in ExecutionStatus JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ExecutionStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'overall') and self.overall is not None:
_dict['overall'] = self.overall
if hasattr(self, 'summary') and self.summary is not None:
_dict['summary'] = self.summary.to_dict()
if hasattr(self, 'details') and self.details is not None:
_dict['details'] = self.details.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ExecutionStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ExecutionStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ExecutionStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ExecutionStatusDetails():
"""
Detailed information about detector execution.
:attr List[str] failed_detectors: List of detector names that failed.
:attr List[str] succeeded_with_retry: List of detector names that succeeded
after retry.
"""
def __init__(self,
failed_detectors: List[str],
succeeded_with_retry: List[str]) -> None:
"""
Initialize a ExecutionStatusDetails object.
:param List[str] failed_detectors: List of detector names that failed.
:param List[str] succeeded_with_retry: List of detector names that
succeeded after retry.
"""
self.failed_detectors = failed_detectors
self.succeeded_with_retry = succeeded_with_retry
@classmethod
def from_dict(cls, _dict: Dict) -> 'ExecutionStatusDetails':
"""Initialize a ExecutionStatusDetails object from a json dictionary."""
args = {}
if 'failed_detectors' in _dict:
args['failed_detectors'] = _dict.get('failed_detectors')
else:
raise ValueError('Required property \'failed_detectors\' not present in ExecutionStatusDetails JSON')
if 'succeeded_with_retry' in _dict:
args['succeeded_with_retry'] = _dict.get('succeeded_with_retry')
else:
raise ValueError('Required property \'succeeded_with_retry\' not present in ExecutionStatusDetails JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ExecutionStatusDetails object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'failed_detectors') and self.failed_detectors is not None:
_dict['failed_detectors'] = self.failed_detectors
if hasattr(self, 'succeeded_with_retry') and self.succeeded_with_retry is not None:
_dict['succeeded_with_retry'] = self.succeeded_with_retry
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ExecutionStatusDetails object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ExecutionStatusDetails') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ExecutionStatusDetails') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ExecutionStatusSummary():
"""
Summary of detector execution results.
:attr int total_detectors: Total number of detectors executed.
:attr int succeeded: Number of detectors that succeeded.
:attr int failed: Number of detectors that failed.
:attr int succeeded_without_retry: Number of detectors that succeeded on first
attempt.
:attr int succeeded_with_retry: Number of detectors that succeeded after retry.
"""
def __init__(self,
total_detectors: int,
succeeded: int,
failed: int,
succeeded_without_retry: int,
succeeded_with_retry: int) -> None:
"""
Initialize a ExecutionStatusSummary object.
:param int total_detectors: Total number of detectors executed.
:param int succeeded: Number of detectors that succeeded.
:param int failed: Number of detectors that failed.
:param int succeeded_without_retry: Number of detectors that succeeded on
first attempt.
:param int succeeded_with_retry: Number of detectors that succeeded after
retry.
"""
self.total_detectors = total_detectors
self.succeeded = succeeded
self.failed = failed
self.succeeded_without_retry = succeeded_without_retry
self.succeeded_with_retry = succeeded_with_retry
@classmethod
def from_dict(cls, _dict: Dict) -> 'ExecutionStatusSummary':
"""Initialize a ExecutionStatusSummary object from a json dictionary."""
args = {}
if 'total_detectors' in _dict:
args['total_detectors'] = _dict.get('total_detectors')
else:
raise ValueError('Required property \'total_detectors\' not present in ExecutionStatusSummary JSON')
if 'succeeded' in _dict:
args['succeeded'] = _dict.get('succeeded')
else:
raise ValueError('Required property \'succeeded\' not present in ExecutionStatusSummary JSON')
if 'failed' in _dict:
args['failed'] = _dict.get('failed')
else:
raise ValueError('Required property \'failed\' not present in ExecutionStatusSummary JSON')
if 'succeeded_without_retry' in _dict:
args['succeeded_without_retry'] = _dict.get('succeeded_without_retry')
else:
raise ValueError('Required property \'succeeded_without_retry\' not present in ExecutionStatusSummary JSON')
if 'succeeded_with_retry' in _dict:
args['succeeded_with_retry'] = _dict.get('succeeded_with_retry')
else:
raise ValueError('Required property \'succeeded_with_retry\' not present in ExecutionStatusSummary JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ExecutionStatusSummary object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'total_detectors') and self.total_detectors is not None:
_dict['total_detectors'] = self.total_detectors
if hasattr(self, 'succeeded') and self.succeeded is not None:
_dict['succeeded'] = self.succeeded
if hasattr(self, 'failed') and self.failed is not None:
_dict['failed'] = self.failed
if hasattr(self, 'succeeded_without_retry') and self.succeeded_without_retry is not None:
_dict['succeeded_without_retry'] = self.succeeded_without_retry
if hasattr(self, 'succeeded_with_retry') and self.succeeded_with_retry is not None:
_dict['succeeded_with_retry'] = self.succeeded_with_retry
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ExecutionStatusSummary object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ExecutionStatusSummary') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ExecutionStatusSummary') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ExplanationError():
"""
Explanation error details.
:attr str explanation_type: (optional) Type of explanation.
:attr ExplanationErrorError error: (optional) The error message details.
:attr str trace_id: (optional) ID used to track the explanation task via logs.
"""
def __init__(self,
*,
explanation_type: str = None,
error: 'ExplanationErrorError' = None,
trace_id: str = None) -> None:
"""
Initialize a ExplanationError object.
:param str explanation_type: (optional) Type of explanation.
:param ExplanationErrorError error: (optional) The error message details.
:param str trace_id: (optional) ID used to track the explanation task via
logs.
"""
self.explanation_type = explanation_type
self.error = error
self.trace_id = trace_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'ExplanationError':
"""Initialize a ExplanationError object from a json dictionary."""
args = {}
if 'explanation_type' in _dict:
args['explanation_type'] = _dict.get('explanation_type')
if 'error' in _dict:
args['error'] = ExplanationErrorError.from_dict(_dict.get('error'))
if 'trace_id' in _dict:
args['trace_id'] = _dict.get('trace_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ExplanationError object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'explanation_type') and self.explanation_type is not None:
_dict['explanation_type'] = self.explanation_type
if hasattr(self, 'error') and self.error is not None:
_dict['error'] = self.error.to_dict()
if hasattr(self, 'trace_id') and self.trace_id is not None:
_dict['trace_id'] = self.trace_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ExplanationError object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ExplanationError') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ExplanationError') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ExplanationErrorError():
"""
The error message details.
:attr str code: (optional) Error code.
:attr str message: (optional) Error message.
"""
def __init__(self,
*,
code: str = None,
message: str = None) -> None:
"""
Initialize a ExplanationErrorError object.
:param str code: (optional) Error code.
:param str message: (optional) Error message.
"""
self.code = code
self.message = message
@classmethod
def from_dict(cls, _dict: Dict) -> 'ExplanationErrorError':
"""Initialize a ExplanationErrorError object from a json dictionary."""
args = {}
if 'code' in _dict:
args['code'] = _dict.get('code')
if 'message' in _dict:
args['message'] = _dict.get('message')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ExplanationErrorError object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'code') and self.code is not None:
_dict['code'] = self.code
if hasattr(self, 'message') and self.message is not None:
_dict['message'] = self.message
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ExplanationErrorError object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ExplanationErrorError') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ExplanationErrorError') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ExplanationTaskResponseEntityAsset():
"""
Asset details in get explanation task response.
:attr str id: (optional) Identifier for the asset.
:attr str name: (optional) Name of the asset.
:attr str input_data_type: (optional) Type of the input data.
:attr str problem_type: (optional) Problem type.
:attr ExplanationTaskResponseEntityAssetDeployment deployment: (optional) Asset
deployment details.
"""
def __init__(self,
*,
id: str = None,
name: str = None,
input_data_type: str = None,
problem_type: str = None,
deployment: 'ExplanationTaskResponseEntityAssetDeployment' = None) -> None:
"""
Initialize a ExplanationTaskResponseEntityAsset object.
:param str id: (optional) Identifier for the asset.
:param str name: (optional) Name of the asset.
:param str input_data_type: (optional) Type of the input data.
:param str problem_type: (optional) Problem type.
:param ExplanationTaskResponseEntityAssetDeployment deployment: (optional)
Asset deployment details.
"""
self.id = id
self.name = name
self.input_data_type = input_data_type
self.problem_type = problem_type
self.deployment = deployment
@classmethod
def from_dict(cls, _dict: Dict) -> 'ExplanationTaskResponseEntityAsset':
"""Initialize a ExplanationTaskResponseEntityAsset object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'input_data_type' in _dict:
args['input_data_type'] = _dict.get('input_data_type')
if 'problem_type' in _dict:
args['problem_type'] = _dict.get('problem_type')
if 'deployment' in _dict:
args['deployment'] = ExplanationTaskResponseEntityAssetDeployment.from_dict(_dict.get('deployment'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ExplanationTaskResponseEntityAsset object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'input_data_type') and self.input_data_type is not None:
_dict['input_data_type'] = self.input_data_type
if hasattr(self, 'problem_type') and self.problem_type is not None:
_dict['problem_type'] = self.problem_type
if hasattr(self, 'deployment') and self.deployment is not None:
_dict['deployment'] = self.deployment.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ExplanationTaskResponseEntityAsset object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ExplanationTaskResponseEntityAsset') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ExplanationTaskResponseEntityAsset') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class InputDataTypeEnum(str, Enum):
"""
Type of the input data.
"""
STRUCTURED = 'structured'
UNSTRUCTURED_IMAGE = 'unstructured_image'
UNSTRUCTURED_TEXT = 'unstructured_text'
class ProblemTypeEnum(str, Enum):
"""
Problem type.
"""
BINARY = 'binary'
REGRESSION = 'regression'
MULTICLASS = 'multiclass'
QUESTION_ANSWERING = 'question_answering'
SUMMARIZATION = 'summarization'
RETRIEVAL_AUGMENTED_GENERATION = 'retrieval_augmented_generation'
CLASSIFICATION = 'classification'
GENERATION = 'generation'
CODE = 'code'
EXTRACTION = 'extraction'
class ExplanationTaskResponseEntityAssetDeployment():
"""
Asset deployment details.
:attr str id: (optional) Identifier for the asset deployment.
:attr str name: (optional) Name of the asset deployment.
"""
def __init__(self,
*,
id: str = None,
name: str = None) -> None:
"""
Initialize a ExplanationTaskResponseEntityAssetDeployment object.
:param str id: (optional) Identifier for the asset deployment.
:param str name: (optional) Name of the asset deployment.
"""
self.id = id
self.name = name
@classmethod
def from_dict(cls, _dict: Dict) -> 'ExplanationTaskResponseEntityAssetDeployment':
"""Initialize a ExplanationTaskResponseEntityAssetDeployment object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
if 'name' in _dict:
args['name'] = _dict.get('name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ExplanationTaskResponseEntityAssetDeployment object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ExplanationTaskResponseEntityAssetDeployment object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ExplanationTaskResponseEntityAssetDeployment') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ExplanationTaskResponseEntityAssetDeployment') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ExplanationTaskResponseEntityInputFeature():
"""
Input feature details in get explanation task response.
:attr str name: (optional) Name of the feature column.
:attr str value: (optional) Value of the feature column.
:attr str feature_type: (optional) Identifies the type of feature column.
"""
def __init__(self,
*,
name: str = None,
value: str = None,
feature_type: str = None) -> None:
"""
Initialize a ExplanationTaskResponseEntityInputFeature object.
:param str name: (optional) Name of the feature column.
:param str value: (optional) Value of the feature column.
:param str feature_type: (optional) Identifies the type of feature column.
"""
self.name = name
self.value = value
self.feature_type = feature_type
@classmethod
def from_dict(cls, _dict: Dict) -> 'ExplanationTaskResponseEntityInputFeature':
"""Initialize a ExplanationTaskResponseEntityInputFeature object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'value' in _dict:
args['value'] = _dict.get('value')
if 'feature_type' in _dict:
args['feature_type'] = _dict.get('feature_type')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ExplanationTaskResponseEntityInputFeature object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'feature_type') and self.feature_type is not None:
_dict['feature_type'] = self.feature_type
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ExplanationTaskResponseEntityInputFeature object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ExplanationTaskResponseEntityInputFeature') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ExplanationTaskResponseEntityInputFeature') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class FeatureTypeEnum(str, Enum):
"""
Identifies the type of feature column.
"""
NUMERICAL = 'numerical'
CATEGORICAL = 'categorical'
class FairnessMonitoringRemediation():
"""
FairnessMonitoringRemediation.
:attr List[str] fields: The fields of the model processed debias scoring.
:attr List[object] values: The values associated to the fields.
"""
def __init__(self,
fields: List[str],
values: List[object]) -> None:
"""
Initialize a FairnessMonitoringRemediation object.
:param List[str] fields: The fields of the model processed debias scoring.
:param List[object] values: The values associated to the fields.
"""
self.fields = fields
self.values = values
@classmethod
def from_dict(cls, _dict: Dict) -> 'FairnessMonitoringRemediation':
"""Initialize a FairnessMonitoringRemediation object from a json dictionary."""
args = {}
if 'fields' in _dict:
args['fields'] = _dict.get('fields')
else:
raise ValueError('Required property \'fields\' not present in FairnessMonitoringRemediation JSON')
if 'values' in _dict:
args['values'] = _dict.get('values')
else:
raise ValueError('Required property \'values\' not present in FairnessMonitoringRemediation JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a FairnessMonitoringRemediation object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'fields') and self.fields is not None:
_dict['fields'] = self.fields
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = self.values
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this FairnessMonitoringRemediation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'FairnessMonitoringRemediation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'FairnessMonitoringRemediation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class FileAssetMetadata():
"""
File data asset metadata.
:attr str project_id: (optional) Project id.
:attr str project_name: (optional) Project name.
:attr str asset_id: (optional) File data asset id.
:attr str asset_name: (optional) File data asset name.
:attr str asset_href: File data asset reference.
:attr FileTrainingDataReferenceOptions meta: (optional) additional options for
different types of training data references.
"""
def __init__(self,
asset_href: str,
*,
project_id: str = None,
project_name: str = None,
asset_id: str = None,
asset_name: str = None,
meta: 'FileTrainingDataReferenceOptions' = None) -> None:
"""
Initialize a FileAssetMetadata object.
:param str asset_href: File data asset reference.
:param str project_id: (optional) Project id.
:param str project_name: (optional) Project name.
:param str asset_id: (optional) File data asset id.
:param str asset_name: (optional) File data asset name.
:param FileTrainingDataReferenceOptions meta: (optional) additional options
for different types of training data references.
"""
self.project_id = project_id
self.project_name = project_name
self.asset_id = asset_id
self.asset_name = asset_name
self.asset_href = asset_href
self.meta = meta
@classmethod
def from_dict(cls, _dict: Dict) -> 'FileAssetMetadata':
"""Initialize a FileAssetMetadata object from a json dictionary."""
args = {}
if 'project_id' in _dict:
args['project_id'] = _dict.get('project_id')
if 'project_name' in _dict:
args['project_name'] = _dict.get('project_name')
if 'asset_id' in _dict:
args['asset_id'] = _dict.get('asset_id')
if 'asset_name' in _dict:
args['asset_name'] = _dict.get('asset_name')
if 'asset_href' in _dict:
args['asset_href'] = _dict.get('asset_href')
else:
raise ValueError('Required property \'asset_href\' not present in FileAssetMetadata JSON')
if 'meta' in _dict:
args['meta'] = FileTrainingDataReferenceOptions.from_dict(_dict.get('meta'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a FileAssetMetadata object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'project_id') and self.project_id is not None:
_dict['project_id'] = self.project_id
if hasattr(self, 'project_name') and self.project_name is not None:
_dict['project_name'] = self.project_name
if hasattr(self, 'asset_id') and self.asset_id is not None:
_dict['asset_id'] = self.asset_id
if hasattr(self, 'asset_name') and self.asset_name is not None:
_dict['asset_name'] = self.asset_name
if hasattr(self, 'asset_href') and self.asset_href is not None:
_dict['asset_href'] = self.asset_href
if hasattr(self, 'meta') and self.meta is not None:
_dict['meta'] = self.meta.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this FileAssetMetadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'FileAssetMetadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'FileAssetMetadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class FileTrainingDataReferenceOptions():
"""
additional options for different types of training data references.
:attr str file_name: (optional) file name.
:attr str file_format: (optional) File format.
:attr bool first_line_is_header: (optional) if not provided service will attempt
to automatically detect header in the first line (for data provided as csv).
:attr str delimiter: (optional) delimiter character for data provided as csv.
:attr float csv_max_line_length: (optional) maximum length of single line in
bytes (default 10000000).
:attr str on_error: (optional) Expected behaviour on error while reading a csv
file. Default behaviour is "stop".
"""
def __init__(self,
*,
file_name: str = None,
file_format: str = None,
first_line_is_header: bool = None,
delimiter: str = None,
csv_max_line_length: float = None,
on_error: str = None) -> None:
"""
Initialize a FileTrainingDataReferenceOptions object.
:param str file_name: (optional) file name.
:param str file_format: (optional) File format.
:param bool first_line_is_header: (optional) if not provided service will
attempt to automatically detect header in the first line (for data provided
as csv).
:param str delimiter: (optional) delimiter character for data provided as
csv.
:param float csv_max_line_length: (optional) maximum length of single line
in bytes (default 10000000).
:param str on_error: (optional) Expected behaviour on error while reading a
csv file. Default behaviour is "stop".
"""
self.file_name = file_name
self.file_format = file_format
self.first_line_is_header = first_line_is_header
self.delimiter = delimiter
self.csv_max_line_length = csv_max_line_length
self.on_error = on_error
@classmethod
def from_dict(cls, _dict: Dict) -> 'FileTrainingDataReferenceOptions':
"""Initialize a FileTrainingDataReferenceOptions object from a json dictionary."""
args = {}
if 'file_name' in _dict:
args['file_name'] = _dict.get('file_name')
if 'file_format' in _dict:
args['file_format'] = _dict.get('file_format')
if 'first_line_is_header' in _dict:
args['first_line_is_header'] = _dict.get('first_line_is_header')
if 'delimiter' in _dict:
args['delimiter'] = _dict.get('delimiter')
if 'csv_max_line_length' in _dict:
args['csv_max_line_length'] = _dict.get('csv_max_line_length')
if 'on_error' in _dict:
args['on_error'] = _dict.get('on_error')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a FileTrainingDataReferenceOptions object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'file_name') and self.file_name is not None:
_dict['file_name'] = self.file_name
if hasattr(self, 'file_format') and self.file_format is not None:
_dict['file_format'] = self.file_format
if hasattr(self, 'first_line_is_header') and self.first_line_is_header is not None:
_dict['first_line_is_header'] = self.first_line_is_header
if hasattr(self, 'delimiter') and self.delimiter is not None:
_dict['delimiter'] = self.delimiter
if hasattr(self, 'csv_max_line_length') and self.csv_max_line_length is not None:
_dict['csv_max_line_length'] = self.csv_max_line_length
if hasattr(self, 'on_error') and self.on_error is not None:
_dict['on_error'] = self.on_error
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this FileTrainingDataReferenceOptions object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'FileTrainingDataReferenceOptions') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'FileTrainingDataReferenceOptions') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class OnErrorEnum(str, Enum):
"""
Expected behaviour on error while reading a csv file. Default behaviour is "stop".
"""
STOP = 'stop'
CONTINUE = 'continue'
class GenAIAppAgentProperties():
"""
manages parameters to represents agentic ai characteristics.
:attr str framework: compossing agentic ai internally.
:attr str architecture: representing an internal architecture for agentc ai.
"""
def __init__(self,
framework: str,
architecture: str) -> None:
"""
Initialize a GenAIAppAgentProperties object.
:param str framework: compossing agentic ai internally.
:param str architecture: representing an internal architecture for agentc
ai.
"""
self.framework = framework
self.architecture = architecture
@classmethod
def from_dict(cls, _dict: Dict) -> 'GenAIAppAgentProperties':
"""Initialize a GenAIAppAgentProperties object from a json dictionary."""
args = {}
if 'framework' in _dict:
args['framework'] = _dict.get('framework')
else:
raise ValueError('Required property \'framework\' not present in GenAIAppAgentProperties JSON')
if 'architecture' in _dict:
args['architecture'] = _dict.get('architecture')
else:
raise ValueError('Required property \'architecture\' not present in GenAIAppAgentProperties JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GenAIAppAgentProperties object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'framework') and self.framework is not None:
_dict['framework'] = self.framework
if hasattr(self, 'architecture') and self.architecture is not None:
_dict['architecture'] = self.architecture
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GenAIAppAgentProperties object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GenAIAppAgentProperties') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GenAIAppAgentProperties') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class GenAIAppAsset():
"""
GenAIAppAsset.
:attr str asset_id:
:attr str url: (optional)
:attr str name: (optional)
:attr str asset_type: ai_decision_coordination is limited for AI Decision
Coordination. agent is limited to Agentitc AI App.
:attr str asset_rn: (optional) Asset Resource Name (used for integration with
3rd party ML engines).
:attr str created_at: (optional)
:attr str problem_type: (optional)
:attr str model_type: (optional)
:attr str runtime_environment: (optional)
:attr str input_data_type: (optional)
:attr str foundational_model_id: (optional)
:attr AssetLocale locale: (optional) represents languages used in both input and
output of the model.
"""
def __init__(self,
asset_id: str,
asset_type: str,
*,
url: str = None,
name: str = None,
asset_rn: str = None,
created_at: str = None,
problem_type: str = None,
model_type: str = None,
runtime_environment: str = None,
input_data_type: str = None,
foundational_model_id: str = None,
locale: 'AssetLocale' = None) -> None:
"""
Initialize a GenAIAppAsset object.
:param str asset_id:
:param str asset_type: ai_decision_coordination is limited for AI Decision
Coordination. agent is limited to Agentitc AI App.
:param str url: (optional)
:param str name: (optional)
:param str asset_rn: (optional) Asset Resource Name (used for integration
with 3rd party ML engines).
:param str created_at: (optional)
:param str problem_type: (optional)
:param str model_type: (optional)
:param str runtime_environment: (optional)
:param str input_data_type: (optional)
:param str foundational_model_id: (optional)
:param AssetLocale locale: (optional) represents languages used in both
input and output of the model.
"""
self.asset_id = asset_id
self.url = url
self.name = name
self.asset_type = asset_type
self.asset_rn = asset_rn
self.created_at = created_at
self.problem_type = problem_type
self.model_type = model_type
self.runtime_environment = runtime_environment
self.input_data_type = input_data_type
self.foundational_model_id = foundational_model_id
self.locale = locale
@classmethod
def from_dict(cls, _dict: Dict) -> 'GenAIAppAsset':
"""Initialize a GenAIAppAsset object from a json dictionary."""
args = {}
if 'asset_id' in _dict:
args['asset_id'] = _dict.get('asset_id')
else:
raise ValueError('Required property \'asset_id\' not present in GenAIAppAsset JSON')
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'asset_type' in _dict:
args['asset_type'] = _dict.get('asset_type')
else:
raise ValueError('Required property \'asset_type\' not present in GenAIAppAsset JSON')
if 'asset_rn' in _dict:
args['asset_rn'] = _dict.get('asset_rn')
if 'created_at' in _dict:
args['created_at'] = _dict.get('created_at')
if 'problem_type' in _dict:
args['problem_type'] = _dict.get('problem_type')
if 'model_type' in _dict:
args['model_type'] = _dict.get('model_type')
if 'runtime_environment' in _dict:
args['runtime_environment'] = _dict.get('runtime_environment')
if 'input_data_type' in _dict:
args['input_data_type'] = _dict.get('input_data_type')
if 'foundational_model_id' in _dict:
args['foundational_model_id'] = _dict.get('foundational_model_id')
if 'locale' in _dict:
args['locale'] = AssetLocale.from_dict(_dict.get('locale'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GenAIAppAsset object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'asset_id') and self.asset_id is not None:
_dict['asset_id'] = self.asset_id
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'asset_type') and self.asset_type is not None:
_dict['asset_type'] = self.asset_type
if hasattr(self, 'asset_rn') and self.asset_rn is not None:
_dict['asset_rn'] = self.asset_rn
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = self.created_at
if hasattr(self, 'problem_type') and self.problem_type is not None:
_dict['problem_type'] = self.problem_type
if hasattr(self, 'model_type') and self.model_type is not None:
_dict['model_type'] = self.model_type
if hasattr(self, 'runtime_environment') and self.runtime_environment is not None:
_dict['runtime_environment'] = self.runtime_environment
if hasattr(self, 'input_data_type') and self.input_data_type is not None:
_dict['input_data_type'] = self.input_data_type
if hasattr(self, 'foundational_model_id') and self.foundational_model_id is not None:
_dict['foundational_model_id'] = self.foundational_model_id
if hasattr(self, 'locale') and self.locale is not None:
_dict['locale'] = self.locale.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GenAIAppAsset object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GenAIAppAsset') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GenAIAppAsset') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class AssetTypeEnum(str, Enum):
"""
ai_decision_coordination is limited for AI Decision Coordination. agent is limited
to Agentitc AI App.
"""
MODEL = 'model'
FUNCTION = 'function'
PROMPT = 'prompt'
AI_DECISION_COORDINATION = 'ai_decision_coordination'
AGENT = 'agent'
class ProblemTypeEnum(str, Enum):
"""
problem_type.
"""
BINARY = 'binary'
REGRESSION = 'regression'
MULTICLASS = 'multiclass'
QUESTION_ANSWERING = 'question_answering'
SUMMARIZATION = 'summarization'
RETRIEVAL_AUGMENTED_GENERATION = 'retrieval_augmented_generation'
CLASSIFICATION = 'classification'
GENERATION = 'generation'
CODE = 'code'
EXTRACTION = 'extraction'
class InputDataTypeEnum(str, Enum):
"""
input_data_type.
"""
STRUCTURED = 'structured'
UNSTRUCTURED_IMAGE = 'unstructured_image'
UNSTRUCTURED_TEXT = 'unstructured_text'
CHAT = 'chat'
UNSTRUCTURED_VIDEO = 'unstructured_video'
UNSTRUCTURED_AUDIO = 'unstructured_audio'
class GenAIAppCollection():
"""
GenAIAppCollection.
:attr List[GenAIAppResponse] gen_ai_apps:
"""
def __init__(self,
gen_ai_apps: List['GenAIAppResponse']) -> None:
"""
Initialize a GenAIAppCollection object.
:param List[GenAIAppResponse] gen_ai_apps:
"""
self.gen_ai_apps = gen_ai_apps
@classmethod
def from_dict(cls, _dict: Dict) -> 'GenAIAppCollection':
"""Initialize a GenAIAppCollection object from a json dictionary."""
args = {}
if 'gen_ai_apps' in _dict:
args['gen_ai_apps'] = [GenAIAppResponse.from_dict(x) for x in _dict.get('gen_ai_apps')]
else:
raise ValueError('Required property \'gen_ai_apps\' not present in GenAIAppCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GenAIAppCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'gen_ai_apps') and self.gen_ai_apps is not None:
_dict['gen_ai_apps'] = [x.to_dict() for x in self.gen_ai_apps]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GenAIAppCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GenAIAppCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GenAIAppCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class GenAIAppDeployment():
"""
GenAIAppDeployment.
:attr str deployment_id: (optional)
:attr str deployment_rn: (optional) Deployment Resource Name (used for
integration with 3rd party ML engines).
:attr str url: (optional)
:attr str name: (optional)
:attr str description: (optional)
:attr str deployment_type: (optional) Deployment type.
:attr str created_at: (optional)
:attr ScoringEndpoint scoring_endpoint: (optional) Definition of scoring
endpoint in custom_machine_learning.
:attr List[InferenceEndpoint] inference_endpoint: (optional) inference endpoints
for the deployment at watsonx.ai. Either of `inference_endpoint` or
`scoring_endpoint` should be provided. If both given, underlying API will reject
the request.
"""
def __init__(self,
*,
deployment_id: str = None,
deployment_rn: str = None,
url: str = None,
name: str = None,
description: str = None,
deployment_type: str = None,
created_at: str = None,
scoring_endpoint: 'ScoringEndpoint' = None,
inference_endpoint: List['InferenceEndpoint'] = None) -> None:
"""
Initialize a GenAIAppDeployment object.
:param str deployment_id: (optional)
:param str deployment_rn: (optional) Deployment Resource Name (used for
integration with 3rd party ML engines).
:param str url: (optional)
:param str name: (optional)
:param str description: (optional)
:param str deployment_type: (optional) Deployment type.
:param str created_at: (optional)
:param ScoringEndpoint scoring_endpoint: (optional) Definition of scoring
endpoint in custom_machine_learning.
:param List[InferenceEndpoint] inference_endpoint: (optional) inference
endpoints for the deployment at watsonx.ai. Either of `inference_endpoint`
or `scoring_endpoint` should be provided. If both given, underlying API
will reject the request.
"""
self.deployment_id = deployment_id
self.deployment_rn = deployment_rn
self.url = url
self.name = name
self.description = description
self.deployment_type = deployment_type
self.created_at = created_at
self.scoring_endpoint = scoring_endpoint
self.inference_endpoint = inference_endpoint
@classmethod
def from_dict(cls, _dict: Dict) -> 'GenAIAppDeployment':
"""Initialize a GenAIAppDeployment object from a json dictionary."""
args = {}
if 'deployment_id' in _dict:
args['deployment_id'] = _dict.get('deployment_id')
if 'deployment_rn' in _dict:
args['deployment_rn'] = _dict.get('deployment_rn')
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'deployment_type' in _dict:
args['deployment_type'] = _dict.get('deployment_type')
if 'created_at' in _dict:
args['created_at'] = _dict.get('created_at')
if 'scoring_endpoint' in _dict:
args['scoring_endpoint'] = ScoringEndpoint.from_dict(_dict.get('scoring_endpoint'))
if 'inference_endpoint' in _dict:
args['inference_endpoint'] = [InferenceEndpoint.from_dict(x) for x in _dict.get('inference_endpoint')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GenAIAppDeployment object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'deployment_id') and self.deployment_id is not None:
_dict['deployment_id'] = self.deployment_id
if hasattr(self, 'deployment_rn') and self.deployment_rn is not None:
_dict['deployment_rn'] = self.deployment_rn
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'deployment_type') and self.deployment_type is not None:
_dict['deployment_type'] = self.deployment_type
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = self.created_at
if hasattr(self, 'scoring_endpoint') and self.scoring_endpoint is not None:
_dict['scoring_endpoint'] = self.scoring_endpoint.to_dict()
if hasattr(self, 'inference_endpoint') and self.inference_endpoint is not None:
_dict['inference_endpoint'] = [x.to_dict() for x in self.inference_endpoint]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GenAIAppDeployment object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GenAIAppDeployment') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GenAIAppDeployment') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DeploymentTypeEnum(str, Enum):
"""
Deployment type.
"""
ONLINE = 'online'
BATCH = 'batch'
DETACHED = 'detached'
class GenAIAppEntity():
"""
Gen AI app definition.
:attr str service_provider_id: The GUID of the Service Provider.
:attr str type: Type of the application.
:attr GenAIAppAsset asset:
:attr GenAIAppDeployment deployment:
:attr GenAIAppAgentProperties agent_properties: (optional) manages parameters to
represents agentic ai characteristics.
:attr Status status: (optional)
"""
def __init__(self,
service_provider_id: str,
type: str,
asset: 'GenAIAppAsset',
deployment: 'GenAIAppDeployment',
*,
agent_properties: 'GenAIAppAgentProperties' = None,
status: 'Status' = None) -> None:
"""
Initialize a GenAIAppEntity object.
:param str service_provider_id: The GUID of the Service Provider.
:param str type: Type of the application.
:param GenAIAppAsset asset:
:param GenAIAppDeployment deployment:
:param GenAIAppAgentProperties agent_properties: (optional) manages
parameters to represents agentic ai characteristics.
:param Status status: (optional)
"""
self.service_provider_id = service_provider_id
self.type = type
self.asset = asset
self.deployment = deployment
self.agent_properties = agent_properties
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'GenAIAppEntity':
"""Initialize a GenAIAppEntity object from a json dictionary."""
args = {}
if 'service_provider_id' in _dict:
args['service_provider_id'] = _dict.get('service_provider_id')
else:
raise ValueError('Required property \'service_provider_id\' not present in GenAIAppEntity JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in GenAIAppEntity JSON')
if 'asset' in _dict:
args['asset'] = GenAIAppAsset.from_dict(_dict.get('asset'))
else:
raise ValueError('Required property \'asset\' not present in GenAIAppEntity JSON')
if 'deployment' in _dict:
args['deployment'] = GenAIAppDeployment.from_dict(_dict.get('deployment'))
else:
raise ValueError('Required property \'deployment\' not present in GenAIAppEntity JSON')
if 'agent_properties' in _dict:
args['agent_properties'] = GenAIAppAgentProperties.from_dict(_dict.get('agent_properties'))
if 'status' in _dict:
args['status'] = Status.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GenAIAppEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'service_provider_id') and self.service_provider_id is not None:
_dict['service_provider_id'] = self.service_provider_id
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'asset') and self.asset is not None:
_dict['asset'] = self.asset.to_dict()
if hasattr(self, 'deployment') and self.deployment is not None:
_dict['deployment'] = self.deployment.to_dict()
if hasattr(self, 'agent_properties') and self.agent_properties is not None:
_dict['agent_properties'] = self.agent_properties.to_dict()
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GenAIAppEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GenAIAppEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GenAIAppEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
Type of the application.
"""
AGENTIC = 'agentic'
WORKFLOW = 'workflow'
CUSTOM = 'custom'
class GenAIAppResponse():
"""
GenAIAppResponse.
:attr Metadata metadata: (optional)
:attr GenAIAppEntity entity: (optional) Gen AI app definition.
"""
def __init__(self,
*,
metadata: 'Metadata' = None,
entity: 'GenAIAppEntity' = None) -> None:
"""
Initialize a GenAIAppResponse object.
:param Metadata metadata: (optional)
:param GenAIAppEntity entity: (optional) Gen AI app definition.
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'GenAIAppResponse':
"""Initialize a GenAIAppResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
if 'entity' in _dict:
args['entity'] = GenAIAppEntity.from_dict(_dict.get('entity'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GenAIAppResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GenAIAppResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GenAIAppResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GenAIAppResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class GenericErrorResponse():
"""
GenericErrorResponse.
:attr str trace: ID of the original request.
:attr List[GenericErrorResponseErrorsItem] errors:
"""
def __init__(self,
trace: str,
errors: List['GenericErrorResponseErrorsItem']) -> None:
"""
Initialize a GenericErrorResponse object.
:param str trace: ID of the original request.
:param List[GenericErrorResponseErrorsItem] errors:
"""
self.trace = trace
self.errors = errors
@classmethod
def from_dict(cls, _dict: Dict) -> 'GenericErrorResponse':
"""Initialize a GenericErrorResponse object from a json dictionary."""
args = {}
if 'trace' in _dict:
args['trace'] = _dict.get('trace')
else:
raise ValueError('Required property \'trace\' not present in GenericErrorResponse JSON')
if 'errors' in _dict:
args['errors'] = [GenericErrorResponseErrorsItem.from_dict(x) for x in _dict.get('errors')]
else:
raise ValueError('Required property \'errors\' not present in GenericErrorResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GenericErrorResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'trace') and self.trace is not None:
_dict['trace'] = self.trace
if hasattr(self, 'errors') and self.errors is not None:
_dict['errors'] = [x.to_dict() for x in self.errors]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GenericErrorResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GenericErrorResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GenericErrorResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class GenericErrorResponseErrorsItem():
"""
GenericErrorResponseErrorsItem.
:attr str code: Error code.
:attr str message: Error message.
:attr List[str] parameters: (optional) Error message parameters.
"""
def __init__(self,
code: str,
message: str,
*,
parameters: List[str] = None) -> None:
"""
Initialize a GenericErrorResponseErrorsItem object.
:param str code: Error code.
:param str message: Error message.
:param List[str] parameters: (optional) Error message parameters.
"""
self.code = code
self.message = message
self.parameters = parameters
@classmethod
def from_dict(cls, _dict: Dict) -> 'GenericErrorResponseErrorsItem':
"""Initialize a GenericErrorResponseErrorsItem object from a json dictionary."""
args = {}
if 'code' in _dict:
args['code'] = _dict.get('code')
else:
raise ValueError('Required property \'code\' not present in GenericErrorResponseErrorsItem JSON')
if 'message' in _dict:
args['message'] = _dict.get('message')
else:
raise ValueError('Required property \'message\' not present in GenericErrorResponseErrorsItem JSON')
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GenericErrorResponseErrorsItem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'code') and self.code is not None:
_dict['code'] = self.code
if hasattr(self, 'message') and self.message is not None:
_dict['message'] = self.message
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GenericErrorResponseErrorsItem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GenericErrorResponseErrorsItem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GenericErrorResponseErrorsItem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class GetExplanationTaskResponse():
"""
Get explanation task response.
:attr GetExplanationTaskResponseMetadata metadata: Metadata of get explanation
task response.
:attr GetExplanationTaskResponseEntity entity: Entity of get explanation task
response.
"""
def __init__(self,
metadata: 'GetExplanationTaskResponseMetadata',
entity: 'GetExplanationTaskResponseEntity') -> None:
"""
Initialize a GetExplanationTaskResponse object.
:param GetExplanationTaskResponseMetadata metadata: Metadata of get
explanation task response.
:param GetExplanationTaskResponseEntity entity: Entity of get explanation
task response.
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'GetExplanationTaskResponse':
"""Initialize a GetExplanationTaskResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = GetExplanationTaskResponseMetadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in GetExplanationTaskResponse JSON')
if 'entity' in _dict:
args['entity'] = GetExplanationTaskResponseEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in GetExplanationTaskResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GetExplanationTaskResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GetExplanationTaskResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GetExplanationTaskResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GetExplanationTaskResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class GetExplanationTaskResponseEntity():
"""
Entity of get explanation task response.
:attr GetExplanationTaskResponseEntityStatus status: Status of the explanation
task.
:attr ExplanationTaskResponseEntityAsset asset: (optional) Asset details in get
explanation task response.
:attr List[ExplanationTaskResponseEntityInputFeature] input_features: (optional)
List of input features.
:attr str perturbed: (optional) Indicate whether the transaction is perturbed or
not.
:attr List[object] explanations: (optional) List of generated explanations.
:attr List[ExplanationError] errors: (optional) List of errors occurred while
generating explanations.
:attr str scoring_id: (optional) ID of the scoring transaction.
"""
def __init__(self,
status: 'GetExplanationTaskResponseEntityStatus',
*,
asset: 'ExplanationTaskResponseEntityAsset' = None,
input_features: List['ExplanationTaskResponseEntityInputFeature'] = None,
perturbed: str = None,
explanations: List[object] = None,
errors: List['ExplanationError'] = None,
scoring_id: str = None) -> None:
"""
Initialize a GetExplanationTaskResponseEntity object.
:param GetExplanationTaskResponseEntityStatus status: Status of the
explanation task.
:param ExplanationTaskResponseEntityAsset asset: (optional) Asset details
in get explanation task response.
:param List[ExplanationTaskResponseEntityInputFeature] input_features:
(optional) List of input features.
:param str perturbed: (optional) Indicate whether the transaction is
perturbed or not.
:param List[object] explanations: (optional) List of generated
explanations.
:param List[ExplanationError] errors: (optional) List of errors occurred
while generating explanations.
:param str scoring_id: (optional) ID of the scoring transaction.
"""
self.status = status
self.asset = asset
self.input_features = input_features
self.perturbed = perturbed
self.explanations = explanations
self.errors = errors
self.scoring_id = scoring_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'GetExplanationTaskResponseEntity':
"""Initialize a GetExplanationTaskResponseEntity object from a json dictionary."""
args = {}
if 'status' in _dict:
args['status'] = GetExplanationTaskResponseEntityStatus.from_dict(_dict.get('status'))
else:
raise ValueError('Required property \'status\' not present in GetExplanationTaskResponseEntity JSON')
if 'asset' in _dict:
args['asset'] = ExplanationTaskResponseEntityAsset.from_dict(_dict.get('asset'))
if 'input_features' in _dict:
args['input_features'] = [ExplanationTaskResponseEntityInputFeature.from_dict(x) for x in _dict.get('input_features')]
if 'perturbed' in _dict:
args['perturbed'] = _dict.get('perturbed')
if 'explanations' in _dict:
args['explanations'] = _dict.get('explanations')
if 'errors' in _dict:
args['errors'] = [ExplanationError.from_dict(x) for x in _dict.get('errors')]
if 'scoring_id' in _dict:
args['scoring_id'] = _dict.get('scoring_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GetExplanationTaskResponseEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
if hasattr(self, 'asset') and self.asset is not None:
_dict['asset'] = self.asset.to_dict()
if hasattr(self, 'input_features') and self.input_features is not None:
_dict['input_features'] = [x.to_dict() for x in self.input_features]
if hasattr(self, 'perturbed') and self.perturbed is not None:
_dict['perturbed'] = self.perturbed
if hasattr(self, 'explanations') and self.explanations is not None:
_dict['explanations'] = self.explanations
if hasattr(self, 'errors') and self.errors is not None:
_dict['errors'] = [x.to_dict() for x in self.errors]
if hasattr(self, 'scoring_id') and self.scoring_id is not None:
_dict['scoring_id'] = self.scoring_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GetExplanationTaskResponseEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GetExplanationTaskResponseEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GetExplanationTaskResponseEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PerturbedEnum(str, Enum):
"""
Indicate whether the transaction is perturbed or not.
"""
TRUE = 'true'
FALSE = 'false'
class GetExplanationTaskResponseEntityStatus():
"""
Status of the explanation task.
:attr str state: (optional) Overall status of the explanation task.
"""
def __init__(self,
*,
state: str = None) -> None:
"""
Initialize a GetExplanationTaskResponseEntityStatus object.
:param str state: (optional) Overall status of the explanation task.
"""
self.state = state
@classmethod
def from_dict(cls, _dict: Dict) -> 'GetExplanationTaskResponseEntityStatus':
"""Initialize a GetExplanationTaskResponseEntityStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GetExplanationTaskResponseEntityStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GetExplanationTaskResponseEntityStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GetExplanationTaskResponseEntityStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GetExplanationTaskResponseEntityStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
Overall status of the explanation task.
"""
IN_PROGRESS = 'in_progress'
FINISHED = 'finished'
ERROR = 'error'
class GetExplanationTaskResponseMetadata():
"""
Metadata of get explanation task response.
:attr str explanation_task_id: Identifier for tracking explanation task.
:attr str created_by: ID of the user creating explanation task.
:attr str created_at: Time when the explanation task was initiated.
:attr str updated_at: (optional) Time when the explanation task was last
updated.
"""
def __init__(self,
explanation_task_id: str,
created_by: str,
created_at: str,
*,
updated_at: str = None) -> None:
"""
Initialize a GetExplanationTaskResponseMetadata object.
:param str explanation_task_id: Identifier for tracking explanation task.
:param str created_by: ID of the user creating explanation task.
:param str created_at: Time when the explanation task was initiated.
:param str updated_at: (optional) Time when the explanation task was last
updated.
"""
self.explanation_task_id = explanation_task_id
self.created_by = created_by
self.created_at = created_at
self.updated_at = updated_at
@classmethod
def from_dict(cls, _dict: Dict) -> 'GetExplanationTaskResponseMetadata':
"""Initialize a GetExplanationTaskResponseMetadata object from a json dictionary."""
args = {}
if 'explanation_task_id' in _dict:
args['explanation_task_id'] = _dict.get('explanation_task_id')
else:
raise ValueError('Required property \'explanation_task_id\' not present in GetExplanationTaskResponseMetadata JSON')
if 'created_by' in _dict:
args['created_by'] = _dict.get('created_by')
else:
raise ValueError('Required property \'created_by\' not present in GetExplanationTaskResponseMetadata JSON')
if 'created_at' in _dict:
args['created_at'] = _dict.get('created_at')
else:
raise ValueError('Required property \'created_at\' not present in GetExplanationTaskResponseMetadata JSON')
if 'updated_at' in _dict:
args['updated_at'] = _dict.get('updated_at')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GetExplanationTaskResponseMetadata object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'explanation_task_id') and self.explanation_task_id is not None:
_dict['explanation_task_id'] = self.explanation_task_id
if hasattr(self, 'created_by') and self.created_by is not None:
_dict['created_by'] = self.created_by
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = self.created_at
if hasattr(self, 'updated_at') and self.updated_at is not None:
_dict['updated_at'] = self.updated_at
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GetExplanationTaskResponseMetadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GetExplanationTaskResponseMetadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GetExplanationTaskResponseMetadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class GetExplanationTasksResponse():
"""
List all explanations response.
:attr int total_count: Total number of computed explanations.
:attr int limit: Maximum number of returned explanations.
:attr int offset: Offset of returned explanations.
:attr List[str] explanation_fields: The list of explanation fields.
:attr List[str] explanation_values: (optional) The list of explanation values.
"""
def __init__(self,
total_count: int,
limit: int,
offset: int,
explanation_fields: List[str],
*,
explanation_values: List[str] = None) -> None:
"""
Initialize a GetExplanationTasksResponse object.
:param int total_count: Total number of computed explanations.
:param int limit: Maximum number of returned explanations.
:param int offset: Offset of returned explanations.
:param List[str] explanation_fields: The list of explanation fields.
:param List[str] explanation_values: (optional) The list of explanation
values.
"""
self.total_count = total_count
self.limit = limit
self.offset = offset
self.explanation_fields = explanation_fields
self.explanation_values = explanation_values
@classmethod
def from_dict(cls, _dict: Dict) -> 'GetExplanationTasksResponse':
"""Initialize a GetExplanationTasksResponse object from a json dictionary."""
args = {}
if 'total_count' in _dict:
args['total_count'] = _dict.get('total_count')
else:
raise ValueError('Required property \'total_count\' not present in GetExplanationTasksResponse JSON')
if 'limit' in _dict:
args['limit'] = _dict.get('limit')
else:
raise ValueError('Required property \'limit\' not present in GetExplanationTasksResponse JSON')
if 'offset' in _dict:
args['offset'] = _dict.get('offset')
else:
raise ValueError('Required property \'offset\' not present in GetExplanationTasksResponse JSON')
if 'explanation_fields' in _dict:
args['explanation_fields'] = _dict.get('explanation_fields')
else:
raise ValueError('Required property \'explanation_fields\' not present in GetExplanationTasksResponse JSON')
if 'explanation_values' in _dict:
args['explanation_values'] = _dict.get('explanation_values')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GetExplanationTasksResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'total_count') and self.total_count is not None:
_dict['total_count'] = self.total_count
if hasattr(self, 'limit') and self.limit is not None:
_dict['limit'] = self.limit
if hasattr(self, 'offset') and self.offset is not None:
_dict['offset'] = self.offset
if hasattr(self, 'explanation_fields') and self.explanation_fields is not None:
_dict['explanation_fields'] = self.explanation_fields
if hasattr(self, 'explanation_values') and self.explanation_values is not None:
_dict['explanation_values'] = self.explanation_values
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GetExplanationTasksResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GetExplanationTasksResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GetExplanationTasksResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class GraphVertexProperties():
"""
GraphVertexProperties.
:attr str id: (optional)
:attr GraphVertexPropertiesProperties properties: (optional)
"""
def __init__(self,
*,
id: str = None,
properties: 'GraphVertexPropertiesProperties' = None) -> None:
"""
Initialize a GraphVertexProperties object.
:param str id: (optional)
:param GraphVertexPropertiesProperties properties: (optional)
"""
self.id = id
self.properties = properties
@classmethod
def from_dict(cls, _dict: Dict) -> 'GraphVertexProperties':
"""Initialize a GraphVertexProperties object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
if 'properties' in _dict:
args['properties'] = GraphVertexPropertiesProperties.from_dict(_dict.get('properties'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GraphVertexProperties object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'properties') and self.properties is not None:
_dict['properties'] = self.properties.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GraphVertexProperties object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GraphVertexProperties') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GraphVertexProperties') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class GraphVertexPropertiesProperties():
"""
GraphVertexPropertiesProperties.
:attr str target_target_type: (optional)
:attr str resource_type: (optional)
:attr str target_target_id: (optional)
:attr str rev: (optional)
:attr str status: (optional)
:attr datetime touched_at: (optional)
:attr str type: (optional)
"""
def __init__(self,
*,
target_target_type: str = None,
resource_type: str = None,
target_target_id: str = None,
rev: str = None,
status: str = None,
touched_at: datetime = None,
type: str = None) -> None:
"""
Initialize a GraphVertexPropertiesProperties object.
:param str target_target_type: (optional)
:param str resource_type: (optional)
:param str target_target_id: (optional)
:param str rev: (optional)
:param str status: (optional)
:param datetime touched_at: (optional)
:param str type: (optional)
"""
self.target_target_type = target_target_type
self.resource_type = resource_type
self.target_target_id = target_target_id
self.rev = rev
self.status = status
self.touched_at = touched_at
self.type = type
@classmethod
def from_dict(cls, _dict: Dict) -> 'GraphVertexPropertiesProperties':
"""Initialize a GraphVertexPropertiesProperties object from a json dictionary."""
args = {}
if 'target.target_type' in _dict:
args['target_target_type'] = _dict.get('target.target_type')
if 'resource_type' in _dict:
args['resource_type'] = _dict.get('resource_type')
if 'target.target_id' in _dict:
args['target_target_id'] = _dict.get('target.target_id')
if 'rev' in _dict:
args['rev'] = _dict.get('rev')
if 'status' in _dict:
args['status'] = _dict.get('status')
if 'touched_at' in _dict:
args['touched_at'] = string_to_datetime(_dict.get('touched_at'))
if 'type' in _dict:
args['type'] = _dict.get('type')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a GraphVertexPropertiesProperties object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'target_target_type') and self.target_target_type is not None:
_dict['target.target_type'] = self.target_target_type
if hasattr(self, 'resource_type') and self.resource_type is not None:
_dict['resource_type'] = self.resource_type
if hasattr(self, 'target_target_id') and self.target_target_id is not None:
_dict['target.target_id'] = self.target_target_id
if hasattr(self, 'rev') and self.rev is not None:
_dict['rev'] = self.rev
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status
if hasattr(self, 'touched_at') and self.touched_at is not None:
_dict['touched_at'] = datetime_to_string(self.touched_at)
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this GraphVertexPropertiesProperties object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'GraphVertexPropertiesProperties') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'GraphVertexPropertiesProperties') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class InferenceEndpoint():
"""
Definition of inference endpoint deployed at watsonx.ai.
:attr str url: URL of the inference endpoint.
:attr bool sse: (optional) This is true if the inference API supports SSE
streaming.
:attr bool uses_serving_name: (optional) This is true if the inference API uses
the serving_name that was defined in this deployment.
"""
def __init__(self,
url: str,
*,
sse: bool = None,
uses_serving_name: bool = None) -> None:
"""
Initialize a InferenceEndpoint object.
:param str url: URL of the inference endpoint.
:param bool sse: (optional) This is true if the inference API supports SSE
streaming.
:param bool uses_serving_name: (optional) This is true if the inference API
uses the serving_name that was defined in this deployment.
"""
self.url = url
self.sse = sse
self.uses_serving_name = uses_serving_name
@classmethod
def from_dict(cls, _dict: Dict) -> 'InferenceEndpoint':
"""Initialize a InferenceEndpoint object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
else:
raise ValueError('Required property \'url\' not present in InferenceEndpoint JSON')
if 'sse' in _dict:
args['sse'] = _dict.get('sse')
if 'uses_serving_name' in _dict:
args['uses_serving_name'] = _dict.get('uses_serving_name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a InferenceEndpoint object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'sse') and self.sse is not None:
_dict['sse'] = self.sse
if hasattr(self, 'uses_serving_name') and self.uses_serving_name is not None:
_dict['uses_serving_name'] = self.uses_serving_name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this InferenceEndpoint object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'InferenceEndpoint') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'InferenceEndpoint') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class InputDataReference():
"""
InputDataReference is the same as TrainingDataReference except that neither location
nor connection is required. This is needed for the Schemas API and to avoid updating
existing APIs.
:attr str type: Type of the storage.
:attr TrainingDataReferenceLocation location: (optional) training data set
location.
:attr TrainingDataReferenceConnection connection: (optional) training data set
connection credentials.
:attr str name: (optional)
"""
def __init__(self,
type: str,
*,
location: 'TrainingDataReferenceLocation' = None,
connection: 'TrainingDataReferenceConnection' = None,
name: str = None) -> None:
"""
Initialize a InputDataReference object.
:param str type: Type of the storage.
:param TrainingDataReferenceLocation location: (optional) training data set
location.
:param TrainingDataReferenceConnection connection: (optional) training data
set connection credentials.
:param str name: (optional)
"""
self.type = type
self.location = location
self.connection = connection
self.name = name
@classmethod
def from_dict(cls, _dict: Dict) -> 'InputDataReference':
"""Initialize a InputDataReference object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in InputDataReference JSON')
if 'location' in _dict:
args['location'] = _dict.get('location')
if 'connection' in _dict:
args['connection'] = _dict.get('connection')
if 'name' in _dict:
args['name'] = _dict.get('name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a InputDataReference object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'location') and self.location is not None:
if isinstance(self.location, dict):
_dict['location'] = self.location
else:
_dict['location'] = self.location.to_dict()
if hasattr(self, 'connection') and self.connection is not None:
if isinstance(self.connection, dict):
_dict['connection'] = self.connection
else:
_dict['connection'] = self.connection.to_dict()
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this InputDataReference object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'InputDataReference') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'InputDataReference') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
Type of the storage.
"""
DB2 = 'db2'
COS = 'cos'
DATASET = 'dataset'
FILE_ASSET = 'file_asset'
class IntegratedMetric():
"""
IntegratedMetric.
:attr str integrated_system_type: (optional)
:attr str mapped_metrics: (optional)
"""
def __init__(self,
*,
integrated_system_type: str = None,
mapped_metrics: str = None) -> None:
"""
Initialize a IntegratedMetric object.
:param str integrated_system_type: (optional)
:param str mapped_metrics: (optional)
"""
self.integrated_system_type = integrated_system_type
self.mapped_metrics = mapped_metrics
@classmethod
def from_dict(cls, _dict: Dict) -> 'IntegratedMetric':
"""Initialize a IntegratedMetric object from a json dictionary."""
args = {}
if 'integrated_system_type' in _dict:
args['integrated_system_type'] = _dict.get('integrated_system_type')
if 'mapped_metrics' in _dict:
args['mapped_metrics'] = _dict.get('mapped_metrics')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a IntegratedMetric object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'integrated_system_type') and self.integrated_system_type is not None:
_dict['integrated_system_type'] = self.integrated_system_type
if hasattr(self, 'mapped_metrics') and self.mapped_metrics is not None:
_dict['mapped_metrics'] = self.mapped_metrics
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this IntegratedMetric object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'IntegratedMetric') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'IntegratedMetric') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class IntegratedSystem():
"""
Integrated System definition.
:attr str name: The name of the Integrated System.
:attr str type:
:attr str description: The description of the Integrated System.
:attr dict credentials: The credentials for the Integrated System.
:attr object connection: (optional) The additional connection information for
the Integrated System.
:attr str service_provider_id: (optional) The GUID of the Service Provider.
Should be specified when the integrated system should be managed with access
contorl over combination of container_id and container_type query params.
:attr List[str] group_ids: (optional) Access control list of group id of Cloud
Pak for Data (Only available for open_pages type and OpenScale on Cloud Pak for
Data >= 4.0.6 with ENABLE_GROUP_AUTH being true).
:attr List[str] user_ids: (optional) Access control list of user id of Cloud Pak
for Data (Only available for open_pages type and OpenScale on Cloud Pak for Data
>= 4.0.6 with ENABLE_GROUP_AUTH being true).
:attr object parameters: (optional) Additional parameters.
"""
def __init__(self,
name: str,
type: str,
description: str,
credentials: dict,
*,
connection: object = None,
service_provider_id: str = None,
group_ids: List[str] = None,
user_ids: List[str] = None,
parameters: object = None) -> None:
"""
Initialize a IntegratedSystem object.
:param str name: The name of the Integrated System.
:param str type:
:param str description: The description of the Integrated System.
:param dict credentials: The credentials for the Integrated System.
:param object connection: (optional) The additional connection information
for the Integrated System.
:param str service_provider_id: (optional) The GUID of the Service
Provider. Should be specified when the integrated system should be managed
with access contorl over combination of container_id and container_type
query params.
:param List[str] group_ids: (optional) Access control list of group id of
Cloud Pak for Data (Only available for open_pages type and OpenScale on
Cloud Pak for Data >= 4.0.6 with ENABLE_GROUP_AUTH being true).
:param List[str] user_ids: (optional) Access control list of user id of
Cloud Pak for Data (Only available for open_pages type and OpenScale on
Cloud Pak for Data >= 4.0.6 with ENABLE_GROUP_AUTH being true).
:param object parameters: (optional) Additional parameters.
"""
self.name = name
self.type = type
self.description = description
self.credentials = credentials
self.connection = connection
self.service_provider_id = service_provider_id
self.group_ids = group_ids
self.user_ids = user_ids
self.parameters = parameters
@classmethod
def from_dict(cls, _dict: Dict) -> 'IntegratedSystem':
"""Initialize a IntegratedSystem object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in IntegratedSystem JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in IntegratedSystem JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
else:
raise ValueError('Required property \'description\' not present in IntegratedSystem JSON')
if 'credentials' in _dict:
args['credentials'] = _dict.get('credentials')
else:
raise ValueError('Required property \'credentials\' not present in IntegratedSystem JSON')
if 'connection' in _dict:
args['connection'] = _dict.get('connection')
if 'service_provider_id' in _dict:
args['service_provider_id'] = _dict.get('service_provider_id')
if 'group_ids' in _dict:
args['group_ids'] = _dict.get('group_ids')
if 'user_ids' in _dict:
args['user_ids'] = _dict.get('user_ids')
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a IntegratedSystem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'credentials') and self.credentials is not None:
_dict['credentials'] = self.credentials
if hasattr(self, 'connection') and self.connection is not None:
_dict['connection'] = self.connection
if hasattr(self, 'service_provider_id') and self.service_provider_id is not None:
_dict['service_provider_id'] = self.service_provider_id
if hasattr(self, 'group_ids') and self.group_ids is not None:
_dict['group_ids'] = self.group_ids
if hasattr(self, 'user_ids') and self.user_ids is not None:
_dict['user_ids'] = self.user_ids
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this IntegratedSystem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'IntegratedSystem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'IntegratedSystem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
type.
"""
OPEN_PAGES = 'open_pages'
SLACK = 'slack'
WEBHOOK = 'webhook'
HIVE = 'hive'
SPARK = 'spark'
JDBC = 'jdbc'
CUSTOM_METRICS_PROVIDER = 'custom_metrics_provider'
WATSON_KNOWLEDGE_CATALOG = 'watson_knowledge_catalog'
GENERATIVE_AI_EVALUATOR = 'generative_ai_evaluator'
EMBEDDINGS_PROVIDER = 'embeddings_provider'
class IntegratedSystemCollection():
"""
IntegratedSystemCollection.
:attr List[IntegratedSystemResponse] integrated_systems:
"""
def __init__(self,
integrated_systems: List['IntegratedSystemResponse']) -> None:
"""
Initialize a IntegratedSystemCollection object.
:param List[IntegratedSystemResponse] integrated_systems:
"""
self.integrated_systems = integrated_systems
@classmethod
def from_dict(cls, _dict: Dict) -> 'IntegratedSystemCollection':
"""Initialize a IntegratedSystemCollection object from a json dictionary."""
args = {}
if 'integrated_systems' in _dict:
args['integrated_systems'] = [IntegratedSystemResponse.from_dict(x) for x in _dict.get('integrated_systems')]
else:
raise ValueError('Required property \'integrated_systems\' not present in IntegratedSystemCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a IntegratedSystemCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'integrated_systems') and self.integrated_systems is not None:
_dict['integrated_systems'] = [x.to_dict() for x in self.integrated_systems]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this IntegratedSystemCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'IntegratedSystemCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'IntegratedSystemCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class IntegratedSystemMetricsArray():
"""
IntegratedSystemMetricsArray.
:attr str type: (optional) The monitor for which the metrics needs to be
published to integrated system.
:attr List[object] measures: (optional)
:attr List[IntegratedMetric] integrated_metrics: (optional)
"""
def __init__(self,
*,
type: str = None,
measures: List[object] = None,
integrated_metrics: List['IntegratedMetric'] = None) -> None:
"""
Initialize a IntegratedSystemMetricsArray object.
:param str type: (optional) The monitor for which the metrics needs to be
published to integrated system.
:param List[object] measures: (optional)
:param List[IntegratedMetric] integrated_metrics: (optional)
"""
self.type = type
self.measures = measures
self.integrated_metrics = integrated_metrics
@classmethod
def from_dict(cls, _dict: Dict) -> 'IntegratedSystemMetricsArray':
"""Initialize a IntegratedSystemMetricsArray object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
if 'measures' in _dict:
args['measures'] = _dict.get('measures')
if 'integrated_metrics' in _dict:
args['integrated_metrics'] = [IntegratedMetric.from_dict(x) for x in _dict.get('integrated_metrics')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a IntegratedSystemMetricsArray object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'measures') and self.measures is not None:
_dict['measures'] = self.measures
if hasattr(self, 'integrated_metrics') and self.integrated_metrics is not None:
_dict['integrated_metrics'] = [x.to_dict() for x in self.integrated_metrics]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this IntegratedSystemMetricsArray object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'IntegratedSystemMetricsArray') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'IntegratedSystemMetricsArray') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class IntegratedSystemReference():
"""
Integrated System reference.
:attr str integrated_system_id: id of the Integrated System.
:attr str external_id: id of the resource in the Integrated System.
:attr object parameters: (optional) Additional parameters.
"""
def __init__(self,
integrated_system_id: str,
external_id: str,
*,
parameters: object = None) -> None:
"""
Initialize a IntegratedSystemReference object.
:param str integrated_system_id: id of the Integrated System.
:param str external_id: id of the resource in the Integrated System.
:param object parameters: (optional) Additional parameters.
"""
self.integrated_system_id = integrated_system_id
self.external_id = external_id
self.parameters = parameters
@classmethod
def from_dict(cls, _dict: Dict) -> 'IntegratedSystemReference':
"""Initialize a IntegratedSystemReference object from a json dictionary."""
args = {}
if 'integrated_system_id' in _dict:
args['integrated_system_id'] = _dict.get('integrated_system_id')
else:
raise ValueError('Required property \'integrated_system_id\' not present in IntegratedSystemReference JSON')
if 'external_id' in _dict:
args['external_id'] = _dict.get('external_id')
else:
raise ValueError('Required property \'external_id\' not present in IntegratedSystemReference JSON')
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a IntegratedSystemReference object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'integrated_system_id') and self.integrated_system_id is not None:
_dict['integrated_system_id'] = self.integrated_system_id
if hasattr(self, 'external_id') and self.external_id is not None:
_dict['external_id'] = self.external_id
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this IntegratedSystemReference object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'IntegratedSystemReference') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'IntegratedSystemReference') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class IntegratedSystemResponse():
"""
IntegratedSystemResponse.
:attr Metadata metadata: (optional)
:attr IntegratedSystem entity: (optional) Integrated System definition.
"""
def __init__(self,
*,
metadata: 'Metadata' = None,
entity: 'IntegratedSystem' = None) -> None:
"""
Initialize a IntegratedSystemResponse object.
:param Metadata metadata: (optional)
:param IntegratedSystem entity: (optional) Integrated System definition.
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'IntegratedSystemResponse':
"""Initialize a IntegratedSystemResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
if 'entity' in _dict:
args['entity'] = IntegratedSystem.from_dict(_dict.get('entity'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a IntegratedSystemResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this IntegratedSystemResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'IntegratedSystemResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'IntegratedSystemResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class JsonPatchOperation():
"""
This model represents an individual patch operation to be performed on a JSON
document, as defined by RFC 6902.
:attr str op: The operation to be performed.
:attr str path: The JSON Pointer that identifies the field that is the target of
the operation.
:attr str from_: (optional) The JSON Pointer that identifies the field that is
the source of the operation.
:attr object value: (optional) The value to be used within the operation.
"""
def __init__(self,
op: str,
path: str,
*,
from_: str = None,
value: object = None) -> None:
"""
Initialize a JsonPatchOperation object.
:param str op: The operation to be performed.
:param str path: The JSON Pointer that identifies the field that is the
target of the operation.
:param str from_: (optional) The JSON Pointer that identifies the field
that is the source of the operation.
:param object value: (optional) The value to be used within the operation.
"""
self.op = op
self.path = path
self.from_ = from_
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'JsonPatchOperation':
"""Initialize a JsonPatchOperation object from a json dictionary."""
args = {}
if 'op' in _dict:
args['op'] = _dict.get('op')
else:
raise ValueError('Required property \'op\' not present in JsonPatchOperation JSON')
if 'path' in _dict:
args['path'] = _dict.get('path')
else:
raise ValueError('Required property \'path\' not present in JsonPatchOperation JSON')
if 'from' in _dict:
args['from_'] = _dict.get('from')
if 'value' in _dict:
args['value'] = _dict.get('value')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a JsonPatchOperation object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'op') and self.op is not None:
_dict['op'] = self.op
if hasattr(self, 'path') and self.path is not None:
_dict['path'] = self.path
if hasattr(self, 'from_') and self.from_ is not None:
_dict['from'] = self.from_
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this JsonPatchOperation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'JsonPatchOperation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'JsonPatchOperation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class OpEnum(str, Enum):
"""
The operation to be performed.
"""
ADD = 'add'
REMOVE = 'remove'
REPLACE = 'replace'
MOVE = 'move'
COPY = 'copy'
TEST = 'test'
class ListDetectorsResponse():
"""
ListDetectorsResponse.
:attr List[Detector] detectors: List of built-in detectors from
detector_template.json.
:attr List[Detector] custom_detectors: List of custom detectors from CAMs.
"""
def __init__(self,
detectors: List['Detector'],
custom_detectors: List['Detector']) -> None:
"""
Initialize a ListDetectorsResponse object.
:param List[Detector] detectors: List of built-in detectors from
detector_template.json.
:param List[Detector] custom_detectors: List of custom detectors from CAMs.
"""
self.detectors = detectors
self.custom_detectors = custom_detectors
@classmethod
def from_dict(cls, _dict: Dict) -> 'ListDetectorsResponse':
"""Initialize a ListDetectorsResponse object from a json dictionary."""
args = {}
if 'detectors' in _dict:
args['detectors'] = [Detector.from_dict(x) for x in _dict.get('detectors')]
else:
raise ValueError('Required property \'detectors\' not present in ListDetectorsResponse JSON')
if 'custom_detectors' in _dict:
args['custom_detectors'] = [Detector.from_dict(x) for x in _dict.get('custom_detectors')]
else:
raise ValueError('Required property \'custom_detectors\' not present in ListDetectorsResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ListDetectorsResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'detectors') and self.detectors is not None:
_dict['detectors'] = [x.to_dict() for x in self.detectors]
if hasattr(self, 'custom_detectors') and self.custom_detectors is not None:
_dict['custom_detectors'] = [x.to_dict() for x in self.custom_detectors]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ListDetectorsResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ListDetectorsResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ListDetectorsResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class LocationSchemaName():
"""
LocationSchemaName.
:attr str schema_name: (optional) Database schema name (for PostgreSQL default
is a public schema).
"""
def __init__(self,
*,
schema_name: str = None) -> None:
"""
Initialize a LocationSchemaName object.
:param str schema_name: (optional) Database schema name (for PostgreSQL
default is a public schema).
"""
self.schema_name = schema_name
@classmethod
def from_dict(cls, _dict: Dict) -> 'LocationSchemaName':
"""Initialize a LocationSchemaName object from a json dictionary."""
args = {}
if 'schema_name' in _dict:
args['schema_name'] = _dict.get('schema_name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a LocationSchemaName object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'schema_name') and self.schema_name is not None:
_dict['schema_name'] = self.schema_name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this LocationSchemaName object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'LocationSchemaName') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'LocationSchemaName') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class LocationTableName():
"""
LocationTableName.
:attr str table_name: (optional) Database table name.
"""
def __init__(self,
*,
table_name: str = None) -> None:
"""
Initialize a LocationTableName object.
:param str table_name: (optional) Database table name.
"""
self.table_name = table_name
@classmethod
def from_dict(cls, _dict: Dict) -> 'LocationTableName':
"""Initialize a LocationTableName object from a json dictionary."""
args = {}
if 'table_name' in _dict:
args['table_name'] = _dict.get('table_name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a LocationTableName object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'table_name') and self.table_name is not None:
_dict['table_name'] = self.table_name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this LocationTableName object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'LocationTableName') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'LocationTableName') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MLCredentials():
"""
MLCredentials.
"""
def __init__(self,
**kwargs) -> None:
"""
Initialize a MLCredentials object.
:param **kwargs: (optional) Any additional properties.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['SageMakerCredentials', 'AzureCredentials', 'CustomCredentials', 'WMLCredentialsCloud', 'WMLCredentialsCP4D', 'SPSSCredentials', 'MLCredentialsWXOCredentials', 'UnknownCredentials']))
raise Exception(msg)
class MeasurementEntity():
"""
MeasurementEntity.
:attr datetime timestamp:
:attr str run_id: (optional) ID of the monitoring run which produced the
measurement.
:attr List[MonitorMeasurementValue] values: Metrics grouped for a single
measurement.
:attr int issue_count: Number of the metrics with issues, which exceeded limits.
:attr str asset_revision: (optional) Revision number of the ML model or function
used by the monitor.
:attr Target target: (optional)
:attr str monitor_instance_id: (optional)
:attr str monitor_definition_id: (optional)
"""
def __init__(self,
timestamp: datetime,
values: List['MonitorMeasurementValue'],
issue_count: int,
*,
run_id: str = None,
asset_revision: str = None,
target: 'Target' = None,
monitor_instance_id: str = None,
monitor_definition_id: str = None) -> None:
"""
Initialize a MeasurementEntity object.
:param datetime timestamp:
:param List[MonitorMeasurementValue] values: Metrics grouped for a single
measurement.
:param int issue_count: Number of the metrics with issues, which exceeded
limits.
:param str run_id: (optional) ID of the monitoring run which produced the
measurement.
:param str asset_revision: (optional) Revision number of the ML model or
function used by the monitor.
:param Target target: (optional)
:param str monitor_instance_id: (optional)
:param str monitor_definition_id: (optional)
"""
self.timestamp = timestamp
self.run_id = run_id
self.values = values
self.issue_count = issue_count
self.asset_revision = asset_revision
self.target = target
self.monitor_instance_id = monitor_instance_id
self.monitor_definition_id = monitor_definition_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'MeasurementEntity':
"""Initialize a MeasurementEntity object from a json dictionary."""
args = {}
if 'timestamp' in _dict:
args['timestamp'] = string_to_datetime(_dict.get('timestamp'))
else:
raise ValueError('Required property \'timestamp\' not present in MeasurementEntity JSON')
if 'run_id' in _dict:
args['run_id'] = _dict.get('run_id')
if 'values' in _dict:
args['values'] = [MonitorMeasurementValue.from_dict(x) for x in _dict.get('values')]
else:
raise ValueError('Required property \'values\' not present in MeasurementEntity JSON')
if 'issue_count' in _dict:
args['issue_count'] = _dict.get('issue_count')
else:
raise ValueError('Required property \'issue_count\' not present in MeasurementEntity JSON')
if 'asset_revision' in _dict:
args['asset_revision'] = _dict.get('asset_revision')
if 'target' in _dict:
args['target'] = Target.from_dict(_dict.get('target'))
if 'monitor_instance_id' in _dict:
args['monitor_instance_id'] = _dict.get('monitor_instance_id')
if 'monitor_definition_id' in _dict:
args['monitor_definition_id'] = _dict.get('monitor_definition_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MeasurementEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'timestamp') and self.timestamp is not None:
_dict['timestamp'] = datetime_to_string(self.timestamp)
if hasattr(self, 'run_id') and self.run_id is not None:
_dict['run_id'] = self.run_id
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = [x.to_dict() for x in self.values]
if hasattr(self, 'issue_count') and self.issue_count is not None:
_dict['issue_count'] = self.issue_count
if hasattr(self, 'asset_revision') and self.asset_revision is not None:
_dict['asset_revision'] = self.asset_revision
if hasattr(self, 'target') and self.target is not None:
_dict['target'] = self.target.to_dict()
if hasattr(self, 'monitor_instance_id') and self.monitor_instance_id is not None:
_dict['monitor_instance_id'] = self.monitor_instance_id
if hasattr(self, 'monitor_definition_id') and self.monitor_definition_id is not None:
_dict['monitor_definition_id'] = self.monitor_definition_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MeasurementEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MeasurementEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MeasurementEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MeasurementsResponseCollection():
"""
MeasurementsResponseCollection.
:attr List[MeasurementsResponseCollectionMeasurementsItem] measurements:
"""
def __init__(self,
measurements: List['MeasurementsResponseCollectionMeasurementsItem']) -> None:
"""
Initialize a MeasurementsResponseCollection object.
:param List[MeasurementsResponseCollectionMeasurementsItem] measurements:
"""
self.measurements = measurements
@classmethod
def from_dict(cls, _dict: Dict) -> 'MeasurementsResponseCollection':
"""Initialize a MeasurementsResponseCollection object from a json dictionary."""
args = {}
if 'measurements' in _dict:
args['measurements'] = [MeasurementsResponseCollectionMeasurementsItem.from_dict(x) for x in _dict.get('measurements')]
else:
raise ValueError('Required property \'measurements\' not present in MeasurementsResponseCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MeasurementsResponseCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'measurements') and self.measurements is not None:
_dict['measurements'] = [x.to_dict() for x in self.measurements]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MeasurementsResponseCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MeasurementsResponseCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MeasurementsResponseCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MeasurementsResponseCollectionMeasurementsItem():
"""
MeasurementsResponseCollectionMeasurementsItem.
:attr Metadata metadata:
:attr MeasurementEntity entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'MeasurementEntity') -> None:
"""
Initialize a MeasurementsResponseCollectionMeasurementsItem object.
:param Metadata metadata:
:param MeasurementEntity entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'MeasurementsResponseCollectionMeasurementsItem':
"""Initialize a MeasurementsResponseCollectionMeasurementsItem object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in MeasurementsResponseCollectionMeasurementsItem JSON')
if 'entity' in _dict:
args['entity'] = MeasurementEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in MeasurementsResponseCollectionMeasurementsItem JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MeasurementsResponseCollectionMeasurementsItem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MeasurementsResponseCollectionMeasurementsItem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MeasurementsResponseCollectionMeasurementsItem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MeasurementsResponseCollectionMeasurementsItem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class Metadata():
"""
Metadata.
:attr str id: The ID (typically a GUID) which uniquely identifies the resource.
:attr str crn: (optional) Cloud Resource Name (CRN) uniquely identify IBM Cloud
resource (https://console.bluemix.net/docs/overview/crn.html).
:attr str url: The URL which can be used to uniquely refer to the resource
Typically a GET on this url would return details of the resource, a DELETE would
delete it and a PUT/PATCH would update it.
:attr datetime created_at: (optional) The timestamp when the resource was first
created In format YYYY-MM-DDTHH:mm:ssZ or YYYY-MM-DDTHH:mm:ss.sssZ, matching the
date-time format as specified by RFC 3339.
:attr str created_by: (optional) The IAM ID of the user who created the
resource.
:attr datetime modified_at: (optional) The timestamp when the resource was first
created In format YYYY-MM-DDTHH:mm:ssZ or YYYY-MM-DDTHH:mm:ss.sssZ, matching the
date-time format as specified by RFC 3339.
:attr str modified_by: (optional) The IAM ID of the user who last modified the
resource.
:attr str account_id: (optional) The BSS Account id of the account.
"""
def __init__(self,
id: str,
url: str,
*,
crn: str = None,
created_at: datetime = None,
created_by: str = None,
modified_at: datetime = None,
modified_by: str = None,
account_id: str = None) -> None:
"""
Initialize a Metadata object.
:param str id: The ID (typically a GUID) which uniquely identifies the
resource.
:param str url: The URL which can be used to uniquely refer to the resource
Typically a GET on this url would return details of the resource, a DELETE
would delete it and a PUT/PATCH would update it.
:param str crn: (optional) Cloud Resource Name (CRN) uniquely identify IBM
Cloud resource (https://console.bluemix.net/docs/overview/crn.html).
:param datetime created_at: (optional) The timestamp when the resource was
first created In format YYYY-MM-DDTHH:mm:ssZ or YYYY-MM-DDTHH:mm:ss.sssZ,
matching the date-time format as specified by RFC 3339.
:param str created_by: (optional) The IAM ID of the user who created the
resource.
:param datetime modified_at: (optional) The timestamp when the resource was
first created In format YYYY-MM-DDTHH:mm:ssZ or YYYY-MM-DDTHH:mm:ss.sssZ,
matching the date-time format as specified by RFC 3339.
:param str modified_by: (optional) The IAM ID of the user who last modified
the resource.
:param str account_id: (optional) The BSS Account id of the account.
"""
self.id = id
self.crn = crn
self.url = url
self.created_at = created_at
self.created_by = created_by
self.modified_at = modified_at
self.modified_by = modified_by
self.account_id = account_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'Metadata':
"""Initialize a Metadata object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in Metadata JSON')
if 'crn' in _dict:
args['crn'] = _dict.get('crn')
if 'url' in _dict:
args['url'] = _dict.get('url')
else:
raise ValueError('Required property \'url\' not present in Metadata JSON')
if 'created_at' in _dict:
args['created_at'] = string_to_datetime(_dict.get('created_at'))
if 'created_by' in _dict:
args['created_by'] = _dict.get('created_by')
if 'modified_at' in _dict:
args['modified_at'] = string_to_datetime(_dict.get('modified_at'))
if 'modified_by' in _dict:
args['modified_by'] = _dict.get('modified_by')
if 'account_id' in _dict:
args['account_id'] = _dict.get('account_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Metadata object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'crn') and self.crn is not None:
_dict['crn'] = self.crn
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = datetime_to_string(self.created_at)
if hasattr(self, 'created_by') and self.created_by is not None:
_dict['created_by'] = self.created_by
if hasattr(self, 'modified_at') and self.modified_at is not None:
_dict['modified_at'] = datetime_to_string(self.modified_at)
if hasattr(self, 'modified_by') and self.modified_by is not None:
_dict['modified_by'] = self.modified_by
if hasattr(self, 'account_id') and self.account_id is not None:
_dict['account_id'] = self.account_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Metadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Metadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Metadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MetricSpecificThresholdObject():
"""
MetricSpecificThresholdObject.
:attr str id:
:attr float default: default value of threshold.
:attr str recommendation: (optional)
:attr List[ThresholdConditionObject] applies_to:
"""
def __init__(self,
id: str,
default: float,
applies_to: List['ThresholdConditionObject'],
*,
recommendation: str = None) -> None:
"""
Initialize a MetricSpecificThresholdObject object.
:param str id:
:param float default: default value of threshold.
:param List[ThresholdConditionObject] applies_to:
:param str recommendation: (optional)
"""
self.id = id
self.default = default
self.recommendation = recommendation
self.applies_to = applies_to
@classmethod
def from_dict(cls, _dict: Dict) -> 'MetricSpecificThresholdObject':
"""Initialize a MetricSpecificThresholdObject object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in MetricSpecificThresholdObject JSON')
if 'default' in _dict:
args['default'] = _dict.get('default')
else:
raise ValueError('Required property \'default\' not present in MetricSpecificThresholdObject JSON')
if 'recommendation' in _dict:
args['recommendation'] = _dict.get('recommendation')
if 'applies_to' in _dict:
args['applies_to'] = [ThresholdConditionObject.from_dict(x) for x in _dict.get('applies_to')]
else:
raise ValueError('Required property \'applies_to\' not present in MetricSpecificThresholdObject JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MetricSpecificThresholdObject object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'default') and self.default is not None:
_dict['default'] = self.default
if hasattr(self, 'recommendation') and self.recommendation is not None:
_dict['recommendation'] = self.recommendation
if hasattr(self, 'applies_to') and self.applies_to is not None:
_dict['applies_to'] = [x.to_dict() for x in self.applies_to]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MetricSpecificThresholdObject object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MetricSpecificThresholdObject') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MetricSpecificThresholdObject') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MetricSpecificThresholdShortObject():
"""
MetricSpecificThresholdShortObject.
:attr float value: value of threshold.
:attr List[ThresholdConditionObject] applies_to:
"""
def __init__(self,
value: float,
applies_to: List['ThresholdConditionObject']) -> None:
"""
Initialize a MetricSpecificThresholdShortObject object.
:param float value: value of threshold.
:param List[ThresholdConditionObject] applies_to:
"""
self.value = value
self.applies_to = applies_to
@classmethod
def from_dict(cls, _dict: Dict) -> 'MetricSpecificThresholdShortObject':
"""Initialize a MetricSpecificThresholdShortObject object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError('Required property \'value\' not present in MetricSpecificThresholdShortObject JSON')
if 'applies_to' in _dict:
args['applies_to'] = [ThresholdConditionObject.from_dict(x) for x in _dict.get('applies_to')]
else:
raise ValueError('Required property \'applies_to\' not present in MetricSpecificThresholdShortObject JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MetricSpecificThresholdShortObject object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'applies_to') and self.applies_to is not None:
_dict['applies_to'] = [x.to_dict() for x in self.applies_to]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MetricSpecificThresholdShortObject object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MetricSpecificThresholdShortObject') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MetricSpecificThresholdShortObject') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class MetricThreshold():
"""
MetricThreshold.
:attr str type:
:attr float default: (optional) default value of threshold.
:attr str default_recommendation: (optional)
:attr List[MetricSpecificThresholdObject] specific_values: (optional)
"""
def __init__(self,
type: str,
*,
default: float = None,
default_recommendation: str = None,
specific_values: List['MetricSpecificThresholdObject'] = None) -> None:
"""
Initialize a MetricThreshold object.
:param str type:
:param float default: (optional) default value of threshold.
:param str default_recommendation: (optional)
:param List[MetricSpecificThresholdObject] specific_values: (optional)
"""
self.type = type
self.default = default
self.default_recommendation = default_recommendation
self.specific_values = specific_values
@classmethod
def from_dict(cls, _dict: Dict) -> 'MetricThreshold':
"""Initialize a MetricThreshold object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in MetricThreshold JSON')
if 'default' in _dict:
args['default'] = _dict.get('default')
if 'default_recommendation' in _dict:
args['default_recommendation'] = _dict.get('default_recommendation')
if 'specific_values' in _dict:
args['specific_values'] = [MetricSpecificThresholdObject.from_dict(x) for x in _dict.get('specific_values')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MetricThreshold object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'default') and self.default is not None:
_dict['default'] = self.default
if hasattr(self, 'default_recommendation') and self.default_recommendation is not None:
_dict['default_recommendation'] = self.default_recommendation
if hasattr(self, 'specific_values') and self.specific_values is not None:
_dict['specific_values'] = [x.to_dict() for x in self.specific_values]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MetricThreshold object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MetricThreshold') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MetricThreshold') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
type.
"""
LOWER_LIMIT = 'lower_limit'
UPPER_LIMIT = 'upper_limit'
class MetricThresholdOverride():
"""
MetricThresholdOverride.
:attr str metric_id:
:attr str type:
:attr float value: (optional) value of the threshold.
:attr List[MetricSpecificThresholdShortObject] specific_values: (optional)
"""
def __init__(self,
metric_id: str,
type: str,
*,
value: float = None,
specific_values: List['MetricSpecificThresholdShortObject'] = None) -> None:
"""
Initialize a MetricThresholdOverride object.
:param str metric_id:
:param str type:
:param float value: (optional) value of the threshold.
:param List[MetricSpecificThresholdShortObject] specific_values: (optional)
"""
self.metric_id = metric_id
self.type = type
self.value = value
self.specific_values = specific_values
@classmethod
def from_dict(cls, _dict: Dict) -> 'MetricThresholdOverride':
"""Initialize a MetricThresholdOverride object from a json dictionary."""
args = {}
if 'metric_id' in _dict:
args['metric_id'] = _dict.get('metric_id')
else:
raise ValueError('Required property \'metric_id\' not present in MetricThresholdOverride JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in MetricThresholdOverride JSON')
if 'value' in _dict:
args['value'] = _dict.get('value')
if 'specific_values' in _dict:
args['specific_values'] = [MetricSpecificThresholdShortObject.from_dict(x) for x in _dict.get('specific_values')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MetricThresholdOverride object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metric_id') and self.metric_id is not None:
_dict['metric_id'] = self.metric_id
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'specific_values') and self.specific_values is not None:
_dict['specific_values'] = [x.to_dict() for x in self.specific_values]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MetricThresholdOverride object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MetricThresholdOverride') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MetricThresholdOverride') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
type.
"""
LOWER_LIMIT = 'lower_limit'
UPPER_LIMIT = 'upper_limit'
class Monitor():
"""
Monitor.
:attr str name: Monitor UI label (must be unique).
:attr str description: (optional) Long monitoring description presented in
monitoring catalog.
:attr List[MonitorMetric] metrics: A list of metric definition.
:attr List[MonitorTag] tags: Available tags.
:attr dict parameters_schema: (optional) JSON schema that will be used to
validate monitoring parameters when enabled.
:attr dict dictionary: (optional) translated resources.
:attr ApplicabilitySelection applies_to: (optional)
:attr str managed_by: (optional)
:attr MonitorInstanceSchedule schedule: (optional) The schedule used to control
how frequently the target is monitored. The maximum frequency is once every 30
minutes.
Defaults to once every hour if not specified.
:attr MonitorInstanceScheduleCollection schedules: (optional) A set of schedules
of online and batch deployment type. If this field is set, schedule field is
ignored.
:attr MonitorRuntime monitor_runtime: (optional) Field to specify if scheduler
should be created or not.
"""
def __init__(self,
name: str,
metrics: List['MonitorMetric'],
tags: List['MonitorTag'],
*,
description: str = None,
parameters_schema: dict = None,
dictionary: dict = None,
applies_to: 'ApplicabilitySelection' = None,
managed_by: str = None,
schedule: 'MonitorInstanceSchedule' = None,
schedules: 'MonitorInstanceScheduleCollection' = None,
monitor_runtime: 'MonitorRuntime' = None) -> None:
"""
Initialize a Monitor object.
:param str name: Monitor UI label (must be unique).
:param List[MonitorMetric] metrics: A list of metric definition.
:param List[MonitorTag] tags: Available tags.
:param str description: (optional) Long monitoring description presented in
monitoring catalog.
:param dict parameters_schema: (optional) JSON schema that will be used to
validate monitoring parameters when enabled.
:param dict dictionary: (optional) translated resources.
:param ApplicabilitySelection applies_to: (optional)
:param str managed_by: (optional)
:param MonitorInstanceSchedule schedule: (optional) The schedule used to
control how frequently the target is monitored. The maximum frequency is
once every 30 minutes.
Defaults to once every hour if not specified.
:param MonitorInstanceScheduleCollection schedules: (optional) A set of
schedules of online and batch deployment type. If this field is set,
schedule field is ignored.
:param MonitorRuntime monitor_runtime: (optional) Field to specify if
scheduler should be created or not.
"""
self.name = name
self.description = description
self.metrics = metrics
self.tags = tags
self.parameters_schema = parameters_schema
self.dictionary = dictionary
self.applies_to = applies_to
self.managed_by = managed_by
self.schedule = schedule
self.schedules = schedules
self.monitor_runtime = monitor_runtime
@classmethod
def from_dict(cls, _dict: Dict) -> 'Monitor':
"""Initialize a Monitor object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in Monitor JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'metrics' in _dict:
args['metrics'] = [MonitorMetric.from_dict(x) for x in _dict.get('metrics')]
else:
raise ValueError('Required property \'metrics\' not present in Monitor JSON')
if 'tags' in _dict:
args['tags'] = [MonitorTag.from_dict(x) for x in _dict.get('tags')]
else:
raise ValueError('Required property \'tags\' not present in Monitor JSON')
if 'parameters_schema' in _dict:
args['parameters_schema'] = _dict.get('parameters_schema')
if 'dictionary' in _dict:
args['dictionary'] = _dict.get('dictionary')
if 'applies_to' in _dict:
args['applies_to'] = ApplicabilitySelection.from_dict(_dict.get('applies_to'))
if 'managed_by' in _dict:
args['managed_by'] = _dict.get('managed_by')
if 'schedule' in _dict:
args['schedule'] = MonitorInstanceSchedule.from_dict(_dict.get('schedule'))
if 'schedules' in _dict:
args['schedules'] = MonitorInstanceScheduleCollection.from_dict(_dict.get('schedules'))
if 'monitor_runtime' in _dict:
args['monitor_runtime'] = MonitorRuntime.from_dict(_dict.get('monitor_runtime'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Monitor object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'metrics') and self.metrics is not None:
_dict['metrics'] = [x.to_dict() for x in self.metrics]
if hasattr(self, 'tags') and self.tags is not None:
_dict['tags'] = [x.to_dict() for x in self.tags]
if hasattr(self, 'parameters_schema') and self.parameters_schema is not None:
_dict['parameters_schema'] = self.parameters_schema
if hasattr(self, 'dictionary') and self.dictionary is not None:
_dict['dictionary'] = self.dictionary
if hasattr(self, 'applies_to') and self.applies_to is not None:
_dict['applies_to'] = self.applies_to.to_dict()
if hasattr(self, 'managed_by') and self.managed_by is not None:
_dict['managed_by'] = self.managed_by
if hasattr(self, 'schedule') and self.schedule is not None:
_dict['schedule'] = self.schedule.to_dict()
if hasattr(self, 'schedules') and self.schedules is not None:
_dict['schedules'] = self.schedules.to_dict()
if hasattr(self, 'monitor_runtime') and self.monitor_runtime is not None:
_dict['monitor_runtime'] = self.monitor_runtime.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Monitor object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Monitor') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Monitor') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorCollections():
"""
MonitorCollections.
:attr List[MonitorDisplayForm] monitor_definitions:
"""
def __init__(self,
monitor_definitions: List['MonitorDisplayForm']) -> None:
"""
Initialize a MonitorCollections object.
:param List[MonitorDisplayForm] monitor_definitions:
"""
self.monitor_definitions = monitor_definitions
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorCollections':
"""Initialize a MonitorCollections object from a json dictionary."""
args = {}
if 'monitor_definitions' in _dict:
args['monitor_definitions'] = [MonitorDisplayForm.from_dict(x) for x in _dict.get('monitor_definitions')]
else:
raise ValueError('Required property \'monitor_definitions\' not present in MonitorCollections JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorCollections object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'monitor_definitions') and self.monitor_definitions is not None:
_dict['monitor_definitions'] = [x.to_dict() for x in self.monitor_definitions]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorCollections object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorCollections') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorCollections') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorDisplayForm():
"""
MonitorDisplayForm.
:attr Metadata metadata:
:attr Monitor entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'Monitor') -> None:
"""
Initialize a MonitorDisplayForm object.
:param Metadata metadata:
:param Monitor entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorDisplayForm':
"""Initialize a MonitorDisplayForm object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in MonitorDisplayForm JSON')
if 'entity' in _dict:
args['entity'] = Monitor.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in MonitorDisplayForm JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorDisplayForm object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorDisplayForm object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorDisplayForm') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorDisplayForm') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorInstanceCollection():
"""
MonitorInstanceCollection.
:attr List[MonitorInstanceResponse] monitor_instances:
"""
def __init__(self,
monitor_instances: List['MonitorInstanceResponse']) -> None:
"""
Initialize a MonitorInstanceCollection object.
:param List[MonitorInstanceResponse] monitor_instances:
"""
self.monitor_instances = monitor_instances
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorInstanceCollection':
"""Initialize a MonitorInstanceCollection object from a json dictionary."""
args = {}
if 'monitor_instances' in _dict:
args['monitor_instances'] = [MonitorInstanceResponse.from_dict(x) for x in _dict.get('monitor_instances')]
else:
raise ValueError('Required property \'monitor_instances\' not present in MonitorInstanceCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorInstanceCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'monitor_instances') and self.monitor_instances is not None:
_dict['monitor_instances'] = [x.to_dict() for x in self.monitor_instances]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorInstanceCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorInstanceCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorInstanceCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorInstanceResponse():
"""
MonitorInstanceResponse.
:attr Metadata metadata: (optional)
:attr MonitorInstanceResponseEntity entity: (optional)
"""
def __init__(self,
*,
metadata: 'Metadata' = None,
entity: 'MonitorInstanceResponseEntity' = None) -> None:
"""
Initialize a MonitorInstanceResponse object.
:param Metadata metadata: (optional)
:param MonitorInstanceResponseEntity entity: (optional)
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorInstanceResponse':
"""Initialize a MonitorInstanceResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
if 'entity' in _dict:
args['entity'] = MonitorInstanceResponseEntity.from_dict(_dict.get('entity'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorInstanceResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorInstanceResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorInstanceResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorInstanceResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorInstanceResponseEntity():
"""
MonitorInstanceResponseEntity.
:attr str data_mart_id:
:attr str monitor_definition_id:
:attr Target target:
:attr dict parameters: (optional) Monitoring parameters consistent with the
`parameters_schema` from the monitor definition.
:attr List[MetricThresholdOverride] thresholds: (optional)
:attr MonitorInstanceSchedule schedule: (optional) The schedule used to control
how frequently the target is monitored. The maximum frequency is once every 30
minutes.
Defaults to once every hour if not specified.
:attr str schedule_id: (optional)
:attr str managed_by: (optional)
:attr RecordsCountSummary unprocessed_records: (optional) Summary about records
count.
:attr MonitorInstanceTotalRecords total_records: (optional) Summary about
records count.
:attr MonitorInstanceResponseEntityStatus status:
"""
def __init__(self,
data_mart_id: str,
monitor_definition_id: str,
target: 'Target',
status: 'MonitorInstanceResponseEntityStatus',
*,
parameters: dict = None,
thresholds: List['MetricThresholdOverride'] = None,
schedule: 'MonitorInstanceSchedule' = None,
schedule_id: str = None,
managed_by: str = None,
unprocessed_records: 'RecordsCountSummary' = None,
total_records: 'MonitorInstanceTotalRecords' = None) -> None:
"""
Initialize a MonitorInstanceResponseEntity object.
:param str data_mart_id:
:param str monitor_definition_id:
:param Target target:
:param MonitorInstanceResponseEntityStatus status:
:param dict parameters: (optional) Monitoring parameters consistent with
the `parameters_schema` from the monitor definition.
:param List[MetricThresholdOverride] thresholds: (optional)
:param MonitorInstanceSchedule schedule: (optional) The schedule used to
control how frequently the target is monitored. The maximum frequency is
once every 30 minutes.
Defaults to once every hour if not specified.
:param str schedule_id: (optional)
:param str managed_by: (optional)
:param RecordsCountSummary unprocessed_records: (optional) Summary about
records count.
:param MonitorInstanceTotalRecords total_records: (optional) Summary about
records count.
"""
self.data_mart_id = data_mart_id
self.monitor_definition_id = monitor_definition_id
self.target = target
self.parameters = parameters
self.thresholds = thresholds
self.schedule = schedule
self.schedule_id = schedule_id
self.managed_by = managed_by
self.unprocessed_records = unprocessed_records
self.total_records = total_records
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorInstanceResponseEntity':
"""Initialize a MonitorInstanceResponseEntity object from a json dictionary."""
args = {}
if 'data_mart_id' in _dict:
args['data_mart_id'] = _dict.get('data_mart_id')
else:
raise ValueError('Required property \'data_mart_id\' not present in MonitorInstanceResponseEntity JSON')
if 'monitor_definition_id' in _dict:
args['monitor_definition_id'] = _dict.get('monitor_definition_id')
else:
raise ValueError('Required property \'monitor_definition_id\' not present in MonitorInstanceResponseEntity JSON')
if 'target' in _dict:
args['target'] = Target.from_dict(_dict.get('target'))
else:
raise ValueError('Required property \'target\' not present in MonitorInstanceResponseEntity JSON')
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
if 'thresholds' in _dict:
args['thresholds'] = [MetricThresholdOverride.from_dict(x) for x in _dict.get('thresholds')]
if 'schedule' in _dict:
args['schedule'] = MonitorInstanceSchedule.from_dict(_dict.get('schedule'))
if 'schedule_id' in _dict:
args['schedule_id'] = _dict.get('schedule_id')
if 'managed_by' in _dict:
args['managed_by'] = _dict.get('managed_by')
if 'unprocessed_records' in _dict:
args['unprocessed_records'] = RecordsCountSummary.from_dict(_dict.get('unprocessed_records'))
if 'total_records' in _dict:
args['total_records'] = MonitorInstanceTotalRecords.from_dict(_dict.get('total_records'))
if 'status' in _dict:
args['status'] = MonitorInstanceResponseEntityStatus.from_dict(_dict.get('status'))
else:
raise ValueError('Required property \'status\' not present in MonitorInstanceResponseEntity JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorInstanceResponseEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'data_mart_id') and self.data_mart_id is not None:
_dict['data_mart_id'] = self.data_mart_id
if hasattr(self, 'monitor_definition_id') and self.monitor_definition_id is not None:
_dict['monitor_definition_id'] = self.monitor_definition_id
if hasattr(self, 'target') and self.target is not None:
_dict['target'] = self.target.to_dict()
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
if hasattr(self, 'thresholds') and self.thresholds is not None:
_dict['thresholds'] = [x.to_dict() for x in self.thresholds]
if hasattr(self, 'schedule') and self.schedule is not None:
_dict['schedule'] = self.schedule.to_dict()
if hasattr(self, 'schedule_id') and self.schedule_id is not None:
_dict['schedule_id'] = self.schedule_id
if hasattr(self, 'managed_by') and self.managed_by is not None:
_dict['managed_by'] = self.managed_by
if hasattr(self, 'unprocessed_records') and self.unprocessed_records is not None:
_dict['unprocessed_records'] = self.unprocessed_records.to_dict()
if hasattr(self, 'total_records') and self.total_records is not None:
_dict['total_records'] = self.total_records.to_dict()
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorInstanceResponseEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorInstanceResponseEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorInstanceResponseEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorInstanceResponseEntityStatus():
"""
MonitorInstanceResponseEntityStatus.
:attr str state:
:attr GenericErrorResponse failure: (optional)
:attr MonitorInstanceResponseEntityStatusActivityStatus activity_status:
(optional)
"""
def __init__(self,
state: str,
*,
failure: 'GenericErrorResponse' = None,
activity_status: 'MonitorInstanceResponseEntityStatusActivityStatus' = None) -> None:
"""
Initialize a MonitorInstanceResponseEntityStatus object.
:param str state:
:param GenericErrorResponse failure: (optional)
:param MonitorInstanceResponseEntityStatusActivityStatus activity_status:
(optional)
"""
self.state = state
self.failure = failure
self.activity_status = activity_status
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorInstanceResponseEntityStatus':
"""Initialize a MonitorInstanceResponseEntityStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
else:
raise ValueError('Required property \'state\' not present in MonitorInstanceResponseEntityStatus JSON')
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
if 'activity_status' in _dict:
args['activity_status'] = MonitorInstanceResponseEntityStatusActivityStatus.from_dict(_dict.get('activity_status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorInstanceResponseEntityStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
if hasattr(self, 'activity_status') and self.activity_status is not None:
_dict['activity_status'] = self.activity_status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorInstanceResponseEntityStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorInstanceResponseEntityStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorInstanceResponseEntityStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
state.
"""
PREPARING = 'preparing'
ACTIVE = 'active'
FAILED = 'failed'
DELETING = 'deleting'
PENDING_DELETE = 'pending_delete'
class MonitorInstanceResponseEntityStatusActivityStatus():
"""
MonitorInstanceResponseEntityStatusActivityStatus.
:attr str id: (optional)
:attr str url: (optional)
"""
def __init__(self,
*,
id: str = None,
url: str = None) -> None:
"""
Initialize a MonitorInstanceResponseEntityStatusActivityStatus object.
:param str id: (optional)
:param str url: (optional)
"""
self.id = id
self.url = url
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorInstanceResponseEntityStatusActivityStatus':
"""Initialize a MonitorInstanceResponseEntityStatusActivityStatus object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
if 'url' in _dict:
args['url'] = _dict.get('url')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorInstanceResponseEntityStatusActivityStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorInstanceResponseEntityStatusActivityStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorInstanceResponseEntityStatusActivityStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorInstanceResponseEntityStatusActivityStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorInstanceSchedule():
"""
The schedule used to control how frequently the target is monitored. The maximum
frequency is once every 30 minutes. Defaults to once every hour if not specified.
:attr int repeat_interval: The interval to monitor the target.
:attr str repeat_unit: The type of interval to monitor the target.
:attr ScheduleStartTime start_time: (optional) Definition of first run time for
scheduled activity; either absolute or relative the the moment of activation.
:attr str repeat_type: (optional) The type of interval to monitor the target.
:attr str status: (optional) The status of scheduler to trigger new evaluation
based on configuration.
"""
def __init__(self,
repeat_interval: int,
repeat_unit: str,
*,
start_time: 'ScheduleStartTime' = None,
repeat_type: str = None,
status: str = None) -> None:
"""
Initialize a MonitorInstanceSchedule object.
:param int repeat_interval: The interval to monitor the target.
:param str repeat_unit: The type of interval to monitor the target.
:param ScheduleStartTime start_time: (optional) Definition of first run
time for scheduled activity; either absolute or relative the the moment of
activation.
:param str repeat_type: (optional) The type of interval to monitor the
target.
:param str status: (optional) The status of scheduler to trigger new
evaluation based on configuration.
"""
self.repeat_interval = repeat_interval
self.repeat_unit = repeat_unit
self.start_time = start_time
self.repeat_type = repeat_type
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorInstanceSchedule':
"""Initialize a MonitorInstanceSchedule object from a json dictionary."""
args = {}
if 'repeat_interval' in _dict:
args['repeat_interval'] = _dict.get('repeat_interval')
else:
raise ValueError('Required property \'repeat_interval\' not present in MonitorInstanceSchedule JSON')
if 'repeat_unit' in _dict:
args['repeat_unit'] = _dict.get('repeat_unit')
else:
raise ValueError('Required property \'repeat_unit\' not present in MonitorInstanceSchedule JSON')
if 'start_time' in _dict:
args['start_time'] = ScheduleStartTime.from_dict(_dict.get('start_time'))
if 'repeat_type' in _dict:
args['repeat_type'] = _dict.get('repeat_type')
if 'status' in _dict:
args['status'] = _dict.get('status')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorInstanceSchedule object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'repeat_interval') and self.repeat_interval is not None:
_dict['repeat_interval'] = self.repeat_interval
if hasattr(self, 'repeat_unit') and self.repeat_unit is not None:
_dict['repeat_unit'] = self.repeat_unit
if hasattr(self, 'start_time') and self.start_time is not None:
_dict['start_time'] = self.start_time.to_dict()
if hasattr(self, 'repeat_type') and self.repeat_type is not None:
_dict['repeat_type'] = self.repeat_type
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorInstanceSchedule object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorInstanceSchedule') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorInstanceSchedule') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class RepeatUnitEnum(str, Enum):
"""
The type of interval to monitor the target.
"""
MINUTE = 'minute'
HOUR = 'hour'
DAY = 'day'
WEEK = 'week'
MONTH = 'month'
YEAR = 'year'
class StatusEnum(str, Enum):
"""
The status of scheduler to trigger new evaluation based on configuration.
"""
ENABLED = 'enabled'
DISABLED = 'disabled'
class MonitorInstanceScheduleCollection():
"""
A set of schedules used to control how frequently the target is monitored for online
and batch deployment type.
:attr MonitorInstanceSchedule online: (optional) Schedule for online deployment
type.
:attr MonitorInstanceSchedule batch: (optional) Schedule for batch deployment
type.
"""
def __init__(self,
*,
online: 'MonitorInstanceSchedule' = None,
batch: 'MonitorInstanceSchedule' = None) -> None:
"""
Initialize a MonitorInstanceScheduleCollection object.
:param MonitorInstanceSchedule online: (optional) Schedule for online
deployment type.
:param MonitorInstanceSchedule batch: (optional) Schedule for batch
deployment type.
"""
self.online = online
self.batch = batch
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorInstanceScheduleCollection':
"""Initialize a MonitorInstanceScheduleCollection object from a json dictionary."""
args = {}
if 'online' in _dict:
args['online'] = MonitorInstanceSchedule.from_dict(_dict.get('online'))
if 'batch' in _dict:
args['batch'] = MonitorInstanceSchedule.from_dict(_dict.get('batch'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorInstanceScheduleCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'online') and self.online is not None:
_dict['online'] = self.online.to_dict()
if hasattr(self, 'batch') and self.batch is not None:
_dict['batch'] = self.batch.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorInstanceScheduleCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorInstanceScheduleCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorInstanceScheduleCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorInstanceTotalRecords():
"""
Summary about records count.
:attr int count:
:attr str type: The type of records time.
:attr datetime timestamp: (optional) timestamp of last consumed record (only for
unprocessed_records).
:attr GenericErrorResponse failure: (optional)
:attr str value: (optional)
"""
def __init__(self,
count: int,
type: str,
*,
timestamp: datetime = None,
failure: 'GenericErrorResponse' = None,
value: str = None) -> None:
"""
Initialize a MonitorInstanceTotalRecords object.
:param int count:
:param str type: The type of records time.
:param datetime timestamp: (optional) timestamp of last consumed record
(only for unprocessed_records).
:param GenericErrorResponse failure: (optional)
:param str value: (optional)
"""
self.count = count
self.type = type
self.timestamp = timestamp
self.failure = failure
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorInstanceTotalRecords':
"""Initialize a MonitorInstanceTotalRecords object from a json dictionary."""
args = {}
if 'count' in _dict:
args['count'] = _dict.get('count')
else:
raise ValueError('Required property \'count\' not present in MonitorInstanceTotalRecords JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in MonitorInstanceTotalRecords JSON')
if 'timestamp' in _dict:
args['timestamp'] = string_to_datetime(_dict.get('timestamp'))
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
if 'value' in _dict:
args['value'] = _dict.get('value')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorInstanceTotalRecords object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'count') and self.count is not None:
_dict['count'] = self.count
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'timestamp') and self.timestamp is not None:
_dict['timestamp'] = datetime_to_string(self.timestamp)
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorInstanceTotalRecords object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorInstanceTotalRecords') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorInstanceTotalRecords') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
The type of records time.
"""
PAYLOAD_LOGGING = 'payload_logging'
FEEDBACK = 'feedback'
class MonitorMeasurementMetric():
"""
Value and limits for the metrics.
:attr str id:
:attr float value:
:attr float lower_limit: (optional)
:attr float upper_limit: (optional)
"""
def __init__(self,
id: str,
value: float,
*,
lower_limit: float = None,
upper_limit: float = None) -> None:
"""
Initialize a MonitorMeasurementMetric object.
:param str id:
:param float value:
:param float lower_limit: (optional)
:param float upper_limit: (optional)
"""
self.id = id
self.value = value
self.lower_limit = lower_limit
self.upper_limit = upper_limit
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMeasurementMetric':
"""Initialize a MonitorMeasurementMetric object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in MonitorMeasurementMetric JSON')
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError('Required property \'value\' not present in MonitorMeasurementMetric JSON')
if 'lower_limit' in _dict:
args['lower_limit'] = _dict.get('lower_limit')
if 'upper_limit' in _dict:
args['upper_limit'] = _dict.get('upper_limit')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMeasurementMetric object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'lower_limit') and self.lower_limit is not None:
_dict['lower_limit'] = self.lower_limit
if hasattr(self, 'upper_limit') and self.upper_limit is not None:
_dict['upper_limit'] = self.upper_limit
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMeasurementMetric object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMeasurementMetric') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMeasurementMetric') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorMeasurementRequest():
"""
MonitorMeasurementRequest.
:attr datetime timestamp:
:attr str run_id: (optional) ID of the monitoring run which produced the
measurement.
:attr List[dict] metrics: Metrics grouped for a single measurement.
:attr List[Source] sources: (optional) The sources of the metric.
:attr str asset_revision: (optional) Revision number of the ML model or function
used by the monitor.
"""
def __init__(self,
timestamp: datetime,
metrics: List[dict],
*,
run_id: str = None,
sources: List['Source'] = None,
asset_revision: str = None) -> None:
"""
Initialize a MonitorMeasurementRequest object.
:param datetime timestamp:
:param List[dict] metrics: Metrics grouped for a single measurement.
:param str run_id: (optional) ID of the monitoring run which produced the
measurement.
:param List[Source] sources: (optional) The sources of the metric.
:param str asset_revision: (optional) Revision number of the ML model or
function used by the monitor.
"""
self.timestamp = timestamp
self.run_id = run_id
self.metrics = metrics
self.sources = sources
self.asset_revision = asset_revision
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMeasurementRequest':
"""Initialize a MonitorMeasurementRequest object from a json dictionary."""
args = {}
if 'timestamp' in _dict:
args['timestamp'] = string_to_datetime(_dict.get('timestamp'))
else:
raise ValueError('Required property \'timestamp\' not present in MonitorMeasurementRequest JSON')
if 'run_id' in _dict:
args['run_id'] = _dict.get('run_id')
if 'metrics' in _dict:
args['metrics'] = _dict.get('metrics')
else:
raise ValueError('Required property \'metrics\' not present in MonitorMeasurementRequest JSON')
if 'sources' in _dict:
args['sources'] = [Source.from_dict(x) for x in _dict.get('sources')]
if 'asset_revision' in _dict:
args['asset_revision'] = _dict.get('asset_revision')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMeasurementRequest object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'timestamp') and self.timestamp is not None:
_dict['timestamp'] = datetime_to_string(self.timestamp)
if hasattr(self, 'run_id') and self.run_id is not None:
_dict['run_id'] = self.run_id
if hasattr(self, 'metrics') and self.metrics is not None:
_dict['metrics'] = self.metrics
if hasattr(self, 'sources') and self.sources is not None:
_dict['sources'] = [x.to_dict() for x in self.sources]
if hasattr(self, 'asset_revision') and self.asset_revision is not None:
_dict['asset_revision'] = self.asset_revision
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMeasurementRequest object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMeasurementRequest') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMeasurementRequest') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorMeasurementResponse():
"""
MonitorMeasurementResponse.
:attr Metadata metadata:
:attr MonitorMeasurementResponseEntity entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'MonitorMeasurementResponseEntity') -> None:
"""
Initialize a MonitorMeasurementResponse object.
:param Metadata metadata:
:param MonitorMeasurementResponseEntity entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMeasurementResponse':
"""Initialize a MonitorMeasurementResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in MonitorMeasurementResponse JSON')
if 'entity' in _dict:
args['entity'] = MonitorMeasurementResponseEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in MonitorMeasurementResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMeasurementResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMeasurementResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMeasurementResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMeasurementResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorMeasurementResponseCollection():
"""
MonitorMeasurementResponseCollection.
:attr datetime start: (optional) Beginning of the time range.
:attr datetime end: (optional) End of the time range.
:attr int limit: (optional) Maximum number of measurements returned.
:attr int offset: (optional) Offset of measurements returned.
:attr List[MonitorMeasurementResponseCollectionMeasurementsItem] measurements:
"""
def __init__(self,
measurements: List['MonitorMeasurementResponseCollectionMeasurementsItem'],
*,
start: datetime = None,
end: datetime = None,
limit: int = None,
offset: int = None) -> None:
"""
Initialize a MonitorMeasurementResponseCollection object.
:param List[MonitorMeasurementResponseCollectionMeasurementsItem]
measurements:
:param datetime start: (optional) Beginning of the time range.
:param datetime end: (optional) End of the time range.
:param int limit: (optional) Maximum number of measurements returned.
:param int offset: (optional) Offset of measurements returned.
"""
self.start = start
self.end = end
self.limit = limit
self.offset = offset
self.measurements = measurements
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMeasurementResponseCollection':
"""Initialize a MonitorMeasurementResponseCollection object from a json dictionary."""
args = {}
if 'start' in _dict:
args['start'] = string_to_datetime(_dict.get('start'))
if 'end' in _dict:
args['end'] = string_to_datetime(_dict.get('end'))
if 'limit' in _dict:
args['limit'] = _dict.get('limit')
if 'offset' in _dict:
args['offset'] = _dict.get('offset')
if 'measurements' in _dict:
args['measurements'] = [MonitorMeasurementResponseCollectionMeasurementsItem.from_dict(x) for x in _dict.get('measurements')]
else:
raise ValueError('Required property \'measurements\' not present in MonitorMeasurementResponseCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMeasurementResponseCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'start') and self.start is not None:
_dict['start'] = datetime_to_string(self.start)
if hasattr(self, 'end') and self.end is not None:
_dict['end'] = datetime_to_string(self.end)
if hasattr(self, 'limit') and self.limit is not None:
_dict['limit'] = self.limit
if hasattr(self, 'offset') and self.offset is not None:
_dict['offset'] = self.offset
if hasattr(self, 'measurements') and self.measurements is not None:
_dict['measurements'] = [x.to_dict() for x in self.measurements]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMeasurementResponseCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMeasurementResponseCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMeasurementResponseCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorMeasurementResponseCollectionMeasurementsItem():
"""
MonitorMeasurementResponseCollectionMeasurementsItem.
:attr Metadata metadata:
:attr MeasurementEntity entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'MeasurementEntity') -> None:
"""
Initialize a MonitorMeasurementResponseCollectionMeasurementsItem object.
:param Metadata metadata:
:param MeasurementEntity entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMeasurementResponseCollectionMeasurementsItem':
"""Initialize a MonitorMeasurementResponseCollectionMeasurementsItem object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in MonitorMeasurementResponseCollectionMeasurementsItem JSON')
if 'entity' in _dict:
args['entity'] = MeasurementEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in MonitorMeasurementResponseCollectionMeasurementsItem JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMeasurementResponseCollectionMeasurementsItem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMeasurementResponseCollectionMeasurementsItem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMeasurementResponseCollectionMeasurementsItem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMeasurementResponseCollectionMeasurementsItem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorMeasurementResponseEntity():
"""
MonitorMeasurementResponseEntity.
:attr datetime timestamp:
:attr str run_id: (optional) ID of the monitoring run which produced the
measurement.
:attr List[MonitorMeasurementValue] values: Metrics grouped for a single
measurement.
:attr int issue_count: Number of the metrics with issues, which exceeded limits.
:attr str asset_revision: (optional) Revision number of the ML model or function
used by the monitor.
:attr Target target: (optional)
:attr str monitor_instance_id: (optional)
:attr str monitor_definition_id: (optional)
:attr List[Source] sources: (optional) The sources of the metric.
"""
def __init__(self,
timestamp: datetime,
values: List['MonitorMeasurementValue'],
issue_count: int,
*,
run_id: str = None,
asset_revision: str = None,
target: 'Target' = None,
monitor_instance_id: str = None,
monitor_definition_id: str = None,
sources: List['Source'] = None) -> None:
"""
Initialize a MonitorMeasurementResponseEntity object.
:param datetime timestamp:
:param List[MonitorMeasurementValue] values: Metrics grouped for a single
measurement.
:param int issue_count: Number of the metrics with issues, which exceeded
limits.
:param str run_id: (optional) ID of the monitoring run which produced the
measurement.
:param str asset_revision: (optional) Revision number of the ML model or
function used by the monitor.
:param Target target: (optional)
:param str monitor_instance_id: (optional)
:param str monitor_definition_id: (optional)
:param List[Source] sources: (optional) The sources of the metric.
"""
self.timestamp = timestamp
self.run_id = run_id
self.values = values
self.issue_count = issue_count
self.asset_revision = asset_revision
self.target = target
self.monitor_instance_id = monitor_instance_id
self.monitor_definition_id = monitor_definition_id
self.sources = sources
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMeasurementResponseEntity':
"""Initialize a MonitorMeasurementResponseEntity object from a json dictionary."""
args = {}
if 'timestamp' in _dict:
args['timestamp'] = string_to_datetime(_dict.get('timestamp'))
else:
raise ValueError('Required property \'timestamp\' not present in MonitorMeasurementResponseEntity JSON')
if 'run_id' in _dict:
args['run_id'] = _dict.get('run_id')
if 'values' in _dict:
args['values'] = [MonitorMeasurementValue.from_dict(x) for x in _dict.get('values')]
else:
raise ValueError('Required property \'values\' not present in MonitorMeasurementResponseEntity JSON')
if 'issue_count' in _dict:
args['issue_count'] = _dict.get('issue_count')
else:
raise ValueError('Required property \'issue_count\' not present in MonitorMeasurementResponseEntity JSON')
if 'asset_revision' in _dict:
args['asset_revision'] = _dict.get('asset_revision')
if 'target' in _dict:
args['target'] = Target.from_dict(_dict.get('target'))
if 'monitor_instance_id' in _dict:
args['monitor_instance_id'] = _dict.get('monitor_instance_id')
if 'monitor_definition_id' in _dict:
args['monitor_definition_id'] = _dict.get('monitor_definition_id')
if 'sources' in _dict:
args['sources'] = [Source.from_dict(x) for x in _dict.get('sources')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMeasurementResponseEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'timestamp') and self.timestamp is not None:
_dict['timestamp'] = datetime_to_string(self.timestamp)
if hasattr(self, 'run_id') and self.run_id is not None:
_dict['run_id'] = self.run_id
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = [x.to_dict() for x in self.values]
if hasattr(self, 'issue_count') and self.issue_count is not None:
_dict['issue_count'] = self.issue_count
if hasattr(self, 'asset_revision') and self.asset_revision is not None:
_dict['asset_revision'] = self.asset_revision
if hasattr(self, 'target') and self.target is not None:
_dict['target'] = self.target.to_dict()
if hasattr(self, 'monitor_instance_id') and self.monitor_instance_id is not None:
_dict['monitor_instance_id'] = self.monitor_instance_id
if hasattr(self, 'monitor_definition_id') and self.monitor_definition_id is not None:
_dict['monitor_definition_id'] = self.monitor_definition_id
if hasattr(self, 'sources') and self.sources is not None:
_dict['sources'] = [x.to_dict() for x in self.sources]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMeasurementResponseEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMeasurementResponseEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMeasurementResponseEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorMeasurementTag():
"""
Tag related to the metrics.
:attr str id:
:attr str value:
"""
def __init__(self,
id: str,
value: str) -> None:
"""
Initialize a MonitorMeasurementTag object.
:param str id:
:param str value:
"""
self.id = id
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMeasurementTag':
"""Initialize a MonitorMeasurementTag object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in MonitorMeasurementTag JSON')
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError('Required property \'value\' not present in MonitorMeasurementTag JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMeasurementTag object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMeasurementTag object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMeasurementTag') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMeasurementTag') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorMeasurementValue():
"""
Measurement metrics and tags.
:attr List[MonitorMeasurementMetric] metrics: Metrics related to the
measurement.
:attr List[MonitorMeasurementTag] tags: Tags related to the measurement.
"""
def __init__(self,
metrics: List['MonitorMeasurementMetric'],
tags: List['MonitorMeasurementTag']) -> None:
"""
Initialize a MonitorMeasurementValue object.
:param List[MonitorMeasurementMetric] metrics: Metrics related to the
measurement.
:param List[MonitorMeasurementTag] tags: Tags related to the measurement.
"""
self.metrics = metrics
self.tags = tags
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMeasurementValue':
"""Initialize a MonitorMeasurementValue object from a json dictionary."""
args = {}
if 'metrics' in _dict:
args['metrics'] = [MonitorMeasurementMetric.from_dict(x) for x in _dict.get('metrics')]
else:
raise ValueError('Required property \'metrics\' not present in MonitorMeasurementValue JSON')
if 'tags' in _dict:
args['tags'] = [MonitorMeasurementTag.from_dict(x) for x in _dict.get('tags')]
else:
raise ValueError('Required property \'tags\' not present in MonitorMeasurementValue JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMeasurementValue object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metrics') and self.metrics is not None:
_dict['metrics'] = [x.to_dict() for x in self.metrics]
if hasattr(self, 'tags') and self.tags is not None:
_dict['tags'] = [x.to_dict() for x in self.tags]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMeasurementValue object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMeasurementValue') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMeasurementValue') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorMetric():
"""
MonitorMetric.
:attr str name: unique name used by UI instead of id (must be unique in scope of
the monitor definition across both metrics and tags).
:attr str description: (optional) Description of the metrics.
:attr List[MetricThreshold] thresholds: (optional)
:attr bool required: (optional)
:attr ApplicabilitySelection applies_to: (optional)
:attr str expected_direction: (optional) the indicator specifying the expected
direction of the monotonic metric values.
:attr str default_aggregation: (optional)
:attr str id:
"""
def __init__(self,
name: str,
id: str,
*,
description: str = None,
thresholds: List['MetricThreshold'] = None,
required: bool = None,
applies_to: 'ApplicabilitySelection' = None,
expected_direction: str = None,
default_aggregation: str = None) -> None:
"""
Initialize a MonitorMetric object.
:param str name: unique name used by UI instead of id (must be unique in
scope of the monitor definition across both metrics and tags).
:param str id:
:param str description: (optional) Description of the metrics.
:param List[MetricThreshold] thresholds: (optional)
:param bool required: (optional)
:param ApplicabilitySelection applies_to: (optional)
:param str expected_direction: (optional) the indicator specifying the
expected direction of the monotonic metric values.
:param str default_aggregation: (optional)
"""
self.name = name
self.description = description
self.thresholds = thresholds
self.required = required
self.applies_to = applies_to
self.expected_direction = expected_direction
self.default_aggregation = default_aggregation
self.id = id
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMetric':
"""Initialize a MonitorMetric object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in MonitorMetric JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'thresholds' in _dict:
args['thresholds'] = [MetricThreshold.from_dict(x) for x in _dict.get('thresholds')]
if 'required' in _dict:
args['required'] = _dict.get('required')
if 'applies_to' in _dict:
args['applies_to'] = ApplicabilitySelection.from_dict(_dict.get('applies_to'))
if 'expected_direction' in _dict:
args['expected_direction'] = _dict.get('expected_direction')
if 'default_aggregation' in _dict:
args['default_aggregation'] = _dict.get('default_aggregation')
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in MonitorMetric JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMetric object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'thresholds') and self.thresholds is not None:
_dict['thresholds'] = [x.to_dict() for x in self.thresholds]
if hasattr(self, 'required') and self.required is not None:
_dict['required'] = self.required
if hasattr(self, 'applies_to') and self.applies_to is not None:
_dict['applies_to'] = self.applies_to.to_dict()
if hasattr(self, 'expected_direction') and self.expected_direction is not None:
_dict['expected_direction'] = self.expected_direction
if hasattr(self, 'default_aggregation') and self.default_aggregation is not None:
_dict['default_aggregation'] = self.default_aggregation
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMetric object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMetric') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMetric') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ExpectedDirectionEnum(str, Enum):
"""
the indicator specifying the expected direction of the monotonic metric values.
"""
INCREASING = 'increasing'
DECREASING = 'decreasing'
UNKNOWN = 'unknown'
class DefaultAggregationEnum(str, Enum):
"""
default_aggregation.
"""
LAST = 'last'
FIRST = 'first'
MIN = 'min'
MAX = 'max'
SUM = 'sum'
COUNT = 'count'
AVG = 'avg'
MEDIAN = 'median'
STDDEV = 'stddev'
class MonitorMetricRequest():
"""
MonitorMetricRequest.
:attr str name: unique name used by UI instead of id (must be unique in scope of
the monitor definition across both metrics and tags).
:attr str description: (optional) Description of the metrics.
:attr List[MetricThreshold] thresholds: (optional)
:attr bool required: (optional)
:attr ApplicabilitySelection applies_to: (optional)
:attr str expected_direction: (optional) the indicator specifying the expected
direction of the monotonic metric values.
:attr str default_aggregation: (optional)
"""
def __init__(self,
name: str,
*,
description: str = None,
thresholds: List['MetricThreshold'] = None,
required: bool = None,
applies_to: 'ApplicabilitySelection' = None,
expected_direction: str = None,
default_aggregation: str = None) -> None:
"""
Initialize a MonitorMetricRequest object.
:param str name: unique name used by UI instead of id (must be unique in
scope of the monitor definition across both metrics and tags).
:param str description: (optional) Description of the metrics.
:param List[MetricThreshold] thresholds: (optional)
:param bool required: (optional)
:param ApplicabilitySelection applies_to: (optional)
:param str expected_direction: (optional) the indicator specifying the
expected direction of the monotonic metric values.
:param str default_aggregation: (optional)
"""
self.name = name
self.description = description
self.thresholds = thresholds
self.required = required
self.applies_to = applies_to
self.expected_direction = expected_direction
self.default_aggregation = default_aggregation
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorMetricRequest':
"""Initialize a MonitorMetricRequest object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in MonitorMetricRequest JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'thresholds' in _dict:
args['thresholds'] = [MetricThreshold.from_dict(x) for x in _dict.get('thresholds')]
if 'required' in _dict:
args['required'] = _dict.get('required')
if 'applies_to' in _dict:
args['applies_to'] = ApplicabilitySelection.from_dict(_dict.get('applies_to'))
if 'expected_direction' in _dict:
args['expected_direction'] = _dict.get('expected_direction')
if 'default_aggregation' in _dict:
args['default_aggregation'] = _dict.get('default_aggregation')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorMetricRequest object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'thresholds') and self.thresholds is not None:
_dict['thresholds'] = [x.to_dict() for x in self.thresholds]
if hasattr(self, 'required') and self.required is not None:
_dict['required'] = self.required
if hasattr(self, 'applies_to') and self.applies_to is not None:
_dict['applies_to'] = self.applies_to.to_dict()
if hasattr(self, 'expected_direction') and self.expected_direction is not None:
_dict['expected_direction'] = self.expected_direction
if hasattr(self, 'default_aggregation') and self.default_aggregation is not None:
_dict['default_aggregation'] = self.default_aggregation
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorMetricRequest object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorMetricRequest') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorMetricRequest') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ExpectedDirectionEnum(str, Enum):
"""
the indicator specifying the expected direction of the monotonic metric values.
"""
INCREASING = 'increasing'
DECREASING = 'decreasing'
UNKNOWN = 'unknown'
class DefaultAggregationEnum(str, Enum):
"""
default_aggregation.
"""
LAST = 'last'
FIRST = 'first'
MIN = 'min'
MAX = 'max'
SUM = 'sum'
COUNT = 'count'
AVG = 'avg'
MEDIAN = 'median'
STDDEV = 'stddev'
class MonitorRuntime():
"""
Field to specify if scheduler should be created or not.
:attr str type: when either `service` or `custom_metrics_provider` is specified,
scheduler gets created. `service` is for OOTB, `custom_metrics_provider` is for
custom metric integrated.
"""
def __init__(self,
type: str) -> None:
"""
Initialize a MonitorRuntime object.
:param str type: when either `service` or `custom_metrics_provider` is
specified, scheduler gets created. `service` is for OOTB,
`custom_metrics_provider` is for custom metric integrated.
"""
self.type = type
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorRuntime':
"""Initialize a MonitorRuntime object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in MonitorRuntime JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorRuntime object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorRuntime object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorRuntime') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorRuntime') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
when either `service` or `custom_metrics_provider` is specified, scheduler gets
created. `service` is for OOTB, `custom_metrics_provider` is for custom metric
integrated.
"""
SERVICE = 'service'
CUSTOM_METRICS_PROVIDER = 'custom_metrics_provider'
NONE = 'none'
class MonitorTag():
"""
MonitorTag.
:attr str name: unique name used by UI instead of id (must be unique in scope of
the monitor definition across both metrics and tags).
:attr str description: (optional) Description of the tag.
:attr bool required: (optional)
:attr str id:
"""
def __init__(self,
name: str,
id: str,
*,
description: str = None,
required: bool = None) -> None:
"""
Initialize a MonitorTag object.
:param str name: unique name used by UI instead of id (must be unique in
scope of the monitor definition across both metrics and tags).
:param str id:
:param str description: (optional) Description of the tag.
:param bool required: (optional)
"""
self.name = name
self.description = description
self.required = required
self.id = id
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorTag':
"""Initialize a MonitorTag object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in MonitorTag JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'required' in _dict:
args['required'] = _dict.get('required')
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in MonitorTag JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorTag object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'required') and self.required is not None:
_dict['required'] = self.required
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorTag object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorTag') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorTag') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitorTagRequest():
"""
MonitorTagRequest.
:attr str name: unique name used by UI instead of id (must be unique in scope of
the monitor definition across both metrics and tags).
:attr str description: (optional) Description of the tag.
:attr bool required: (optional)
"""
def __init__(self,
name: str,
*,
description: str = None,
required: bool = None) -> None:
"""
Initialize a MonitorTagRequest object.
:param str name: unique name used by UI instead of id (must be unique in
scope of the monitor definition across both metrics and tags).
:param str description: (optional) Description of the tag.
:param bool required: (optional)
"""
self.name = name
self.description = description
self.required = required
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitorTagRequest':
"""Initialize a MonitorTagRequest object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in MonitorTagRequest JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'required' in _dict:
args['required'] = _dict.get('required')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitorTagRequest object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'required') and self.required is not None:
_dict['required'] = self.required
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitorTagRequest object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitorTagRequest') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitorTagRequest') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitoringRun():
"""
MonitoringRun.
:attr Metadata metadata:
:attr MonitoringRunEntity entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'MonitoringRunEntity') -> None:
"""
Initialize a MonitoringRun object.
:param Metadata metadata:
:param MonitoringRunEntity entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitoringRun':
"""Initialize a MonitoringRun object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in MonitoringRun JSON')
if 'entity' in _dict:
args['entity'] = MonitoringRunEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in MonitoringRun JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitoringRun object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitoringRun object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitoringRun') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitoringRun') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitoringRunCollection():
"""
A page from a collection of monitoring runs.
:attr List[MonitoringRun] runs: A page from a collection of monitoring runs.
:attr CollectionUrlModel first: (optional)
:attr CollectionUrlModel prev: (optional)
:attr CollectionUrlModel next: (optional)
:attr CollectionUrlModel last: (optional)
:attr int limit: (optional) The number of monitoring runs requested to be
returned.
:attr int total_count: (optional) The total number of monitoring runs available.
"""
def __init__(self,
runs: List['MonitoringRun'],
*,
first: 'CollectionUrlModel' = None,
prev: 'CollectionUrlModel' = None,
next: 'CollectionUrlModel' = None,
last: 'CollectionUrlModel' = None,
limit: int = None,
total_count: int = None) -> None:
"""
Initialize a MonitoringRunCollection object.
:param List[MonitoringRun] runs: A page from a collection of monitoring
runs.
:param CollectionUrlModel first: (optional)
:param CollectionUrlModel prev: (optional)
:param CollectionUrlModel next: (optional)
:param CollectionUrlModel last: (optional)
:param int limit: (optional) The number of monitoring runs requested to be
returned.
:param int total_count: (optional) The total number of monitoring runs
available.
"""
self.runs = runs
self.first = first
self.prev = prev
self.next = next
self.last = last
self.limit = limit
self.total_count = total_count
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitoringRunCollection':
"""Initialize a MonitoringRunCollection object from a json dictionary."""
args = {}
if 'runs' in _dict:
args['runs'] = [MonitoringRun.from_dict(x) for x in _dict.get('runs')]
else:
raise ValueError('Required property \'runs\' not present in MonitoringRunCollection JSON')
if 'first' in _dict:
args['first'] = CollectionUrlModel.from_dict(_dict.get('first'))
if 'prev' in _dict:
args['prev'] = CollectionUrlModel.from_dict(_dict.get('prev'))
if 'next' in _dict:
args['next'] = CollectionUrlModel.from_dict(_dict.get('next'))
if 'last' in _dict:
args['last'] = CollectionUrlModel.from_dict(_dict.get('last'))
if 'limit' in _dict:
args['limit'] = _dict.get('limit')
if 'total_count' in _dict:
args['total_count'] = _dict.get('total_count')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitoringRunCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'runs') and self.runs is not None:
_dict['runs'] = [x.to_dict() for x in self.runs]
if hasattr(self, 'first') and self.first is not None:
_dict['first'] = self.first.to_dict()
if hasattr(self, 'prev') and self.prev is not None:
_dict['prev'] = self.prev.to_dict()
if hasattr(self, 'next') and self.next is not None:
_dict['next'] = self.next.to_dict()
if hasattr(self, 'last') and self.last is not None:
_dict['last'] = self.last.to_dict()
if hasattr(self, 'limit') and self.limit is not None:
_dict['limit'] = self.limit
if hasattr(self, 'total_count') and self.total_count is not None:
_dict['total_count'] = self.total_count
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitoringRunCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitoringRunCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitoringRunCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitoringRunEntity():
"""
MonitoringRunEntity.
:attr str triggered_by: (optional) An identifier representing the source that
triggered the run request (optional). One of: event, scheduler, user, webhook.
:attr dict parameters: (optional) Monitoring parameters consistent with the
`parameters_schema` from the monitor definition.
:attr MonitoringRunStatus status: The status information for the monitoring run.
"""
def __init__(self,
status: 'MonitoringRunStatus',
*,
triggered_by: str = None,
parameters: dict = None) -> None:
"""
Initialize a MonitoringRunEntity object.
:param MonitoringRunStatus status: The status information for the
monitoring run.
:param str triggered_by: (optional) An identifier representing the source
that triggered the run request (optional). One of: event, scheduler, user,
webhook.
:param dict parameters: (optional) Monitoring parameters consistent with
the `parameters_schema` from the monitor definition.
"""
self.triggered_by = triggered_by
self.parameters = parameters
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitoringRunEntity':
"""Initialize a MonitoringRunEntity object from a json dictionary."""
args = {}
if 'triggered_by' in _dict:
args['triggered_by'] = _dict.get('triggered_by')
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
if 'status' in _dict:
args['status'] = MonitoringRunStatus.from_dict(_dict.get('status'))
else:
raise ValueError('Required property \'status\' not present in MonitoringRunEntity JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitoringRunEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'triggered_by') and self.triggered_by is not None:
_dict['triggered_by'] = self.triggered_by
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitoringRunEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitoringRunEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitoringRunEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TriggeredByEnum(str, Enum):
"""
An identifier representing the source that triggered the run request (optional).
One of: event, scheduler, user, webhook.
"""
EVENT = 'event'
SCHEDULER = 'scheduler'
USER = 'user'
WEBHOOK = 'webhook'
BKPI_MANAGER = 'bkpi_manager'
class MonitoringRunOperator():
"""
MonitoringRunOperator.
:attr str id: (optional)
:attr MonitoringRunOperatorStatus status: (optional)
:attr dict result: (optional) Result produced by the operator, if any.
"""
def __init__(self,
*,
id: str = None,
status: 'MonitoringRunOperatorStatus' = None,
result: dict = None) -> None:
"""
Initialize a MonitoringRunOperator object.
:param str id: (optional)
:param MonitoringRunOperatorStatus status: (optional)
:param dict result: (optional) Result produced by the operator, if any.
"""
self.id = id
self.status = status
self.result = result
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitoringRunOperator':
"""Initialize a MonitoringRunOperator object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
if 'status' in _dict:
args['status'] = MonitoringRunOperatorStatus.from_dict(_dict.get('status'))
if 'result' in _dict:
args['result'] = _dict.get('result')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitoringRunOperator object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
if hasattr(self, 'result') and self.result is not None:
_dict['result'] = self.result
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitoringRunOperator object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitoringRunOperator') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitoringRunOperator') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MonitoringRunOperatorStatus():
"""
MonitoringRunOperatorStatus.
:attr str state: (optional)
:attr datetime started_at: (optional)
:attr datetime completed_at: (optional)
:attr GenericErrorResponse failure: (optional)
"""
def __init__(self,
*,
state: str = None,
started_at: datetime = None,
completed_at: datetime = None,
failure: 'GenericErrorResponse' = None) -> None:
"""
Initialize a MonitoringRunOperatorStatus object.
:param str state: (optional)
:param datetime started_at: (optional)
:param datetime completed_at: (optional)
:param GenericErrorResponse failure: (optional)
"""
self.state = state
self.started_at = started_at
self.completed_at = completed_at
self.failure = failure
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitoringRunOperatorStatus':
"""Initialize a MonitoringRunOperatorStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
if 'started_at' in _dict:
args['started_at'] = string_to_datetime(_dict.get('started_at'))
if 'completed_at' in _dict:
args['completed_at'] = string_to_datetime(_dict.get('completed_at'))
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitoringRunOperatorStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
if hasattr(self, 'started_at') and self.started_at is not None:
_dict['started_at'] = datetime_to_string(self.started_at)
if hasattr(self, 'completed_at') and self.completed_at is not None:
_dict['completed_at'] = datetime_to_string(self.completed_at)
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitoringRunOperatorStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitoringRunOperatorStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitoringRunOperatorStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
state.
"""
QUEUED = 'queued'
RUNNING = 'running'
FINISHED = 'finished'
ERROR = 'error'
class MonitoringRunStatus():
"""
The status information for the monitoring run.
:attr str state: (optional)
:attr datetime queued_at: (optional) The timestamp when the monitoring run was
queued to be run (in the format YYYY-MM-DDTHH:mm:ssZ or
YYYY-MM-DDTHH:mm:ss.sssZ, matching the date-time format as specified by RFC
3339).
:attr datetime started_at: (optional) The timestamp when the monitoring run was
started running (in the format YYYY-MM-DDTHH:mm:ssZ or YYYY-MM-DDTHH:mm:ss.sssZ,
matching the date-time format as specified by RFC 3339).
:attr datetime updated_at: (optional) The timestamp when the monitoring run was
last updated (in the format YYYY-MM-DDTHH:mm:ssZ or YYYY-MM-DDTHH:mm:ss.sssZ,
matching the date-time format as specified by RFC 3339).
:attr datetime completed_at: (optional) The timestamp when the monitoring run
finished running (in the format YYYY-MM-DDTHH:mm:ssZ or
YYYY-MM-DDTHH:mm:ss.sssZ, matching the date-time format as specified by RFC
3339).
:attr str message: (optional) Any message associated with the monitoring run.
:attr GenericErrorResponse failure: (optional)
:attr List[MonitoringRunOperator] operators: (optional)
"""
def __init__(self,
*,
state: str = None,
queued_at: datetime = None,
started_at: datetime = None,
updated_at: datetime = None,
completed_at: datetime = None,
message: str = None,
failure: 'GenericErrorResponse' = None,
operators: List['MonitoringRunOperator'] = None) -> None:
"""
Initialize a MonitoringRunStatus object.
:param str state: (optional)
:param datetime queued_at: (optional) The timestamp when the monitoring run
was queued to be run (in the format YYYY-MM-DDTHH:mm:ssZ or
YYYY-MM-DDTHH:mm:ss.sssZ, matching the date-time format as specified by RFC
3339).
:param datetime started_at: (optional) The timestamp when the monitoring
run was started running (in the format YYYY-MM-DDTHH:mm:ssZ or
YYYY-MM-DDTHH:mm:ss.sssZ, matching the date-time format as specified by RFC
3339).
:param datetime updated_at: (optional) The timestamp when the monitoring
run was last updated (in the format YYYY-MM-DDTHH:mm:ssZ or
YYYY-MM-DDTHH:mm:ss.sssZ, matching the date-time format as specified by RFC
3339).
:param datetime completed_at: (optional) The timestamp when the monitoring
run finished running (in the format YYYY-MM-DDTHH:mm:ssZ or
YYYY-MM-DDTHH:mm:ss.sssZ, matching the date-time format as specified by RFC
3339).
:param str message: (optional) Any message associated with the monitoring
run.
:param GenericErrorResponse failure: (optional)
:param List[MonitoringRunOperator] operators: (optional)
"""
self.state = state
self.queued_at = queued_at
self.started_at = started_at
self.updated_at = updated_at
self.completed_at = completed_at
self.message = message
self.failure = failure
self.operators = operators
@classmethod
def from_dict(cls, _dict: Dict) -> 'MonitoringRunStatus':
"""Initialize a MonitoringRunStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
if 'queued_at' in _dict:
args['queued_at'] = string_to_datetime(_dict.get('queued_at'))
if 'started_at' in _dict:
args['started_at'] = string_to_datetime(_dict.get('started_at'))
if 'updated_at' in _dict:
args['updated_at'] = string_to_datetime(_dict.get('updated_at'))
if 'completed_at' in _dict:
args['completed_at'] = string_to_datetime(_dict.get('completed_at'))
if 'message' in _dict:
args['message'] = _dict.get('message')
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
if 'operators' in _dict:
args['operators'] = [MonitoringRunOperator.from_dict(x) for x in _dict.get('operators')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MonitoringRunStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
if hasattr(self, 'queued_at') and self.queued_at is not None:
_dict['queued_at'] = datetime_to_string(self.queued_at)
if hasattr(self, 'started_at') and self.started_at is not None:
_dict['started_at'] = datetime_to_string(self.started_at)
if hasattr(self, 'updated_at') and self.updated_at is not None:
_dict['updated_at'] = datetime_to_string(self.updated_at)
if hasattr(self, 'completed_at') and self.completed_at is not None:
_dict['completed_at'] = datetime_to_string(self.completed_at)
if hasattr(self, 'message') and self.message is not None:
_dict['message'] = self.message
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
if hasattr(self, 'operators') and self.operators is not None:
_dict['operators'] = [x.to_dict() for x in self.operators]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MonitoringRunStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MonitoringRunStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MonitoringRunStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
state.
"""
QUEUED = 'queued'
RUNNING = 'running'
FINISHED = 'finished'
ERROR = 'error'
class MrmGetRiskEvaluationStatus():
"""
MrmGetRiskEvaluationStatus.
:attr str subscription_id: (optional)
:attr str status: (optional)
:attr str localized_status: (optional)
"""
def __init__(self,
*,
subscription_id: str = None,
status: str = None,
localized_status: str = None) -> None:
"""
Initialize a MrmGetRiskEvaluationStatus object.
:param str subscription_id: (optional)
:param str status: (optional)
:param str localized_status: (optional)
"""
self.subscription_id = subscription_id
self.status = status
self.localized_status = localized_status
@classmethod
def from_dict(cls, _dict: Dict) -> 'MrmGetRiskEvaluationStatus':
"""Initialize a MrmGetRiskEvaluationStatus object from a json dictionary."""
args = {}
if 'subscription_id' in _dict:
args['subscription_id'] = _dict.get('subscription_id')
if 'status' in _dict:
args['status'] = _dict.get('status')
if 'localized_status' in _dict:
args['localized_status'] = _dict.get('localized_status')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MrmGetRiskEvaluationStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'subscription_id') and self.subscription_id is not None:
_dict['subscription_id'] = self.subscription_id
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status
if hasattr(self, 'localized_status') and self.localized_status is not None:
_dict['localized_status'] = self.localized_status
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MrmGetRiskEvaluationStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MrmGetRiskEvaluationStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MrmGetRiskEvaluationStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MrmGetRiskEvaluationStatusEntity():
"""
MrmGetRiskEvaluationStatusEntity.
:attr List[MrmGetRiskEvaluationStatus] risk_evaluation_status: (optional)
"""
def __init__(self,
*,
risk_evaluation_status: List['MrmGetRiskEvaluationStatus'] = None) -> None:
"""
Initialize a MrmGetRiskEvaluationStatusEntity object.
:param List[MrmGetRiskEvaluationStatus] risk_evaluation_status: (optional)
"""
self.risk_evaluation_status = risk_evaluation_status
@classmethod
def from_dict(cls, _dict: Dict) -> 'MrmGetRiskEvaluationStatusEntity':
"""Initialize a MrmGetRiskEvaluationStatusEntity object from a json dictionary."""
args = {}
if 'risk_evaluation_status' in _dict:
args['risk_evaluation_status'] = [MrmGetRiskEvaluationStatus.from_dict(x) for x in _dict.get('risk_evaluation_status')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MrmGetRiskEvaluationStatusEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'risk_evaluation_status') and self.risk_evaluation_status is not None:
_dict['risk_evaluation_status'] = [x.to_dict() for x in self.risk_evaluation_status]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MrmGetRiskEvaluationStatusEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MrmGetRiskEvaluationStatusEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MrmGetRiskEvaluationStatusEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class OperationalSpace():
"""
Operational Space definition.
:attr str name: The name of the Operational Space.
:attr str description: (optional) The description of the Operational Space.
"""
def __init__(self,
name: str,
*,
description: str = None) -> None:
"""
Initialize a OperationalSpace object.
:param str name: The name of the Operational Space.
:param str description: (optional) The description of the Operational
Space.
"""
self.name = name
self.description = description
@classmethod
def from_dict(cls, _dict: Dict) -> 'OperationalSpace':
"""Initialize a OperationalSpace object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in OperationalSpace JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a OperationalSpace object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this OperationalSpace object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'OperationalSpace') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'OperationalSpace') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class OperationalSpaceCollection():
"""
OperationalSpaceCollection.
:attr List[OperationalSpace] operational_spaces:
"""
def __init__(self,
operational_spaces: List['OperationalSpace']) -> None:
"""
Initialize a OperationalSpaceCollection object.
:param List[OperationalSpace] operational_spaces:
"""
self.operational_spaces = operational_spaces
@classmethod
def from_dict(cls, _dict: Dict) -> 'OperationalSpaceCollection':
"""Initialize a OperationalSpaceCollection object from a json dictionary."""
args = {}
if 'operational_spaces' in _dict:
args['operational_spaces'] = [OperationalSpace.from_dict(x) for x in _dict.get('operational_spaces')]
else:
raise ValueError('Required property \'operational_spaces\' not present in OperationalSpaceCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a OperationalSpaceCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'operational_spaces') and self.operational_spaces is not None:
_dict['operational_spaces'] = [x.to_dict() for x in self.operational_spaces]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this OperationalSpaceCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'OperationalSpaceCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'OperationalSpaceCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class OperationalSpaceResponse():
"""
OperationalSpaceResponse.
:attr Metadata metadata: (optional)
:attr OperationalSpace entity: (optional) Operational Space definition.
"""
def __init__(self,
*,
metadata: 'Metadata' = None,
entity: 'OperationalSpace' = None) -> None:
"""
Initialize a OperationalSpaceResponse object.
:param Metadata metadata: (optional)
:param OperationalSpace entity: (optional) Operational Space definition.
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'OperationalSpaceResponse':
"""Initialize a OperationalSpaceResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
if 'entity' in _dict:
args['entity'] = OperationalSpace.from_dict(_dict.get('entity'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a OperationalSpaceResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this OperationalSpaceResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'OperationalSpaceResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'OperationalSpaceResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PatchDocument():
"""
A JSONPatch document as defined by RFC 6902.
:attr str op: The operation to be performed.
:attr str path: A JSON-Pointer.
:attr object value: (optional) The value to be used within the operations.
:attr str from_: (optional) A string containing a JSON Pointer value.
"""
def __init__(self,
op: str,
path: str,
*,
value: object = None,
from_: str = None) -> None:
"""
Initialize a PatchDocument object.
:param str op: The operation to be performed.
:param str path: A JSON-Pointer.
:param object value: (optional) The value to be used within the operations.
:param str from_: (optional) A string containing a JSON Pointer value.
"""
self.op = op
self.path = path
self.value = value
self.from_ = from_
@classmethod
def from_dict(cls, _dict: Dict) -> 'PatchDocument':
"""Initialize a PatchDocument object from a json dictionary."""
args = {}
if 'op' in _dict:
args['op'] = _dict.get('op')
else:
raise ValueError('Required property \'op\' not present in PatchDocument JSON')
if 'path' in _dict:
args['path'] = _dict.get('path')
else:
raise ValueError('Required property \'path\' not present in PatchDocument JSON')
if 'value' in _dict:
args['value'] = _dict.get('value')
if 'from' in _dict:
args['from_'] = _dict.get('from')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PatchDocument object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'op') and self.op is not None:
_dict['op'] = self.op
if hasattr(self, 'path') and self.path is not None:
_dict['path'] = self.path
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'from_') and self.from_ is not None:
_dict['from'] = self.from_
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PatchDocument object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PatchDocument') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PatchDocument') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class OpEnum(str, Enum):
"""
The operation to be performed.
"""
ADD = 'add'
REMOVE = 'remove'
REPLACE = 'replace'
MOVE = 'move'
COPY = 'copy'
TEST = 'test'
class PolicyDetectorConfig():
"""
Configuration for a detector in a policy.
:attr str detector: Name of the detector to use.
:attr str action: Action to take when detector triggers.
:attr List[PolicyDetectorConfigDetectorPropertiesItem] detector_properties:
Properties to configure the detector.
"""
def __init__(self,
detector: str,
action: str,
detector_properties: List['PolicyDetectorConfigDetectorPropertiesItem']) -> None:
"""
Initialize a PolicyDetectorConfig object.
:param str detector: Name of the detector to use.
:param str action: Action to take when detector triggers.
:param List[PolicyDetectorConfigDetectorPropertiesItem]
detector_properties: Properties to configure the detector.
"""
self.detector = detector
self.action = action
self.detector_properties = detector_properties
@classmethod
def from_dict(cls, _dict: Dict) -> 'PolicyDetectorConfig':
"""Initialize a PolicyDetectorConfig object from a json dictionary."""
args = {}
if 'detector' in _dict:
args['detector'] = _dict.get('detector')
else:
raise ValueError('Required property \'detector\' not present in PolicyDetectorConfig JSON')
if 'action' in _dict:
args['action'] = _dict.get('action')
else:
raise ValueError('Required property \'action\' not present in PolicyDetectorConfig JSON')
if 'detector_properties' in _dict:
args['detector_properties'] = [PolicyDetectorConfigDetectorPropertiesItem.from_dict(x) for x in _dict.get('detector_properties')]
else:
raise ValueError('Required property \'detector_properties\' not present in PolicyDetectorConfig JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PolicyDetectorConfig object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'detector') and self.detector is not None:
_dict['detector'] = self.detector
if hasattr(self, 'action') and self.action is not None:
_dict['action'] = self.action
if hasattr(self, 'detector_properties') and self.detector_properties is not None:
_dict['detector_properties'] = [x.to_dict() for x in self.detector_properties]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PolicyDetectorConfig object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PolicyDetectorConfig') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PolicyDetectorConfig') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ActionEnum(str, Enum):
"""
Action to take when detector triggers.
"""
BLOCK = 'block'
MASK = 'mask'
class PolicyDetectorConfigDetectorPropertiesItem():
"""
PolicyDetectorConfigDetectorPropertiesItem.
:attr str name: Name of the detector property.
:attr str value: Value of the detector property.
"""
def __init__(self,
name: str,
value: str) -> None:
"""
Initialize a PolicyDetectorConfigDetectorPropertiesItem object.
:param str name: Name of the detector property.
:param str value: Value of the detector property.
"""
self.name = name
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'PolicyDetectorConfigDetectorPropertiesItem':
"""Initialize a PolicyDetectorConfigDetectorPropertiesItem object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in PolicyDetectorConfigDetectorPropertiesItem JSON')
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError('Required property \'value\' not present in PolicyDetectorConfigDetectorPropertiesItem JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PolicyDetectorConfigDetectorPropertiesItem object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PolicyDetectorConfigDetectorPropertiesItem object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PolicyDetectorConfigDetectorPropertiesItem') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PolicyDetectorConfigDetectorPropertiesItem') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PolicyEntity():
"""
Policy entity containing all policy details.
:attr str inventory_id: CAMS inventory ID.
:attr str name: Name of the policy.
:attr str description: (optional) Description of the policy.
:attr str block_message: (optional) Message to display when content is blocked.
:attr str mask_character: (optional) Character used for masking.
:attr List[PolicyDetectorConfig] input: Detector configurations for input
direction.
:attr List[PolicyDetectorConfig] output: Detector configurations for output
direction.
:attr str policy_status: Status of the policy.
:attr List[str] tags: Tags associated with the policy.
:attr datetime created_at: (optional) Timestamp when the policy was created.
:attr datetime modified_at: (optional) Timestamp when the policy was last
modified.
:attr PolicyStatus status: Status information for the policy.
"""
def __init__(self,
inventory_id: str,
name: str,
input: List['PolicyDetectorConfig'],
output: List['PolicyDetectorConfig'],
policy_status: str,
tags: List[str],
status: 'PolicyStatus',
*,
description: str = None,
block_message: str = None,
mask_character: str = None,
created_at: datetime = None,
modified_at: datetime = None) -> None:
"""
Initialize a PolicyEntity object.
:param str inventory_id: CAMS inventory ID.
:param str name: Name of the policy.
:param List[PolicyDetectorConfig] input: Detector configurations for input
direction.
:param List[PolicyDetectorConfig] output: Detector configurations for
output direction.
:param str policy_status: Status of the policy.
:param List[str] tags: Tags associated with the policy.
:param PolicyStatus status: Status information for the policy.
:param str description: (optional) Description of the policy.
:param str block_message: (optional) Message to display when content is
blocked.
:param str mask_character: (optional) Character used for masking.
:param datetime created_at: (optional) Timestamp when the policy was
created.
:param datetime modified_at: (optional) Timestamp when the policy was last
modified.
"""
self.inventory_id = inventory_id
self.name = name
self.description = description
self.block_message = block_message
self.mask_character = mask_character
self.input = input
self.output = output
self.policy_status = policy_status
self.tags = tags
self.created_at = created_at
self.modified_at = modified_at
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'PolicyEntity':
"""Initialize a PolicyEntity object from a json dictionary."""
args = {}
if 'inventory_id' in _dict:
args['inventory_id'] = _dict.get('inventory_id')
else:
raise ValueError('Required property \'inventory_id\' not present in PolicyEntity JSON')
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in PolicyEntity JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'block_message' in _dict:
args['block_message'] = _dict.get('block_message')
if 'mask_character' in _dict:
args['mask_character'] = _dict.get('mask_character')
if 'input' in _dict:
args['input'] = [PolicyDetectorConfig.from_dict(x) for x in _dict.get('input')]
else:
raise ValueError('Required property \'input\' not present in PolicyEntity JSON')
if 'output' in _dict:
args['output'] = [PolicyDetectorConfig.from_dict(x) for x in _dict.get('output')]
else:
raise ValueError('Required property \'output\' not present in PolicyEntity JSON')
if 'policy_status' in _dict:
args['policy_status'] = _dict.get('policy_status')
else:
raise ValueError('Required property \'policy_status\' not present in PolicyEntity JSON')
if 'tags' in _dict:
args['tags'] = _dict.get('tags')
else:
raise ValueError('Required property \'tags\' not present in PolicyEntity JSON')
if 'created_at' in _dict:
args['created_at'] = string_to_datetime(_dict.get('created_at'))
if 'modified_at' in _dict:
args['modified_at'] = string_to_datetime(_dict.get('modified_at'))
if 'status' in _dict:
args['status'] = PolicyStatus.from_dict(_dict.get('status'))
else:
raise ValueError('Required property \'status\' not present in PolicyEntity JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PolicyEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'inventory_id') and self.inventory_id is not None:
_dict['inventory_id'] = self.inventory_id
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'block_message') and self.block_message is not None:
_dict['block_message'] = self.block_message
if hasattr(self, 'mask_character') and self.mask_character is not None:
_dict['mask_character'] = self.mask_character
if hasattr(self, 'input') and self.input is not None:
_dict['input'] = [x.to_dict() for x in self.input]
if hasattr(self, 'output') and self.output is not None:
_dict['output'] = [x.to_dict() for x in self.output]
if hasattr(self, 'policy_status') and self.policy_status is not None:
_dict['policy_status'] = self.policy_status
if hasattr(self, 'tags') and self.tags is not None:
_dict['tags'] = self.tags
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = datetime_to_string(self.created_at)
if hasattr(self, 'modified_at') and self.modified_at is not None:
_dict['modified_at'] = datetime_to_string(self.modified_at)
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PolicyEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PolicyEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PolicyEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PolicyStatusEnum(str, Enum):
"""
Status of the policy.
"""
PUBLISH = 'publish'
DRAFT = 'draft'
class PolicyMetadata():
"""
Metadata about the policy.
:attr str id: Unique identifier for the policy.
:attr datetime created_at: Creation timestamp.
:attr datetime modified_at: (optional) Last modification timestamp.
"""
def __init__(self,
id: str,
created_at: datetime,
*,
modified_at: datetime = None) -> None:
"""
Initialize a PolicyMetadata object.
:param str id: Unique identifier for the policy.
:param datetime created_at: Creation timestamp.
:param datetime modified_at: (optional) Last modification timestamp.
"""
self.id = id
self.created_at = created_at
self.modified_at = modified_at
@classmethod
def from_dict(cls, _dict: Dict) -> 'PolicyMetadata':
"""Initialize a PolicyMetadata object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in PolicyMetadata JSON')
if 'created_at' in _dict:
args['created_at'] = string_to_datetime(_dict.get('created_at'))
else:
raise ValueError('Required property \'created_at\' not present in PolicyMetadata JSON')
if 'modified_at' in _dict:
args['modified_at'] = string_to_datetime(_dict.get('modified_at'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PolicyMetadata object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = datetime_to_string(self.created_at)
if hasattr(self, 'modified_at') and self.modified_at is not None:
_dict['modified_at'] = datetime_to_string(self.modified_at)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PolicyMetadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PolicyMetadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PolicyMetadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PolicyResponse():
"""
Response wrapper for policy operations.
:attr PolicyEntity entity: Policy entity containing all policy details.
:attr PolicyMetadata metadata: Metadata about the policy.
"""
def __init__(self,
entity: 'PolicyEntity',
metadata: 'PolicyMetadata') -> None:
"""
Initialize a PolicyResponse object.
:param PolicyEntity entity: Policy entity containing all policy details.
:param PolicyMetadata metadata: Metadata about the policy.
"""
self.entity = entity
self.metadata = metadata
@classmethod
def from_dict(cls, _dict: Dict) -> 'PolicyResponse':
"""Initialize a PolicyResponse object from a json dictionary."""
args = {}
if 'entity' in _dict:
args['entity'] = PolicyEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in PolicyResponse JSON')
if 'metadata' in _dict:
args['metadata'] = PolicyMetadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in PolicyResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PolicyResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PolicyResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PolicyResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PolicyResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PolicyResponseCollection():
"""
Response wrapper for list of policies.
:attr List[PolicyResponse] policies: List of policies.
"""
def __init__(self,
policies: List['PolicyResponse']) -> None:
"""
Initialize a PolicyResponseCollection object.
:param List[PolicyResponse] policies: List of policies.
"""
self.policies = policies
@classmethod
def from_dict(cls, _dict: Dict) -> 'PolicyResponseCollection':
"""Initialize a PolicyResponseCollection object from a json dictionary."""
args = {}
if 'policies' in _dict:
args['policies'] = [PolicyResponse.from_dict(x) for x in _dict.get('policies')]
else:
raise ValueError('Required property \'policies\' not present in PolicyResponseCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PolicyResponseCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'policies') and self.policies is not None:
_dict['policies'] = [x.to_dict() for x in self.policies]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PolicyResponseCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PolicyResponseCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PolicyResponseCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PolicyStatus():
"""
Status information for the policy.
:attr str state: (optional) Current state of the policy.
"""
def __init__(self,
*,
state: str = None) -> None:
"""
Initialize a PolicyStatus object.
:param str state: (optional) Current state of the policy.
"""
self.state = state
@classmethod
def from_dict(cls, _dict: Dict) -> 'PolicyStatus':
"""Initialize a PolicyStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PolicyStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PolicyStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PolicyStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PolicyStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PostExplanationTaskResponse():
"""
Post explanation tasks response.
:attr PostExplanationTaskResponseMetadata metadata: Metadata of post explanation
tasks response.
"""
def __init__(self,
metadata: 'PostExplanationTaskResponseMetadata') -> None:
"""
Initialize a PostExplanationTaskResponse object.
:param PostExplanationTaskResponseMetadata metadata: Metadata of post
explanation tasks response.
"""
self.metadata = metadata
@classmethod
def from_dict(cls, _dict: Dict) -> 'PostExplanationTaskResponse':
"""Initialize a PostExplanationTaskResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = PostExplanationTaskResponseMetadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in PostExplanationTaskResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PostExplanationTaskResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PostExplanationTaskResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PostExplanationTaskResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PostExplanationTaskResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PostExplanationTaskResponseMetadata():
"""
Metadata of post explanation tasks response.
:attr List[str] explanation_task_ids: List of identifiers for tracking
explanation tasks.
:attr str created_by: ID of the user creating explanation task.
:attr str created_at: Time when the explanation task was initiated.
"""
def __init__(self,
explanation_task_ids: List[str],
created_by: str,
created_at: str) -> None:
"""
Initialize a PostExplanationTaskResponseMetadata object.
:param List[str] explanation_task_ids: List of identifiers for tracking
explanation tasks.
:param str created_by: ID of the user creating explanation task.
:param str created_at: Time when the explanation task was initiated.
"""
self.explanation_task_ids = explanation_task_ids
self.created_by = created_by
self.created_at = created_at
@classmethod
def from_dict(cls, _dict: Dict) -> 'PostExplanationTaskResponseMetadata':
"""Initialize a PostExplanationTaskResponseMetadata object from a json dictionary."""
args = {}
if 'explanation_task_ids' in _dict:
args['explanation_task_ids'] = _dict.get('explanation_task_ids')
else:
raise ValueError('Required property \'explanation_task_ids\' not present in PostExplanationTaskResponseMetadata JSON')
if 'created_by' in _dict:
args['created_by'] = _dict.get('created_by')
else:
raise ValueError('Required property \'created_by\' not present in PostExplanationTaskResponseMetadata JSON')
if 'created_at' in _dict:
args['created_at'] = _dict.get('created_at')
else:
raise ValueError('Required property \'created_at\' not present in PostExplanationTaskResponseMetadata JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PostExplanationTaskResponseMetadata object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'explanation_task_ids') and self.explanation_task_ids is not None:
_dict['explanation_task_ids'] = self.explanation_task_ids
if hasattr(self, 'created_by') and self.created_by is not None:
_dict['created_by'] = self.created_by
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = self.created_at
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PostExplanationTaskResponseMetadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PostExplanationTaskResponseMetadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PostExplanationTaskResponseMetadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PostRiskEvaluationsResponse():
"""
PostRiskEvaluationsResponse.
:attr str evaluation_id: (optional) The unique ID for the MRM evaluation.
:attr str evaluation_date: (optional) The date time stamp in UTC ISO format for
the MRM evaluation.
:attr str publish_metrics: (optional) Flag to decide whether to send evaluated
metrics to OpenPages.
:attr str evaluation_tests: (optional) Comma separated list of monitor tests to
run.
:attr str evaluation_start_time: (optional) Time stamp of the evaluation.
:attr PostRiskEvaluationsResponseStatus status: (optional)
"""
def __init__(self,
*,
evaluation_id: str = None,
evaluation_date: str = None,
publish_metrics: str = None,
evaluation_tests: str = None,
evaluation_start_time: str = None,
status: 'PostRiskEvaluationsResponseStatus' = None) -> None:
"""
Initialize a PostRiskEvaluationsResponse object.
:param str evaluation_id: (optional) The unique ID for the MRM evaluation.
:param str evaluation_date: (optional) The date time stamp in UTC ISO
format for the MRM evaluation.
:param str publish_metrics: (optional) Flag to decide whether to send
evaluated metrics to OpenPages.
:param str evaluation_tests: (optional) Comma separated list of monitor
tests to run.
:param str evaluation_start_time: (optional) Time stamp of the evaluation.
:param PostRiskEvaluationsResponseStatus status: (optional)
"""
self.evaluation_id = evaluation_id
self.evaluation_date = evaluation_date
self.publish_metrics = publish_metrics
self.evaluation_tests = evaluation_tests
self.evaluation_start_time = evaluation_start_time
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'PostRiskEvaluationsResponse':
"""Initialize a PostRiskEvaluationsResponse object from a json dictionary."""
args = {}
if 'evaluation_id' in _dict:
args['evaluation_id'] = _dict.get('evaluation_id')
if 'evaluation_date' in _dict:
args['evaluation_date'] = _dict.get('evaluation_date')
if 'publish_metrics' in _dict:
args['publish_metrics'] = _dict.get('publish_metrics')
if 'evaluation_tests' in _dict:
args['evaluation_tests'] = _dict.get('evaluation_tests')
if 'evaluation_start_time' in _dict:
args['evaluation_start_time'] = _dict.get('evaluation_start_time')
if 'status' in _dict:
args['status'] = PostRiskEvaluationsResponseStatus.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PostRiskEvaluationsResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'evaluation_id') and self.evaluation_id is not None:
_dict['evaluation_id'] = self.evaluation_id
if hasattr(self, 'evaluation_date') and self.evaluation_date is not None:
_dict['evaluation_date'] = self.evaluation_date
if hasattr(self, 'publish_metrics') and self.publish_metrics is not None:
_dict['publish_metrics'] = self.publish_metrics
if hasattr(self, 'evaluation_tests') and self.evaluation_tests is not None:
_dict['evaluation_tests'] = self.evaluation_tests
if hasattr(self, 'evaluation_start_time') and self.evaluation_start_time is not None:
_dict['evaluation_start_time'] = self.evaluation_start_time
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PostRiskEvaluationsResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PostRiskEvaluationsResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PostRiskEvaluationsResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PostRiskEvaluationsResponseStatus():
"""
PostRiskEvaluationsResponseStatus.
:attr str state: (optional) The state of the upload data.
"""
def __init__(self,
*,
state: str = None) -> None:
"""
Initialize a PostRiskEvaluationsResponseStatus object.
:param str state: (optional) The state of the upload data.
"""
self.state = state
@classmethod
def from_dict(cls, _dict: Dict) -> 'PostRiskEvaluationsResponseStatus':
"""Initialize a PostRiskEvaluationsResponseStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PostRiskEvaluationsResponseStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PostRiskEvaluationsResponseStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PostRiskEvaluationsResponseStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PostRiskEvaluationsResponseStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PrimaryStorageCredentials():
"""
PrimaryStorageCredentials.
"""
def __init__(self) -> None:
"""
Initialize a PrimaryStorageCredentials object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['PrimaryStorageCredentialsLong']))
raise Exception(msg)
class PromptSetupDataProperties():
"""
The metadata properties of the prompt variables, meta-fields, reference column and
model output column.
:attr str field_name: (optional) The name of the column.
:attr bool expect_large_content: (optional) Boolean flag to indicate if the
column can contain large content.
"""
def __init__(self,
*,
field_name: str = None,
expect_large_content: bool = None) -> None:
"""
Initialize a PromptSetupDataProperties object.
:param str field_name: (optional) The name of the column.
:param bool expect_large_content: (optional) Boolean flag to indicate if
the column can contain large content.
"""
self.field_name = field_name
self.expect_large_content = expect_large_content
@classmethod
def from_dict(cls, _dict: Dict) -> 'PromptSetupDataProperties':
"""Initialize a PromptSetupDataProperties object from a json dictionary."""
args = {}
if 'field_name' in _dict:
args['field_name'] = _dict.get('field_name')
if 'expect_large_content' in _dict:
args['expect_large_content'] = _dict.get('expect_large_content')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PromptSetupDataProperties object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'field_name') and self.field_name is not None:
_dict['field_name'] = self.field_name
if hasattr(self, 'expect_large_content') and self.expect_large_content is not None:
_dict['expect_large_content'] = self.expect_large_content
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PromptSetupDataProperties object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PromptSetupDataProperties') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PromptSetupDataProperties') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PromptSetupMetaField():
"""
The details of the meta-fields to be input for prompt setup.
:attr str name: (optional) The name of the meta-field.
:attr str data_type: (optional) The data-type of the meta-field.
"""
def __init__(self,
*,
name: str = None,
data_type: str = None) -> None:
"""
Initialize a PromptSetupMetaField object.
:param str name: (optional) The name of the meta-field.
:param str data_type: (optional) The data-type of the meta-field.
"""
self.name = name
self.data_type = data_type
@classmethod
def from_dict(cls, _dict: Dict) -> 'PromptSetupMetaField':
"""Initialize a PromptSetupMetaField object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
if 'data_type' in _dict:
args['data_type'] = _dict.get('data_type')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PromptSetupMetaField object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'data_type') and self.data_type is not None:
_dict['data_type'] = self.data_type
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PromptSetupMetaField object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PromptSetupMetaField') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PromptSetupMetaField') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PromptSetupRequestMonitors():
"""
The list of monitors to be configured for the prompt template.
:attr PromptSetupRequestMonitorsMonitorDefinitionId monitor_definition_id:
(optional)
"""
def __init__(self,
*,
monitor_definition_id: 'PromptSetupRequestMonitorsMonitorDefinitionId' = None) -> None:
"""
Initialize a PromptSetupRequestMonitors object.
:param PromptSetupRequestMonitorsMonitorDefinitionId monitor_definition_id:
(optional)
"""
self.monitor_definition_id = monitor_definition_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'PromptSetupRequestMonitors':
"""Initialize a PromptSetupRequestMonitors object from a json dictionary."""
args = {}
if 'monitor_definition_id' in _dict:
args['monitor_definition_id'] = PromptSetupRequestMonitorsMonitorDefinitionId.from_dict(_dict.get('monitor_definition_id'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PromptSetupRequestMonitors object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'monitor_definition_id') and self.monitor_definition_id is not None:
_dict['monitor_definition_id'] = self.monitor_definition_id.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PromptSetupRequestMonitors object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PromptSetupRequestMonitors') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PromptSetupRequestMonitors') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PromptSetupRequestMonitorsMonitorDefinitionId():
"""
PromptSetupRequestMonitorsMonitorDefinitionId.
:attr object parameters: (optional)
:attr List[object] thresholds: (optional)
"""
def __init__(self,
*,
parameters: object = None,
thresholds: List[object] = None) -> None:
"""
Initialize a PromptSetupRequestMonitorsMonitorDefinitionId object.
:param object parameters: (optional)
:param List[object] thresholds: (optional)
"""
self.parameters = parameters
self.thresholds = thresholds
@classmethod
def from_dict(cls, _dict: Dict) -> 'PromptSetupRequestMonitorsMonitorDefinitionId':
"""Initialize a PromptSetupRequestMonitorsMonitorDefinitionId object from a json dictionary."""
args = {}
if 'parameters' in _dict:
args['parameters'] = _dict.get('parameters')
if 'thresholds' in _dict:
args['thresholds'] = _dict.get('thresholds')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PromptSetupRequestMonitorsMonitorDefinitionId object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'parameters') and self.parameters is not None:
_dict['parameters'] = self.parameters
if hasattr(self, 'thresholds') and self.thresholds is not None:
_dict['thresholds'] = self.thresholds
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PromptSetupRequestMonitorsMonitorDefinitionId object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PromptSetupRequestMonitorsMonitorDefinitionId') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PromptSetupRequestMonitorsMonitorDefinitionId') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PromptSetupResponse():
"""
The prompt setup response.
:attr str prompt_template_asset_id:
:attr str project_id: (optional)
:attr str space_id: (optional)
:attr str deployment_id: (optional)
:attr str service_provider_id: (optional)
:attr str subscription_id: (optional)
:attr str mrm_monitor_instance_id: (optional) The MRM monitor instance ID.
:attr str start_time: The date-timestamp when the prompt setup was started.
:attr str end_time: (optional) The date-timestamp when the prompt setup ended.
:attr PromptSetupResponseStatus status: (optional) The status of the prompt
setup.
"""
def __init__(self,
prompt_template_asset_id: str,
start_time: str,
*,
project_id: str = None,
space_id: str = None,
deployment_id: str = None,
service_provider_id: str = None,
subscription_id: str = None,
mrm_monitor_instance_id: str = None,
end_time: str = None,
status: 'PromptSetupResponseStatus' = None) -> None:
"""
Initialize a PromptSetupResponse object.
:param str prompt_template_asset_id:
:param str start_time: The date-timestamp when the prompt setup was
started.
:param str project_id: (optional)
:param str space_id: (optional)
:param str deployment_id: (optional)
:param str service_provider_id: (optional)
:param str subscription_id: (optional)
:param str mrm_monitor_instance_id: (optional) The MRM monitor instance ID.
:param str end_time: (optional) The date-timestamp when the prompt setup
ended.
:param PromptSetupResponseStatus status: (optional) The status of the
prompt setup.
"""
self.prompt_template_asset_id = prompt_template_asset_id
self.project_id = project_id
self.space_id = space_id
self.deployment_id = deployment_id
self.service_provider_id = service_provider_id
self.subscription_id = subscription_id
self.mrm_monitor_instance_id = mrm_monitor_instance_id
self.start_time = start_time
self.end_time = end_time
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'PromptSetupResponse':
"""Initialize a PromptSetupResponse object from a json dictionary."""
args = {}
if 'prompt_template_asset_id' in _dict:
args['prompt_template_asset_id'] = _dict.get('prompt_template_asset_id')
else:
raise ValueError('Required property \'prompt_template_asset_id\' not present in PromptSetupResponse JSON')
if 'project_id' in _dict:
args['project_id'] = _dict.get('project_id')
if 'space_id' in _dict:
args['space_id'] = _dict.get('space_id')
if 'deployment_id' in _dict:
args['deployment_id'] = _dict.get('deployment_id')
if 'service_provider_id' in _dict:
args['service_provider_id'] = _dict.get('service_provider_id')
if 'subscription_id' in _dict:
args['subscription_id'] = _dict.get('subscription_id')
if 'mrm_monitor_instance_id' in _dict:
args['mrm_monitor_instance_id'] = _dict.get('mrm_monitor_instance_id')
if 'start_time' in _dict:
args['start_time'] = _dict.get('start_time')
else:
raise ValueError('Required property \'start_time\' not present in PromptSetupResponse JSON')
if 'end_time' in _dict:
args['end_time'] = _dict.get('end_time')
if 'status' in _dict:
args['status'] = PromptSetupResponseStatus.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PromptSetupResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'prompt_template_asset_id') and self.prompt_template_asset_id is not None:
_dict['prompt_template_asset_id'] = self.prompt_template_asset_id
if hasattr(self, 'project_id') and self.project_id is not None:
_dict['project_id'] = self.project_id
if hasattr(self, 'space_id') and self.space_id is not None:
_dict['space_id'] = self.space_id
if hasattr(self, 'deployment_id') and self.deployment_id is not None:
_dict['deployment_id'] = self.deployment_id
if hasattr(self, 'service_provider_id') and self.service_provider_id is not None:
_dict['service_provider_id'] = self.service_provider_id
if hasattr(self, 'subscription_id') and self.subscription_id is not None:
_dict['subscription_id'] = self.subscription_id
if hasattr(self, 'mrm_monitor_instance_id') and self.mrm_monitor_instance_id is not None:
_dict['mrm_monitor_instance_id'] = self.mrm_monitor_instance_id
if hasattr(self, 'start_time') and self.start_time is not None:
_dict['start_time'] = self.start_time
if hasattr(self, 'end_time') and self.end_time is not None:
_dict['end_time'] = self.end_time
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PromptSetupResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PromptSetupResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PromptSetupResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PromptSetupResponseStatus():
"""
The status of the prompt setup.
:attr str state: The prompt setup state.
:attr GenericErrorResponse failure: (optional)
"""
def __init__(self,
state: str,
*,
failure: 'GenericErrorResponse' = None) -> None:
"""
Initialize a PromptSetupResponseStatus object.
:param str state: The prompt setup state.
:param GenericErrorResponse failure: (optional)
"""
self.state = state
self.failure = failure
@classmethod
def from_dict(cls, _dict: Dict) -> 'PromptSetupResponseStatus':
"""Initialize a PromptSetupResponseStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
else:
raise ValueError('Required property \'state\' not present in PromptSetupResponseStatus JSON')
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PromptSetupResponseStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PromptSetupResponseStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PromptSetupResponseStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PromptSetupResponseStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
The prompt setup state.
"""
RUNNING = 'RUNNING'
ERROR = 'ERROR'
FINISHED = 'FINISHED'
class RecordsCountSummary():
"""
Summary about records count.
:attr int count:
:attr str type: The type of records time.
:attr datetime timestamp: (optional) timestamp of last consumed record (only for
unprocessed_records).
:attr GenericErrorResponse failure: (optional)
"""
def __init__(self,
count: int,
type: str,
*,
timestamp: datetime = None,
failure: 'GenericErrorResponse' = None) -> None:
"""
Initialize a RecordsCountSummary object.
:param int count:
:param str type: The type of records time.
:param datetime timestamp: (optional) timestamp of last consumed record
(only for unprocessed_records).
:param GenericErrorResponse failure: (optional)
"""
self.count = count
self.type = type
self.timestamp = timestamp
self.failure = failure
@classmethod
def from_dict(cls, _dict: Dict) -> 'RecordsCountSummary':
"""Initialize a RecordsCountSummary object from a json dictionary."""
args = {}
if 'count' in _dict:
args['count'] = _dict.get('count')
else:
raise ValueError('Required property \'count\' not present in RecordsCountSummary JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in RecordsCountSummary JSON')
if 'timestamp' in _dict:
args['timestamp'] = string_to_datetime(_dict.get('timestamp'))
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RecordsCountSummary object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'count') and self.count is not None:
_dict['count'] = self.count
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'timestamp') and self.timestamp is not None:
_dict['timestamp'] = datetime_to_string(self.timestamp)
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RecordsCountSummary object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RecordsCountSummary') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RecordsCountSummary') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
The type of records time.
"""
PAYLOAD_LOGGING = 'payload_logging'
FEEDBACK = 'feedback'
class RecordsListResponse():
"""
RecordsListResponse.
"""
def __init__(self) -> None:
"""
Initialize a RecordsListResponse object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['RecordsListResponseDataRecordsResponseCollectionDict', 'RecordsListResponseDataRecordsResponseCollectionList']))
raise Exception(msg)
class RiskEvaluationResponse():
"""
RiskEvaluationResponse.
:attr RiskEvaluationResponseMetadata metadata: (optional)
:attr MonitoringRunEntity entity: (optional)
"""
def __init__(self,
*,
metadata: 'RiskEvaluationResponseMetadata' = None,
entity: 'MonitoringRunEntity' = None) -> None:
"""
Initialize a RiskEvaluationResponse object.
:param RiskEvaluationResponseMetadata metadata: (optional)
:param MonitoringRunEntity entity: (optional)
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'RiskEvaluationResponse':
"""Initialize a RiskEvaluationResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = RiskEvaluationResponseMetadata.from_dict(_dict.get('metadata'))
if 'entity' in _dict:
args['entity'] = MonitoringRunEntity.from_dict(_dict.get('entity'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RiskEvaluationResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RiskEvaluationResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RiskEvaluationResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RiskEvaluationResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class RiskEvaluationResponseMetadata():
"""
RiskEvaluationResponseMetadata.
:attr str id: (optional)
:attr str created_at: (optional)
:attr str created_by: (optional)
:attr str modified_by: (optional)
"""
def __init__(self,
*,
id: str = None,
created_at: str = None,
created_by: str = None,
modified_by: str = None) -> None:
"""
Initialize a RiskEvaluationResponseMetadata object.
:param str id: (optional)
:param str created_at: (optional)
:param str created_by: (optional)
:param str modified_by: (optional)
"""
self.id = id
self.created_at = created_at
self.created_by = created_by
self.modified_by = modified_by
@classmethod
def from_dict(cls, _dict: Dict) -> 'RiskEvaluationResponseMetadata':
"""Initialize a RiskEvaluationResponseMetadata object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
if 'created_at' in _dict:
args['created_at'] = _dict.get('created_at')
if 'created_by' in _dict:
args['created_by'] = _dict.get('created_by')
if 'modified_by' in _dict:
args['modified_by'] = _dict.get('modified_by')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RiskEvaluationResponseMetadata object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = self.created_at
if hasattr(self, 'created_by') and self.created_by is not None:
_dict['created_by'] = self.created_by
if hasattr(self, 'modified_by') and self.modified_by is not None:
_dict['modified_by'] = self.modified_by
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RiskEvaluationResponseMetadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RiskEvaluationResponseMetadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RiskEvaluationResponseMetadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class RiskEvaluationStatus():
"""
RiskEvaluationStatus.
:attr str state:
:attr str comment: (optional) Optional comment to the evaluation.
:attr str evaluated_by: (optional) Author of the evaluation.
:attr str evaluated_at: (optional) Time of the evaluation.
"""
def __init__(self,
state: str,
*,
comment: str = None,
evaluated_by: str = None,
evaluated_at: str = None) -> None:
"""
Initialize a RiskEvaluationStatus object.
:param str state:
:param str comment: (optional) Optional comment to the evaluation.
:param str evaluated_by: (optional) Author of the evaluation.
:param str evaluated_at: (optional) Time of the evaluation.
"""
self.state = state
self.comment = comment
self.evaluated_by = evaluated_by
self.evaluated_at = evaluated_at
@classmethod
def from_dict(cls, _dict: Dict) -> 'RiskEvaluationStatus':
"""Initialize a RiskEvaluationStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
else:
raise ValueError('Required property \'state\' not present in RiskEvaluationStatus JSON')
if 'comment' in _dict:
args['comment'] = _dict.get('comment')
if 'evaluated_by' in _dict:
args['evaluated_by'] = _dict.get('evaluated_by')
if 'evaluated_at' in _dict:
args['evaluated_at'] = _dict.get('evaluated_at')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RiskEvaluationStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
if hasattr(self, 'comment') and self.comment is not None:
_dict['comment'] = self.comment
if hasattr(self, 'evaluated_by') and self.evaluated_by is not None:
_dict['evaluated_by'] = self.evaluated_by
if hasattr(self, 'evaluated_at') and self.evaluated_at is not None:
_dict['evaluated_at'] = self.evaluated_at
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RiskEvaluationStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RiskEvaluationStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RiskEvaluationStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
state.
"""
PENDING_EVALUATION = 'pending_evaluation'
APPROVED = 'approved'
REJECTED = 'rejected'
class RiskNotificationPreferencesResponse():
"""
RiskNotificationPreferencesResponse.
:attr RiskNotificationPreferencesResponseMetadata metadata: (optional)
:attr RiskNotificationPreferencesResponseEntity entity: (optional)
"""
def __init__(self,
*,
metadata: 'RiskNotificationPreferencesResponseMetadata' = None,
entity: 'RiskNotificationPreferencesResponseEntity' = None) -> None:
"""
Initialize a RiskNotificationPreferencesResponse object.
:param RiskNotificationPreferencesResponseMetadata metadata: (optional)
:param RiskNotificationPreferencesResponseEntity entity: (optional)
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'RiskNotificationPreferencesResponse':
"""Initialize a RiskNotificationPreferencesResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = RiskNotificationPreferencesResponseMetadata.from_dict(_dict.get('metadata'))
if 'entity' in _dict:
args['entity'] = RiskNotificationPreferencesResponseEntity.from_dict(_dict.get('entity'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RiskNotificationPreferencesResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RiskNotificationPreferencesResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RiskNotificationPreferencesResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RiskNotificationPreferencesResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class RiskNotificationPreferencesResponseEntity():
"""
RiskNotificationPreferencesResponseEntity.
:attr bool notification_enabled: (optional)
:attr str notification_frequency: (optional)
:attr List[str] notification_emails: (optional)
"""
def __init__(self,
*,
notification_enabled: bool = None,
notification_frequency: str = None,
notification_emails: List[str] = None) -> None:
"""
Initialize a RiskNotificationPreferencesResponseEntity object.
:param bool notification_enabled: (optional)
:param str notification_frequency: (optional)
:param List[str] notification_emails: (optional)
"""
self.notification_enabled = notification_enabled
self.notification_frequency = notification_frequency
self.notification_emails = notification_emails
@classmethod
def from_dict(cls, _dict: Dict) -> 'RiskNotificationPreferencesResponseEntity':
"""Initialize a RiskNotificationPreferencesResponseEntity object from a json dictionary."""
args = {}
if 'notification_enabled' in _dict:
args['notification_enabled'] = _dict.get('notification_enabled')
if 'notification_frequency' in _dict:
args['notification_frequency'] = _dict.get('notification_frequency')
if 'notification_emails' in _dict:
args['notification_emails'] = _dict.get('notification_emails')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RiskNotificationPreferencesResponseEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'notification_enabled') and self.notification_enabled is not None:
_dict['notification_enabled'] = self.notification_enabled
if hasattr(self, 'notification_frequency') and self.notification_frequency is not None:
_dict['notification_frequency'] = self.notification_frequency
if hasattr(self, 'notification_emails') and self.notification_emails is not None:
_dict['notification_emails'] = self.notification_emails
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RiskNotificationPreferencesResponseEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RiskNotificationPreferencesResponseEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RiskNotificationPreferencesResponseEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class RiskNotificationPreferencesResponseMetadata():
"""
RiskNotificationPreferencesResponseMetadata.
:attr str created_at: (optional)
:attr str created_by: (optional)
:attr str url: (optional)
:attr str id: (optional)
"""
def __init__(self,
*,
created_at: str = None,
created_by: str = None,
url: str = None,
id: str = None) -> None:
"""
Initialize a RiskNotificationPreferencesResponseMetadata object.
:param str created_at: (optional)
:param str created_by: (optional)
:param str url: (optional)
:param str id: (optional)
"""
self.created_at = created_at
self.created_by = created_by
self.url = url
self.id = id
@classmethod
def from_dict(cls, _dict: Dict) -> 'RiskNotificationPreferencesResponseMetadata':
"""Initialize a RiskNotificationPreferencesResponseMetadata object from a json dictionary."""
args = {}
if 'created_at' in _dict:
args['created_at'] = _dict.get('created_at')
if 'created_by' in _dict:
args['created_by'] = _dict.get('created_by')
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'id' in _dict:
args['id'] = _dict.get('id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RiskNotificationPreferencesResponseMetadata object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'created_at') and self.created_at is not None:
_dict['created_at'] = self.created_at
if hasattr(self, 'created_by') and self.created_by is not None:
_dict['created_by'] = self.created_by
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RiskNotificationPreferencesResponseMetadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RiskNotificationPreferencesResponseMetadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RiskNotificationPreferencesResponseMetadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ScheduleStartTime():
"""
Definition of first run time for scheduled activity; either absolute or relative the
the moment of activation.
:attr str type: The type of start time.
:attr str delay_unit: (optional) must be set if type is `relative`.
:attr int delay: (optional) must be set if type is `relative`.
:attr datetime timestamp: (optional) must be set if type is `absolute`.
"""
def __init__(self,
type: str,
*,
delay_unit: str = None,
delay: int = None,
timestamp: datetime = None) -> None:
"""
Initialize a ScheduleStartTime object.
:param str type: The type of start time.
:param str delay_unit: (optional) must be set if type is `relative`.
:param int delay: (optional) must be set if type is `relative`.
:param datetime timestamp: (optional) must be set if type is `absolute`.
"""
self.type = type
self.delay_unit = delay_unit
self.delay = delay
self.timestamp = timestamp
@classmethod
def from_dict(cls, _dict: Dict) -> 'ScheduleStartTime':
"""Initialize a ScheduleStartTime object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in ScheduleStartTime JSON')
if 'delay_unit' in _dict:
args['delay_unit'] = _dict.get('delay_unit')
if 'delay' in _dict:
args['delay'] = _dict.get('delay')
if 'timestamp' in _dict:
args['timestamp'] = string_to_datetime(_dict.get('timestamp'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ScheduleStartTime object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'delay_unit') and self.delay_unit is not None:
_dict['delay_unit'] = self.delay_unit
if hasattr(self, 'delay') and self.delay is not None:
_dict['delay'] = self.delay
if hasattr(self, 'timestamp') and self.timestamp is not None:
_dict['timestamp'] = datetime_to_string(self.timestamp)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ScheduleStartTime object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ScheduleStartTime') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ScheduleStartTime') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
The type of start time.
"""
RELATIVE = 'relative'
ABSOLUTE = 'absolute'
class DelayUnitEnum(str, Enum):
"""
must be set if type is `relative`.
"""
MINUTE = 'minute'
HOUR = 'hour'
DAY = 'day'
WEEK = 'week'
MONTH = 'month'
YEAR = 'year'
class SchemaInferenceResponse():
"""
Schema inference response.
:attr FileAssetMetadata file_asset_metadata: (optional) File data asset
metadata.
:attr SubscriptionResponse subscription:
"""
def __init__(self,
subscription: 'SubscriptionResponse',
*,
file_asset_metadata: 'FileAssetMetadata' = None) -> None:
"""
Initialize a SchemaInferenceResponse object.
:param SubscriptionResponse subscription:
:param FileAssetMetadata file_asset_metadata: (optional) File data asset
metadata.
"""
self.file_asset_metadata = file_asset_metadata
self.subscription = subscription
@classmethod
def from_dict(cls, _dict: Dict) -> 'SchemaInferenceResponse':
"""Initialize a SchemaInferenceResponse object from a json dictionary."""
args = {}
if 'file_asset_metadata' in _dict:
args['file_asset_metadata'] = FileAssetMetadata.from_dict(_dict.get('file_asset_metadata'))
if 'subscription' in _dict:
args['subscription'] = SubscriptionResponse.from_dict(_dict.get('subscription'))
else:
raise ValueError('Required property \'subscription\' not present in SchemaInferenceResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SchemaInferenceResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'file_asset_metadata') and self.file_asset_metadata is not None:
_dict['file_asset_metadata'] = self.file_asset_metadata.to_dict()
if hasattr(self, 'subscription') and self.subscription is not None:
_dict['subscription'] = self.subscription.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SchemaInferenceResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SchemaInferenceResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SchemaInferenceResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ScoreData():
"""
Score data object.
:attr List[object] values: Score value records.
:attr List[str] fields: (optional) Score fields.
:attr str id: (optional) Discriminates the data for multi input data situation.
For example in cases where multiple tensors are expected.
"""
def __init__(self,
values: List[object],
*,
fields: List[str] = None,
id: str = None) -> None:
"""
Initialize a ScoreData object.
:param List[object] values: Score value records.
:param List[str] fields: (optional) Score fields.
:param str id: (optional) Discriminates the data for multi input data
situation. For example in cases where multiple tensors are expected.
"""
self.values = values
self.fields = fields
self.id = id
@classmethod
def from_dict(cls, _dict: Dict) -> 'ScoreData':
"""Initialize a ScoreData object from a json dictionary."""
args = {}
if 'values' in _dict:
args['values'] = _dict.get('values')
else:
raise ValueError('Required property \'values\' not present in ScoreData JSON')
if 'fields' in _dict:
args['fields'] = _dict.get('fields')
if 'id' in _dict:
args['id'] = _dict.get('id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ScoreData object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = self.values
if hasattr(self, 'fields') and self.fields is not None:
_dict['fields'] = self.fields
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ScoreData object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ScoreData') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ScoreData') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ScoringEndpoint():
"""
Definition of scoring endpoint in custom_machine_learning.
:attr str url: (optional)
:attr SecretCleaned credentials: (optional)
:attr dict request_headers: (optional) map header name to header value.
"""
def __init__(self,
*,
url: str = None,
credentials: 'SecretCleaned' = None,
request_headers: dict = None) -> None:
"""
Initialize a ScoringEndpoint object.
:param str url: (optional)
:param SecretCleaned credentials: (optional)
:param dict request_headers: (optional) map header name to header value.
"""
self.url = url
self.credentials = credentials
self.request_headers = request_headers
@classmethod
def from_dict(cls, _dict: Dict) -> 'ScoringEndpoint':
"""Initialize a ScoringEndpoint object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'credentials' in _dict:
args['credentials'] = SecretCleaned.from_dict(_dict.get('credentials'))
if 'request_headers' in _dict:
args['request_headers'] = _dict.get('request_headers')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ScoringEndpoint object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'credentials') and self.credentials is not None:
_dict['credentials'] = self.credentials.to_dict()
if hasattr(self, 'request_headers') and self.request_headers is not None:
_dict['request_headers'] = self.request_headers
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ScoringEndpoint object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ScoringEndpoint') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ScoringEndpoint') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ScoringEndpointCredentials():
"""
ScoringEndpointCredentials.
"""
def __init__(self,
**kwargs) -> None:
"""
Initialize a ScoringEndpointCredentials object.
:param **kwargs: (optional) Any additional properties.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['ScoringEndpointCredentialsAzureScoringEndpointCredentials']))
raise Exception(msg)
class ScoringEndpointRequest():
"""
Definition of scoring endpoint in custom_machine_learning.
:attr str url: (optional)
:attr ScoringEndpointCredentials credentials: (optional)
:attr dict request_headers: (optional) map header name to header value.
"""
def __init__(self,
*,
url: str = None,
credentials: 'ScoringEndpointCredentials' = None,
request_headers: dict = None) -> None:
"""
Initialize a ScoringEndpointRequest object.
:param str url: (optional)
:param ScoringEndpointCredentials credentials: (optional)
:param dict request_headers: (optional) map header name to header value.
"""
self.url = url
self.credentials = credentials
self.request_headers = request_headers
@classmethod
def from_dict(cls, _dict: Dict) -> 'ScoringEndpointRequest':
"""Initialize a ScoringEndpointRequest object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'credentials' in _dict:
args['credentials'] = _dict.get('credentials')
if 'request_headers' in _dict:
args['request_headers'] = _dict.get('request_headers')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ScoringEndpointRequest object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'credentials') and self.credentials is not None:
if isinstance(self.credentials, dict):
_dict['credentials'] = self.credentials
else:
_dict['credentials'] = self.credentials.to_dict()
if hasattr(self, 'request_headers') and self.request_headers is not None:
_dict['request_headers'] = self.request_headers
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ScoringEndpointRequest object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ScoringEndpointRequest') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ScoringEndpointRequest') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class SecretCleaned():
"""
SecretCleaned.
:attr str secret_id: Generated id which identifies credentials.
"""
def __init__(self,
secret_id: str) -> None:
"""
Initialize a SecretCleaned object.
:param str secret_id: Generated id which identifies credentials.
"""
self.secret_id = secret_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'SecretCleaned':
"""Initialize a SecretCleaned object from a json dictionary."""
args = {}
if 'secret_id' in _dict:
args['secret_id'] = _dict.get('secret_id')
else:
raise ValueError('Required property \'secret_id\' not present in SecretCleaned JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SecretCleaned object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'secret_id') and self.secret_id is not None:
_dict['secret_id'] = self.secret_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SecretCleaned object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SecretCleaned') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SecretCleaned') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ServiceProviderResponse():
"""
ServiceProviderResponse.
:attr Metadata metadata:
:attr ServiceProviderResponseEntity entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'ServiceProviderResponseEntity') -> None:
"""
Initialize a ServiceProviderResponse object.
:param Metadata metadata:
:param ServiceProviderResponseEntity entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'ServiceProviderResponse':
"""Initialize a ServiceProviderResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in ServiceProviderResponse JSON')
if 'entity' in _dict:
args['entity'] = ServiceProviderResponseEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in ServiceProviderResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ServiceProviderResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ServiceProviderResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ServiceProviderResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ServiceProviderResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ServiceProviderResponseCollection():
"""
ServiceProviderResponseCollection.
:attr List[ServiceProviderResponse] service_providers:
"""
def __init__(self,
service_providers: List['ServiceProviderResponse']) -> None:
"""
Initialize a ServiceProviderResponseCollection object.
:param List[ServiceProviderResponse] service_providers:
"""
self.service_providers = service_providers
@classmethod
def from_dict(cls, _dict: Dict) -> 'ServiceProviderResponseCollection':
"""Initialize a ServiceProviderResponseCollection object from a json dictionary."""
args = {}
if 'service_providers' in _dict:
args['service_providers'] = [ServiceProviderResponse.from_dict(x) for x in _dict.get('service_providers')]
else:
raise ValueError('Required property \'service_providers\' not present in ServiceProviderResponseCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ServiceProviderResponseCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'service_providers') and self.service_providers is not None:
_dict['service_providers'] = [x.to_dict() for x in self.service_providers]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ServiceProviderResponseCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ServiceProviderResponseCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ServiceProviderResponseCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ServiceProviderResponseEntity():
"""
ServiceProviderResponseEntity.
:attr str name: Name of the ML service instance.
:attr str service_type:
:attr str instance_id: (optional) ID of the ML service instance (required for
Watson Machine Learning).
:attr SecretCleaned credentials: (optional)
:attr dict request_headers: (optional) Additional headers passed to the ML
engine API (for example when scoring).
:attr str operational_space_id: (optional) Reference to Operational Space.
:attr str deployment_space_id: (optional) Reference to V2 Space ID.
:attr str integrated_project_id: (optional) Project ID.
:attr List[str] group_ids: (optional) Access control list of group id of Cloud
Pak for Data (Only available for OpenScale on Cloud Pak for Data >= 4.0.6 with
ENABLE_GROUP_AUTH being true).
:attr List[str] user_ids: (optional) Access control list of user id of Cloud Pak
for Data (Only available for OpenScale on Cloud Pak for Data >= 4.0.6 with
ENABLE_GROUP_AUTH being true).
:attr Status status: (optional)
"""
def __init__(self,
name: str,
service_type: str,
*,
instance_id: str = None,
credentials: 'SecretCleaned' = None,
request_headers: dict = None,
operational_space_id: str = None,
deployment_space_id: str = None,
integrated_project_id: str = None,
group_ids: List[str] = None,
user_ids: List[str] = None,
status: 'Status' = None) -> None:
"""
Initialize a ServiceProviderResponseEntity object.
:param str name: Name of the ML service instance.
:param str service_type:
:param str instance_id: (optional) ID of the ML service instance (required
for Watson Machine Learning).
:param SecretCleaned credentials: (optional)
:param dict request_headers: (optional) Additional headers passed to the ML
engine API (for example when scoring).
:param str operational_space_id: (optional) Reference to Operational Space.
:param str deployment_space_id: (optional) Reference to V2 Space ID.
:param str integrated_project_id: (optional) Project ID.
:param List[str] group_ids: (optional) Access control list of group id of
Cloud Pak for Data (Only available for OpenScale on Cloud Pak for Data >=
4.0.6 with ENABLE_GROUP_AUTH being true).
:param List[str] user_ids: (optional) Access control list of user id of
Cloud Pak for Data (Only available for OpenScale on Cloud Pak for Data >=
4.0.6 with ENABLE_GROUP_AUTH being true).
:param Status status: (optional)
"""
self.name = name
self.service_type = service_type
self.instance_id = instance_id
self.credentials = credentials
self.request_headers = request_headers
self.operational_space_id = operational_space_id
self.deployment_space_id = deployment_space_id
self.integrated_project_id = integrated_project_id
self.group_ids = group_ids
self.user_ids = user_ids
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'ServiceProviderResponseEntity':
"""Initialize a ServiceProviderResponseEntity object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in ServiceProviderResponseEntity JSON')
if 'service_type' in _dict:
args['service_type'] = _dict.get('service_type')
else:
raise ValueError('Required property \'service_type\' not present in ServiceProviderResponseEntity JSON')
if 'instance_id' in _dict:
args['instance_id'] = _dict.get('instance_id')
if 'credentials' in _dict:
args['credentials'] = SecretCleaned.from_dict(_dict.get('credentials'))
if 'request_headers' in _dict:
args['request_headers'] = _dict.get('request_headers')
if 'operational_space_id' in _dict:
args['operational_space_id'] = _dict.get('operational_space_id')
if 'deployment_space_id' in _dict:
args['deployment_space_id'] = _dict.get('deployment_space_id')
if 'integrated_project_id' in _dict:
args['integrated_project_id'] = _dict.get('integrated_project_id')
if 'group_ids' in _dict:
args['group_ids'] = _dict.get('group_ids')
if 'user_ids' in _dict:
args['user_ids'] = _dict.get('user_ids')
if 'status' in _dict:
args['status'] = Status.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ServiceProviderResponseEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'service_type') and self.service_type is not None:
_dict['service_type'] = self.service_type
if hasattr(self, 'instance_id') and self.instance_id is not None:
_dict['instance_id'] = self.instance_id
if hasattr(self, 'credentials') and self.credentials is not None:
_dict['credentials'] = self.credentials.to_dict()
if hasattr(self, 'request_headers') and self.request_headers is not None:
_dict['request_headers'] = self.request_headers
if hasattr(self, 'operational_space_id') and self.operational_space_id is not None:
_dict['operational_space_id'] = self.operational_space_id
if hasattr(self, 'deployment_space_id') and self.deployment_space_id is not None:
_dict['deployment_space_id'] = self.deployment_space_id
if hasattr(self, 'integrated_project_id') and self.integrated_project_id is not None:
_dict['integrated_project_id'] = self.integrated_project_id
if hasattr(self, 'group_ids') and self.group_ids is not None:
_dict['group_ids'] = self.group_ids
if hasattr(self, 'user_ids') and self.user_ids is not None:
_dict['user_ids'] = self.user_ids
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ServiceProviderResponseEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ServiceProviderResponseEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ServiceProviderResponseEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ServiceTypeEnum(str, Enum):
"""
service_type.
"""
WATSON_MACHINE_LEARNING = 'watson_machine_learning'
AMAZON_SAGEMAKER = 'amazon_sagemaker'
AZURE_MACHINE_LEARNING = 'azure_machine_learning'
CUSTOM_MACHINE_LEARNING = 'custom_machine_learning'
SPSS_COLLABORATION_AND_DEPLOYMENT_SERVICES = 'spss_collaboration_and_deployment_services'
class Source():
"""
Source.
:attr str id: id of the source.
:attr str type: type of the source.
:attr List[str] metric_ids: (optional) a selection of metrics that the source
applies to (if not provided the source applies to all metrics).
:attr object data: Data representing the source. It can be any value - object,
string, number, boolean or array.
"""
def __init__(self,
id: str,
type: str,
data: object,
*,
metric_ids: List[str] = None) -> None:
"""
Initialize a Source object.
:param str id: id of the source.
:param str type: type of the source.
:param object data: Data representing the source. It can be any value -
object, string, number, boolean or array.
:param List[str] metric_ids: (optional) a selection of metrics that the
source applies to (if not provided the source applies to all metrics).
"""
self.id = id
self.type = type
self.metric_ids = metric_ids
self.data = data
@classmethod
def from_dict(cls, _dict: Dict) -> 'Source':
"""Initialize a Source object from a json dictionary."""
args = {}
if 'id' in _dict:
args['id'] = _dict.get('id')
else:
raise ValueError('Required property \'id\' not present in Source JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in Source JSON')
if 'metric_ids' in _dict:
args['metric_ids'] = _dict.get('metric_ids')
if 'data' in _dict:
args['data'] = _dict.get('data')
else:
raise ValueError('Required property \'data\' not present in Source JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Source object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'metric_ids') and self.metric_ids is not None:
_dict['metric_ids'] = self.metric_ids
if hasattr(self, 'data') and self.data is not None:
_dict['data'] = self.data
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Source object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Source') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Source') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class SparkStruct():
"""
SparkStruct.
:attr str type:
:attr List[SparkStructField] fields:
:attr str id: (optional)
:attr str name: (optional)
"""
def __init__(self,
type: str,
fields: List['SparkStructField'],
*,
id: str = None,
name: str = None) -> None:
"""
Initialize a SparkStruct object.
:param str type:
:param List[SparkStructField] fields:
:param str id: (optional)
:param str name: (optional)
"""
self.type = type
self.fields = fields
self.id = id
self.name = name
@classmethod
def from_dict(cls, _dict: Dict) -> 'SparkStruct':
"""Initialize a SparkStruct object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in SparkStruct JSON')
if 'fields' in _dict:
args['fields'] = _dict.get('fields')
else:
raise ValueError('Required property \'fields\' not present in SparkStruct JSON')
if 'id' in _dict:
args['id'] = _dict.get('id')
if 'name' in _dict:
args['name'] = _dict.get('name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SparkStruct object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'fields') and self.fields is not None:
fields_list = []
for x in self.fields:
if isinstance(x, dict):
fields_list.append(x)
else:
fields_list.append(x.to_dict())
_dict['fields'] = fields_list
if hasattr(self, 'id') and self.id is not None:
_dict['id'] = self.id
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SparkStruct object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SparkStruct') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SparkStruct') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class SparkStructField():
"""
Spark struct field.
"""
def __init__(self) -> None:
"""
Initialize a SparkStructField object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['SparkStructFieldPrimitive', 'SparkStructFieldObject']))
raise Exception(msg)
class Status():
"""
Status.
:attr str state:
:attr str deleted_at: (optional)
:attr GenericErrorResponse failure: (optional)
"""
def __init__(self,
state: str,
*,
deleted_at: str = None,
failure: 'GenericErrorResponse' = None) -> None:
"""
Initialize a Status object.
:param str state:
:param str deleted_at: (optional)
:param GenericErrorResponse failure: (optional)
"""
self.state = state
self.deleted_at = deleted_at
self.failure = failure
@classmethod
def from_dict(cls, _dict: Dict) -> 'Status':
"""Initialize a Status object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
else:
raise ValueError('Required property \'state\' not present in Status JSON')
if 'deleted_at' in _dict:
args['deleted_at'] = _dict.get('deleted_at')
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Status object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
if hasattr(self, 'deleted_at') and self.deleted_at is not None:
_dict['deleted_at'] = self.deleted_at
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Status object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Status') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Status') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
state.
"""
PREPARING = 'preparing'
ACTIVE = 'active'
DELETING = 'deleting'
PENDING_DELETE = 'pending_delete'
DISABLED = 'disabled'
ERROR = 'error'
class SubscriptionResponse():
"""
SubscriptionResponse.
:attr Metadata metadata:
:attr SubscriptionResponseEntity entity:
"""
def __init__(self,
metadata: 'Metadata',
entity: 'SubscriptionResponseEntity') -> None:
"""
Initialize a SubscriptionResponse object.
:param Metadata metadata:
:param SubscriptionResponseEntity entity:
"""
self.metadata = metadata
self.entity = entity
@classmethod
def from_dict(cls, _dict: Dict) -> 'SubscriptionResponse':
"""Initialize a SubscriptionResponse object from a json dictionary."""
args = {}
if 'metadata' in _dict:
args['metadata'] = Metadata.from_dict(_dict.get('metadata'))
else:
raise ValueError('Required property \'metadata\' not present in SubscriptionResponse JSON')
if 'entity' in _dict:
args['entity'] = SubscriptionResponseEntity.from_dict(_dict.get('entity'))
else:
raise ValueError('Required property \'entity\' not present in SubscriptionResponse JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SubscriptionResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SubscriptionResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SubscriptionResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SubscriptionResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class SubscriptionResponseCollection():
"""
SubscriptionResponseCollection.
:attr List[SubscriptionResponse] subscriptions:
"""
def __init__(self,
subscriptions: List['SubscriptionResponse']) -> None:
"""
Initialize a SubscriptionResponseCollection object.
:param List[SubscriptionResponse] subscriptions:
"""
self.subscriptions = subscriptions
@classmethod
def from_dict(cls, _dict: Dict) -> 'SubscriptionResponseCollection':
"""Initialize a SubscriptionResponseCollection object from a json dictionary."""
args = {}
if 'subscriptions' in _dict:
args['subscriptions'] = [SubscriptionResponse.from_dict(x) for x in _dict.get('subscriptions')]
else:
raise ValueError('Required property \'subscriptions\' not present in SubscriptionResponseCollection JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SubscriptionResponseCollection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'subscriptions') and self.subscriptions is not None:
_dict['subscriptions'] = [x.to_dict() for x in self.subscriptions]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SubscriptionResponseCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SubscriptionResponseCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SubscriptionResponseCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class SubscriptionResponseEntity():
"""
SubscriptionResponseEntity.
:attr str data_mart_id:
:attr str service_provider_id:
:attr Asset asset:
:attr AssetProperties asset_properties: (optional) Additional asset properties
(subject of discovery if not provided when creating the subscription).
:attr AssetDeployment deployment:
:attr IntegratedSystemReference integration_reference: (optional) Integrated
System reference.
:attr RiskEvaluationStatus risk_evaluation_status: (optional)
:attr AnalyticsEngine analytics_engine: (optional)
:attr List[DataSource] data_sources: (optional)
:attr List[EmbeddingsProvider] embeddings_providers: (optional)
:attr Status status: (optional)
"""
def __init__(self,
data_mart_id: str,
service_provider_id: str,
asset: 'Asset',
deployment: 'AssetDeployment',
*,
asset_properties: 'AssetProperties' = None,
integration_reference: 'IntegratedSystemReference' = None,
risk_evaluation_status: 'RiskEvaluationStatus' = None,
analytics_engine: 'AnalyticsEngine' = None,
data_sources: List['DataSource'] = None,
embeddings_providers: List['EmbeddingsProvider'] = None,
status: 'Status' = None) -> None:
"""
Initialize a SubscriptionResponseEntity object.
:param str data_mart_id:
:param str service_provider_id:
:param Asset asset:
:param AssetDeployment deployment:
:param AssetProperties asset_properties: (optional) Additional asset
properties (subject of discovery if not provided when creating the
subscription).
:param IntegratedSystemReference integration_reference: (optional)
Integrated System reference.
:param RiskEvaluationStatus risk_evaluation_status: (optional)
:param AnalyticsEngine analytics_engine: (optional)
:param List[DataSource] data_sources: (optional)
:param List[EmbeddingsProvider] embeddings_providers: (optional)
:param Status status: (optional)
"""
self.data_mart_id = data_mart_id
self.service_provider_id = service_provider_id
self.asset = asset
self.asset_properties = asset_properties
self.deployment = deployment
self.integration_reference = integration_reference
self.risk_evaluation_status = risk_evaluation_status
self.analytics_engine = analytics_engine
self.data_sources = data_sources
self.embeddings_providers = embeddings_providers
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'SubscriptionResponseEntity':
"""Initialize a SubscriptionResponseEntity object from a json dictionary."""
args = {}
if 'data_mart_id' in _dict:
args['data_mart_id'] = _dict.get('data_mart_id')
else:
raise ValueError('Required property \'data_mart_id\' not present in SubscriptionResponseEntity JSON')
if 'service_provider_id' in _dict:
args['service_provider_id'] = _dict.get('service_provider_id')
else:
raise ValueError('Required property \'service_provider_id\' not present in SubscriptionResponseEntity JSON')
if 'asset' in _dict:
args['asset'] = Asset.from_dict(_dict.get('asset'))
else:
raise ValueError('Required property \'asset\' not present in SubscriptionResponseEntity JSON')
if 'asset_properties' in _dict:
args['asset_properties'] = AssetProperties.from_dict(_dict.get('asset_properties'))
if 'deployment' in _dict:
args['deployment'] = AssetDeployment.from_dict(_dict.get('deployment'))
else:
raise ValueError('Required property \'deployment\' not present in SubscriptionResponseEntity JSON')
if 'integration_reference' in _dict:
args['integration_reference'] = IntegratedSystemReference.from_dict(_dict.get('integration_reference'))
if 'risk_evaluation_status' in _dict:
args['risk_evaluation_status'] = RiskEvaluationStatus.from_dict(_dict.get('risk_evaluation_status'))
if 'analytics_engine' in _dict:
args['analytics_engine'] = AnalyticsEngine.from_dict(_dict.get('analytics_engine'))
if 'data_sources' in _dict:
args['data_sources'] = [DataSource.from_dict(x) for x in _dict.get('data_sources')]
if 'embeddings_providers' in _dict:
args['embeddings_providers'] = [EmbeddingsProvider.from_dict(x) for x in _dict.get('embeddings_providers')]
if 'status' in _dict:
args['status'] = Status.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SubscriptionResponseEntity object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'data_mart_id') and self.data_mart_id is not None:
_dict['data_mart_id'] = self.data_mart_id
if hasattr(self, 'service_provider_id') and self.service_provider_id is not None:
_dict['service_provider_id'] = self.service_provider_id
if hasattr(self, 'asset') and self.asset is not None:
_dict['asset'] = self.asset.to_dict()
if hasattr(self, 'asset_properties') and self.asset_properties is not None:
_dict['asset_properties'] = self.asset_properties.to_dict()
if hasattr(self, 'deployment') and self.deployment is not None:
_dict['deployment'] = self.deployment.to_dict()
if hasattr(self, 'integration_reference') and self.integration_reference is not None:
_dict['integration_reference'] = self.integration_reference.to_dict()
if hasattr(self, 'risk_evaluation_status') and self.risk_evaluation_status is not None:
_dict['risk_evaluation_status'] = self.risk_evaluation_status.to_dict()
if hasattr(self, 'analytics_engine') and self.analytics_engine is not None:
_dict['analytics_engine'] = self.analytics_engine.to_dict()
if hasattr(self, 'data_sources') and self.data_sources is not None:
_dict['data_sources'] = [x.to_dict() for x in self.data_sources]
if hasattr(self, 'embeddings_providers') and self.embeddings_providers is not None:
_dict['embeddings_providers'] = [x.to_dict() for x in self.embeddings_providers]
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SubscriptionResponseEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SubscriptionResponseEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SubscriptionResponseEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class Target():
"""
Target.
:attr str target_type: Type of the target (e.g. subscription, ...).
:attr str target_id: ID of the data set target (e.g. subscription ID, ...).
"""
def __init__(self,
target_type: str,
target_id: str) -> None:
"""
Initialize a Target object.
:param str target_type: Type of the target (e.g. subscription, ...).
:param str target_id: ID of the data set target (e.g. subscription ID,
...).
"""
self.target_type = target_type
self.target_id = target_id
@classmethod
def from_dict(cls, _dict: Dict) -> 'Target':
"""Initialize a Target object from a json dictionary."""
args = {}
if 'target_type' in _dict:
args['target_type'] = _dict.get('target_type')
else:
raise ValueError('Required property \'target_type\' not present in Target JSON')
if 'target_id' in _dict:
args['target_id'] = _dict.get('target_id')
else:
raise ValueError('Required property \'target_id\' not present in Target JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Target object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'target_type') and self.target_type is not None:
_dict['target_type'] = self.target_type
if hasattr(self, 'target_id') and self.target_id is not None:
_dict['target_id'] = self.target_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Target object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Target') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Target') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TargetTypeEnum(str, Enum):
"""
Type of the target (e.g. subscription, ...).
"""
SUBSCRIPTION = 'subscription'
INSTANCE = 'instance'
DATA_MART = 'data_mart'
PROJECT = 'project'
SPACE = 'space'
AI_DECISION_COORDINATION = 'ai_decision_coordination'
GEN_AI_APP = 'gen_ai_app'
WXO = 'wxo'
class ThresholdConditionObject():
"""
ThresholdConditionObject.
:attr str type:
:attr str key:
:attr str value:
"""
def __init__(self,
type: str,
key: str,
value: str) -> None:
"""
Initialize a ThresholdConditionObject object.
:param str type:
:param str key:
:param str value:
"""
self.type = type
self.key = key
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'ThresholdConditionObject':
"""Initialize a ThresholdConditionObject object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in ThresholdConditionObject JSON')
if 'key' in _dict:
args['key'] = _dict.get('key')
else:
raise ValueError('Required property \'key\' not present in ThresholdConditionObject JSON')
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError('Required property \'value\' not present in ThresholdConditionObject JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ThresholdConditionObject object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'key') and self.key is not None:
_dict['key'] = self.key
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ThresholdConditionObject object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ThresholdConditionObject') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ThresholdConditionObject') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
type.
"""
TAG = 'tag'
class TrainingDataReference():
"""
TrainingDataReference.
:attr str type: Type of the storage.
:attr TrainingDataReferenceLocation location: training data set location.
:attr TrainingDataReferenceConnection connection: training data set connection
credentials.
:attr str name: (optional)
"""
def __init__(self,
type: str,
location: 'TrainingDataReferenceLocation',
connection: 'TrainingDataReferenceConnection',
*,
name: str = None) -> None:
"""
Initialize a TrainingDataReference object.
:param str type: Type of the storage.
:param TrainingDataReferenceLocation location: training data set location.
:param TrainingDataReferenceConnection connection: training data set
connection credentials.
:param str name: (optional)
"""
self.type = type
self.location = location
self.connection = connection
self.name = name
@classmethod
def from_dict(cls, _dict: Dict) -> 'TrainingDataReference':
"""Initialize a TrainingDataReference object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in TrainingDataReference JSON')
if 'location' in _dict:
args['location'] = _dict.get('location')
else:
raise ValueError('Required property \'location\' not present in TrainingDataReference JSON')
if 'connection' in _dict:
args['connection'] = _dict.get('connection')
else:
raise ValueError('Required property \'connection\' not present in TrainingDataReference JSON')
if 'name' in _dict:
args['name'] = _dict.get('name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a TrainingDataReference object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'location') and self.location is not None:
if isinstance(self.location, dict):
_dict['location'] = self.location
else:
_dict['location'] = self.location.to_dict()
if hasattr(self, 'connection') and self.connection is not None:
if isinstance(self.connection, dict):
_dict['connection'] = self.connection
else:
_dict['connection'] = self.connection.to_dict()
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this TrainingDataReference object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'TrainingDataReference') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'TrainingDataReference') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class TypeEnum(str, Enum):
"""
Type of the storage.
"""
DB2 = 'db2'
POSTGRESQL = 'postgresql'
COS = 'cos'
S3 = 's3'
DATASET = 'dataset'
FILE_ASSET = 'file_asset'
class TrainingDataReferenceConnection():
"""
training data set connection credentials.
"""
def __init__(self) -> None:
"""
Initialize a TrainingDataReferenceConnection object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['DB2TrainingDataReferenceConnection', 'PostgresqlTrainingDataReferenceConnection', 'COSTrainingDataReferenceConnection', 'S3TrainingDataReferenceConnection']))
raise Exception(msg)
class TrainingDataReferenceLocation():
"""
training data set location.
"""
def __init__(self) -> None:
"""
Initialize a TrainingDataReferenceLocation object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['DB2TrainingDataReferenceLocation', 'PostgresqlTrainingDataReferenceLocation', 'COSTrainingDataReferenceLocation', 'S3TrainingDataReferenceLocation', 'DatasetTrainingDataReferenceLocation', 'FileAssetTrainingDataReferenceLocation']))
raise Exception(msg)
class UploadTracesGenAIAppResponse():
"""
The response object for successful acceptance of traces upload request for gen_ai_app.
:attr str gen_ai_app_id: (optional)
:attr str start_time: (optional) The date-timestamp when the upload traces was
started.
:attr str end_time: (optional) The date-timestamp when the upload traces ended.
:attr UploadTracesGenAIAppResponseStatus status: (optional) The status of the
upload traces for gen_ai_app.
"""
def __init__(self,
*,
gen_ai_app_id: str = None,
start_time: str = None,
end_time: str = None,
status: 'UploadTracesGenAIAppResponseStatus' = None) -> None:
"""
Initialize a UploadTracesGenAIAppResponse object.
:param str gen_ai_app_id: (optional)
:param str start_time: (optional) The date-timestamp when the upload traces
was started.
:param str end_time: (optional) The date-timestamp when the upload traces
ended.
:param UploadTracesGenAIAppResponseStatus status: (optional) The status of
the upload traces for gen_ai_app.
"""
self.gen_ai_app_id = gen_ai_app_id
self.start_time = start_time
self.end_time = end_time
self.status = status
@classmethod
def from_dict(cls, _dict: Dict) -> 'UploadTracesGenAIAppResponse':
"""Initialize a UploadTracesGenAIAppResponse object from a json dictionary."""
args = {}
if 'gen_ai_app_id' in _dict:
args['gen_ai_app_id'] = _dict.get('gen_ai_app_id')
if 'start_time' in _dict:
args['start_time'] = _dict.get('start_time')
if 'end_time' in _dict:
args['end_time'] = _dict.get('end_time')
if 'status' in _dict:
args['status'] = UploadTracesGenAIAppResponseStatus.from_dict(_dict.get('status'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a UploadTracesGenAIAppResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'gen_ai_app_id') and self.gen_ai_app_id is not None:
_dict['gen_ai_app_id'] = self.gen_ai_app_id
if hasattr(self, 'start_time') and self.start_time is not None:
_dict['start_time'] = self.start_time
if hasattr(self, 'end_time') and self.end_time is not None:
_dict['end_time'] = self.end_time
if hasattr(self, 'status') and self.status is not None:
_dict['status'] = self.status.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this UploadTracesGenAIAppResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'UploadTracesGenAIAppResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'UploadTracesGenAIAppResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class UploadTracesGenAIAppResponseStatus():
"""
The status of the upload traces for gen_ai_app.
:attr str state: The upload traces state.
:attr GenericErrorResponse failure: (optional)
"""
def __init__(self,
state: str,
*,
failure: 'GenericErrorResponse' = None) -> None:
"""
Initialize a UploadTracesGenAIAppResponseStatus object.
:param str state: The upload traces state.
:param GenericErrorResponse failure: (optional)
"""
self.state = state
self.failure = failure
@classmethod
def from_dict(cls, _dict: Dict) -> 'UploadTracesGenAIAppResponseStatus':
"""Initialize a UploadTracesGenAIAppResponseStatus object from a json dictionary."""
args = {}
if 'state' in _dict:
args['state'] = _dict.get('state')
else:
raise ValueError('Required property \'state\' not present in UploadTracesGenAIAppResponseStatus JSON')
if 'failure' in _dict:
args['failure'] = GenericErrorResponse.from_dict(_dict.get('failure'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a UploadTracesGenAIAppResponseStatus object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'state') and self.state is not None:
_dict['state'] = self.state
if hasattr(self, 'failure') and self.failure is not None:
_dict['failure'] = self.failure.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this UploadTracesGenAIAppResponseStatus object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'UploadTracesGenAIAppResponseStatus') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'UploadTracesGenAIAppResponseStatus') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class StateEnum(str, Enum):
"""
The upload traces state.
"""
RUNNING = 'RUNNING'
ERROR = 'ERROR'
FINISHED = 'FINISHED'
class UserPreferencesGetResponse():
"""
UserPreferencesGetResponse.
"""
def __init__(self) -> None:
"""
Initialize a UserPreferencesGetResponse object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['UserPreferencesGetResponseUserPreferenceValueObject', 'UserPreferencesGetResponseUserPreferenceValueString']))
raise Exception(msg)
class UserPreferencesPatchResponse():
"""
UserPreferencesPatchResponse.
"""
def __init__(self) -> None:
"""
Initialize a UserPreferencesPatchResponse object.
"""
@classmethod
def from_dict(cls, _dict: Dict) -> 'UserPreferencesPatchResponse':
"""Initialize a UserPreferencesPatchResponse object from a json dictionary."""
return cls(**_dict)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a UserPreferencesPatchResponse object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
return vars(self)
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this UserPreferencesPatchResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'UserPreferencesPatchResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'UserPreferencesPatchResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class UserPreferencesUpdateRequest():
"""
UserPreferencesUpdateRequest.
"""
def __init__(self) -> None:
"""
Initialize a UserPreferencesUpdateRequest object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['UserPreferencesUpdateRequestUserPreferenceValueObject', 'UserPreferencesUpdateRequestUserPreferenceValueString']))
raise Exception(msg)
class DetectorPropertyDefaultValue():
"""
Default value for the property (optional, type depends on property type).
"""
def __init__(self) -> None:
"""
Initialize a DetectorPropertyDefaultValue object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join(['DetectorPropertyDefaultValueDetectorPropertyDefaultValueString', 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber', 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean']))
raise Exception(msg)
[docs]
class AzureCredentials(MLCredentials):
"""
AzureCredentials.
:attr str token: (optional)
:attr str username: (optional)
:attr str password: (optional)
:attr str subscription_id: (optional)
:attr str client_id: (optional)
:attr str client_secret: (optional)
:attr str tenant: (optional)
:attr List[AzureWorkspaceCredentials] workspaces: (optional)
"""
# The set of defined properties for the class
_properties = frozenset(['token', 'username', 'password', 'subscription_id', 'client_id', 'client_secret', 'tenant', 'workspaces'])
def __init__(self,
*,
token: str = None,
username: str = None,
password: str = None,
subscription_id: str = None,
client_id: str = None,
client_secret: str = None,
tenant: str = None,
workspaces: List['AzureWorkspaceCredentials'] = None,
**kwargs) -> None:
"""
Initialize a AzureCredentials object.
:param str token: (optional)
:param str username: (optional)
:param str password: (optional)
:param str subscription_id: (optional)
:param str client_id: (optional)
:param str client_secret: (optional)
:param str tenant: (optional)
:param List[AzureWorkspaceCredentials] workspaces: (optional)
:param **kwargs: (optional) Any additional properties.
"""
# pylint: disable=super-init-not-called
self.token = token
self.username = username
self.password = password
self.subscription_id = subscription_id
self.client_id = client_id
self.client_secret = client_secret
self.tenant = tenant
self.workspaces = workspaces
for _key, _value in kwargs.items():
setattr(self, _key, _value)
@classmethod
def from_dict(cls, _dict: Dict) -> 'AzureCredentials':
"""Initialize a AzureCredentials object from a json dictionary."""
args = {}
if 'token' in _dict:
args['token'] = _dict.get('token')
if 'username' in _dict:
args['username'] = _dict.get('username')
if 'password' in _dict:
args['password'] = _dict.get('password')
if 'subscription_id' in _dict:
args['subscription_id'] = _dict.get('subscription_id')
if 'client_id' in _dict:
args['client_id'] = _dict.get('client_id')
if 'client_secret' in _dict:
args['client_secret'] = _dict.get('client_secret')
if 'tenant' in _dict:
args['tenant'] = _dict.get('tenant')
if 'workspaces' in _dict:
args['workspaces'] = [AzureWorkspaceCredentials.from_dict(x) for x in _dict.get('workspaces')]
args.update({k:v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a AzureCredentials object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'token') and self.token is not None:
_dict['token'] = self.token
if hasattr(self, 'username') and self.username is not None:
_dict['username'] = self.username
if hasattr(self, 'password') and self.password is not None:
_dict['password'] = self.password
if hasattr(self, 'subscription_id') and self.subscription_id is not None:
_dict['subscription_id'] = self.subscription_id
if hasattr(self, 'client_id') and self.client_id is not None:
_dict['client_id'] = self.client_id
if hasattr(self, 'client_secret') and self.client_secret is not None:
_dict['client_secret'] = self.client_secret
if hasattr(self, 'tenant') and self.tenant is not None:
_dict['tenant'] = self.tenant
if hasattr(self, 'workspaces') and self.workspaces is not None:
_dict['workspaces'] = [x.to_dict() for x in self.workspaces]
for _key in [k for k in vars(self).keys() if k not in AzureCredentials._properties]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this AzureCredentials object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'AzureCredentials') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'AzureCredentials') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class COSTrainingDataReferenceConnection(TrainingDataReferenceConnection):
"""
COSTrainingDataReferenceConnection.
:attr str resource_instance_id:
:attr str url:
:attr str api_key:
:attr str iam_url: (optional)
"""
def __init__(self,
resource_instance_id: str,
url: str,
api_key: str,
*,
iam_url: str = None) -> None:
"""
Initialize a COSTrainingDataReferenceConnection object.
:param str resource_instance_id:
:param str url:
:param str api_key:
:param str iam_url: (optional)
"""
# pylint: disable=super-init-not-called
self.resource_instance_id = resource_instance_id
self.url = url
self.api_key = api_key
self.iam_url = iam_url
@classmethod
def from_dict(cls, _dict: Dict) -> 'COSTrainingDataReferenceConnection':
"""Initialize a COSTrainingDataReferenceConnection object from a json dictionary."""
args = {}
if 'resource_instance_id' in _dict:
args['resource_instance_id'] = _dict.get('resource_instance_id')
else:
raise ValueError('Required property \'resource_instance_id\' not present in COSTrainingDataReferenceConnection JSON')
if 'url' in _dict:
args['url'] = _dict.get('url')
else:
raise ValueError('Required property \'url\' not present in COSTrainingDataReferenceConnection JSON')
if 'api_key' in _dict:
args['api_key'] = _dict.get('api_key')
else:
raise ValueError('Required property \'api_key\' not present in COSTrainingDataReferenceConnection JSON')
if 'iam_url' in _dict:
args['iam_url'] = _dict.get('iam_url')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a COSTrainingDataReferenceConnection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'resource_instance_id') and self.resource_instance_id is not None:
_dict['resource_instance_id'] = self.resource_instance_id
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'api_key') and self.api_key is not None:
_dict['api_key'] = self.api_key
if hasattr(self, 'iam_url') and self.iam_url is not None:
_dict['iam_url'] = self.iam_url
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this COSTrainingDataReferenceConnection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'COSTrainingDataReferenceConnection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'COSTrainingDataReferenceConnection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class COSTrainingDataReferenceLocation(TrainingDataReferenceLocation):
"""
COS file location.
:attr str bucket:
:attr str file_name:
:attr bool firstlineheader: (optional)
:attr str infer_schema: (optional)
:attr str file_format: (optional)
"""
def __init__(self,
bucket: str,
file_name: str,
*,
firstlineheader: bool = None,
infer_schema: str = None,
file_format: str = None) -> None:
"""
Initialize a COSTrainingDataReferenceLocation object.
:param str bucket:
:param str file_name:
:param bool firstlineheader: (optional)
:param str infer_schema: (optional)
:param str file_format: (optional)
"""
# pylint: disable=super-init-not-called
self.bucket = bucket
self.file_name = file_name
self.firstlineheader = firstlineheader
self.infer_schema = infer_schema
self.file_format = file_format
@classmethod
def from_dict(cls, _dict: Dict) -> 'COSTrainingDataReferenceLocation':
"""Initialize a COSTrainingDataReferenceLocation object from a json dictionary."""
args = {}
if 'bucket' in _dict:
args['bucket'] = _dict.get('bucket')
else:
raise ValueError('Required property \'bucket\' not present in COSTrainingDataReferenceLocation JSON')
if 'file_name' in _dict:
args['file_name'] = _dict.get('file_name')
else:
raise ValueError('Required property \'file_name\' not present in COSTrainingDataReferenceLocation JSON')
if 'firstlineheader' in _dict:
args['firstlineheader'] = _dict.get('firstlineheader')
if 'infer_schema' in _dict:
args['infer_schema'] = _dict.get('infer_schema')
if 'file_format' in _dict:
args['file_format'] = _dict.get('file_format')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a COSTrainingDataReferenceLocation object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'bucket') and self.bucket is not None:
_dict['bucket'] = self.bucket
if hasattr(self, 'file_name') and self.file_name is not None:
_dict['file_name'] = self.file_name
if hasattr(self, 'firstlineheader') and self.firstlineheader is not None:
_dict['firstlineheader'] = self.firstlineheader
if hasattr(self, 'infer_schema') and self.infer_schema is not None:
_dict['infer_schema'] = self.infer_schema
if hasattr(self, 'file_format') and self.file_format is not None:
_dict['file_format'] = self.file_format
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this COSTrainingDataReferenceLocation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'COSTrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'COSTrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class FileFormatEnum(str, Enum):
"""
file_format.
"""
CSV = 'csv'
[docs]
class CustomCredentials(MLCredentials):
"""
CustomCredentials.
:attr str url: (optional)
:attr str username: (optional)
:attr str password: (optional)
:attr str apikey: (optional)
:attr str auth_url: (optional)
:attr str auth_type: (optional)
:attr str auth_provider: (optional)
"""
# The set of defined properties for the class
_properties = frozenset(['url', 'username', 'password', 'apikey', 'auth_url', 'auth_type', 'auth_provider'])
def __init__(self,
*,
url: str = None,
username: str = None,
password: str = None,
apikey: str = None,
auth_url: str = None,
auth_type: str = None,
auth_provider: str = None,
**kwargs) -> None:
"""
Initialize a CustomCredentials object.
:param str url: (optional)
:param str username: (optional)
:param str password: (optional)
:param str apikey: (optional)
:param str auth_url: (optional)
:param str auth_type: (optional)
:param str auth_provider: (optional)
:param **kwargs: (optional) Any additional properties.
"""
# pylint: disable=super-init-not-called
self.url = url
self.username = username
self.password = password
self.apikey = apikey
self.auth_url = auth_url
self.auth_type = auth_type
self.auth_provider = auth_provider
for _key, _value in kwargs.items():
setattr(self, _key, _value)
@classmethod
def from_dict(cls, _dict: Dict) -> 'CustomCredentials':
"""Initialize a CustomCredentials object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'username' in _dict:
args['username'] = _dict.get('username')
if 'password' in _dict:
args['password'] = _dict.get('password')
if 'apikey' in _dict:
args['apikey'] = _dict.get('apikey')
if 'auth_url' in _dict:
args['auth_url'] = _dict.get('auth_url')
if 'auth_type' in _dict:
args['auth_type'] = _dict.get('auth_type')
if 'auth_provider' in _dict:
args['auth_provider'] = _dict.get('auth_provider')
args.update({k:v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a CustomCredentials object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'username') and self.username is not None:
_dict['username'] = self.username
if hasattr(self, 'password') and self.password is not None:
_dict['password'] = self.password
if hasattr(self, 'apikey') and self.apikey is not None:
_dict['apikey'] = self.apikey
if hasattr(self, 'auth_url') and self.auth_url is not None:
_dict['auth_url'] = self.auth_url
if hasattr(self, 'auth_type') and self.auth_type is not None:
_dict['auth_type'] = self.auth_type
if hasattr(self, 'auth_provider') and self.auth_provider is not None:
_dict['auth_provider'] = self.auth_provider
for _key in [k for k in vars(self).keys() if k not in CustomCredentials._properties]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this CustomCredentials object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'CustomCredentials') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'CustomCredentials') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class AuthTypeEnum(str, Enum):
"""
auth_type.
"""
BASIC = 'basic'
API_KEY = 'api_key'
[docs]
class AuthProviderEnum(str, Enum):
"""
auth_provider.
"""
CLOUD = 'cloud'
CPD = 'cpd'
MCSP = 'mcsp'
class DB2TrainingDataReferenceConnection(TrainingDataReferenceConnection):
"""
DB2TrainingDataReferenceConnection.
:attr str hostname:
:attr str username:
:attr str password:
:attr str database_name:
:attr int port: (optional)
:attr bool ssl: (optional)
:attr str certificate_base64: (optional) DER-encoded certificate in Base64
encoding. The decoded content must be bound at the beginning by -----BEGIN
CERTIFICATE----- and at the end by -----END CERTIFICATE-----.
:attr str connection_string: (optional)
"""
def __init__(self,
hostname: str,
username: str,
password: str,
database_name: str,
*,
port: int = None,
ssl: bool = None,
certificate_base64: str = None,
connection_string: str = None) -> None:
"""
Initialize a DB2TrainingDataReferenceConnection object.
:param str hostname:
:param str username:
:param str password:
:param str database_name:
:param int port: (optional)
:param bool ssl: (optional)
:param str certificate_base64: (optional) DER-encoded certificate in Base64
encoding. The decoded content must be bound at the beginning by -----BEGIN
CERTIFICATE----- and at the end by -----END CERTIFICATE-----.
:param str connection_string: (optional)
"""
# pylint: disable=super-init-not-called
self.hostname = hostname
self.username = username
self.password = password
self.database_name = database_name
self.port = port
self.ssl = ssl
self.certificate_base64 = certificate_base64
self.connection_string = connection_string
@classmethod
def from_dict(cls, _dict: Dict) -> 'DB2TrainingDataReferenceConnection':
"""Initialize a DB2TrainingDataReferenceConnection object from a json dictionary."""
args = {}
if 'hostname' in _dict:
args['hostname'] = _dict.get('hostname')
else:
raise ValueError('Required property \'hostname\' not present in DB2TrainingDataReferenceConnection JSON')
if 'username' in _dict:
args['username'] = _dict.get('username')
else:
raise ValueError('Required property \'username\' not present in DB2TrainingDataReferenceConnection JSON')
if 'password' in _dict:
args['password'] = _dict.get('password')
else:
raise ValueError('Required property \'password\' not present in DB2TrainingDataReferenceConnection JSON')
if 'database_name' in _dict:
args['database_name'] = _dict.get('database_name')
else:
raise ValueError('Required property \'database_name\' not present in DB2TrainingDataReferenceConnection JSON')
if 'port' in _dict:
args['port'] = _dict.get('port')
if 'ssl' in _dict:
args['ssl'] = _dict.get('ssl')
if 'certificate_base64' in _dict:
args['certificate_base64'] = _dict.get('certificate_base64')
if 'connection_string' in _dict:
args['connection_string'] = _dict.get('connection_string')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DB2TrainingDataReferenceConnection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'hostname') and self.hostname is not None:
_dict['hostname'] = self.hostname
if hasattr(self, 'username') and self.username is not None:
_dict['username'] = self.username
if hasattr(self, 'password') and self.password is not None:
_dict['password'] = self.password
if hasattr(self, 'database_name') and self.database_name is not None:
_dict['database_name'] = self.database_name
if hasattr(self, 'port') and self.port is not None:
_dict['port'] = self.port
if hasattr(self, 'ssl') and self.ssl is not None:
_dict['ssl'] = self.ssl
if hasattr(self, 'certificate_base64') and self.certificate_base64 is not None:
_dict['certificate_base64'] = self.certificate_base64
if hasattr(self, 'connection_string') and self.connection_string is not None:
_dict['connection_string'] = self.connection_string
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DB2TrainingDataReferenceConnection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DB2TrainingDataReferenceConnection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DB2TrainingDataReferenceConnection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DB2TrainingDataReferenceLocation(TrainingDataReferenceLocation):
"""
DB2 table name.
:attr str table_name: name of the table.
:attr str schema_name: (optional) name of the schema.
"""
def __init__(self,
table_name: str,
*,
schema_name: str = None) -> None:
"""
Initialize a DB2TrainingDataReferenceLocation object.
:param str table_name: name of the table.
:param str schema_name: (optional) name of the schema.
"""
# pylint: disable=super-init-not-called
self.table_name = table_name
self.schema_name = schema_name
@classmethod
def from_dict(cls, _dict: Dict) -> 'DB2TrainingDataReferenceLocation':
"""Initialize a DB2TrainingDataReferenceLocation object from a json dictionary."""
args = {}
if 'table_name' in _dict:
args['table_name'] = _dict.get('table_name')
else:
raise ValueError('Required property \'table_name\' not present in DB2TrainingDataReferenceLocation JSON')
if 'schema_name' in _dict:
args['schema_name'] = _dict.get('schema_name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DB2TrainingDataReferenceLocation object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'table_name') and self.table_name is not None:
_dict['table_name'] = self.table_name
if hasattr(self, 'schema_name') and self.schema_name is not None:
_dict['schema_name'] = self.schema_name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DB2TrainingDataReferenceLocation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DB2TrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DB2TrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DatasetTrainingDataReferenceLocation(TrainingDataReferenceLocation):
"""
WOS dataset id.
:attr str dataset_id: Dataset id.
:attr FileTrainingDataReferenceOptions meta: (optional) additional options for
different types of training data references.
"""
def __init__(self,
dataset_id: str,
*,
meta: 'FileTrainingDataReferenceOptions' = None) -> None:
"""
Initialize a DatasetTrainingDataReferenceLocation object.
:param str dataset_id: Dataset id.
:param FileTrainingDataReferenceOptions meta: (optional) additional options
for different types of training data references.
"""
# pylint: disable=super-init-not-called
self.dataset_id = dataset_id
self.meta = meta
@classmethod
def from_dict(cls, _dict: Dict) -> 'DatasetTrainingDataReferenceLocation':
"""Initialize a DatasetTrainingDataReferenceLocation object from a json dictionary."""
args = {}
if 'dataset_id' in _dict:
args['dataset_id'] = _dict.get('dataset_id')
else:
raise ValueError('Required property \'dataset_id\' not present in DatasetTrainingDataReferenceLocation JSON')
if 'meta' in _dict:
args['meta'] = FileTrainingDataReferenceOptions.from_dict(_dict.get('meta'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DatasetTrainingDataReferenceLocation object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'dataset_id') and self.dataset_id is not None:
_dict['dataset_id'] = self.dataset_id
if hasattr(self, 'meta') and self.meta is not None:
_dict['meta'] = self.meta.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DatasetTrainingDataReferenceLocation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DatasetTrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DatasetTrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class FileAssetTrainingDataReferenceLocation(TrainingDataReferenceLocation):
"""
File data asset reference location.
:attr str project_id: (optional) Project id.
:attr str asset_id: (optional) File data asset id.
:attr str asset_href: File data asset reference.
:attr FileTrainingDataReferenceOptions meta: (optional) additional options for
different types of training data references.
"""
def __init__(self,
asset_href: str,
*,
project_id: str = None,
asset_id: str = None,
meta: 'FileTrainingDataReferenceOptions' = None) -> None:
"""
Initialize a FileAssetTrainingDataReferenceLocation object.
:param str asset_href: File data asset reference.
:param str project_id: (optional) Project id.
:param str asset_id: (optional) File data asset id.
:param FileTrainingDataReferenceOptions meta: (optional) additional options
for different types of training data references.
"""
# pylint: disable=super-init-not-called
self.project_id = project_id
self.asset_id = asset_id
self.asset_href = asset_href
self.meta = meta
@classmethod
def from_dict(cls, _dict: Dict) -> 'FileAssetTrainingDataReferenceLocation':
"""Initialize a FileAssetTrainingDataReferenceLocation object from a json dictionary."""
args = {}
if 'project_id' in _dict:
args['project_id'] = _dict.get('project_id')
if 'asset_id' in _dict:
args['asset_id'] = _dict.get('asset_id')
if 'asset_href' in _dict:
args['asset_href'] = _dict.get('asset_href')
else:
raise ValueError('Required property \'asset_href\' not present in FileAssetTrainingDataReferenceLocation JSON')
if 'meta' in _dict:
args['meta'] = FileTrainingDataReferenceOptions.from_dict(_dict.get('meta'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a FileAssetTrainingDataReferenceLocation object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'project_id') and self.project_id is not None:
_dict['project_id'] = self.project_id
if hasattr(self, 'asset_id') and self.asset_id is not None:
_dict['asset_id'] = self.asset_id
if hasattr(self, 'asset_href') and self.asset_href is not None:
_dict['asset_href'] = self.asset_href
if hasattr(self, 'meta') and self.meta is not None:
_dict['meta'] = self.meta.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this FileAssetTrainingDataReferenceLocation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'FileAssetTrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'FileAssetTrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class MLCredentialsWXOCredentials(MLCredentials):
"""
Currently this must be empty object, but present.
"""
def __init__(self,
**kwargs) -> None:
"""
Initialize a MLCredentialsWXOCredentials object.
:param **kwargs: (optional) Any additional properties.
"""
# pylint: disable=super-init-not-called
for _key, _value in kwargs.items():
setattr(self, _key, _value)
@classmethod
def from_dict(cls, _dict: Dict) -> 'MLCredentialsWXOCredentials':
"""Initialize a MLCredentialsWXOCredentials object from a json dictionary."""
return cls(**_dict)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MLCredentialsWXOCredentials object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
return vars(self)
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MLCredentialsWXOCredentials object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MLCredentialsWXOCredentials') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MLCredentialsWXOCredentials') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class PostgresqlTrainingDataReferenceConnection(TrainingDataReferenceConnection):
"""
PostgresqlTrainingDataReferenceConnection.
:attr str hostname:
:attr str username:
:attr str password:
:attr str database_name:
:attr int port: (optional)
:attr bool ssl: (optional)
:attr str ssl_mode: (optional)
:attr str certificate_base64: (optional) DER-encoded certificate in Base64
encoding. The decoded content must be bound at the beginning by -----BEGIN
CERTIFICATE----- and at the end by -----END CERTIFICATE-----.
:attr str connection_string: (optional) connection string of database.
"""
def __init__(self,
hostname: str,
username: str,
password: str,
database_name: str,
*,
port: int = None,
ssl: bool = None,
ssl_mode: str = None,
certificate_base64: str = None,
connection_string: str = None) -> None:
"""
Initialize a PostgresqlTrainingDataReferenceConnection object.
:param str hostname:
:param str username:
:param str password:
:param str database_name:
:param int port: (optional)
:param bool ssl: (optional)
:param str ssl_mode: (optional)
:param str certificate_base64: (optional) DER-encoded certificate in Base64
encoding. The decoded content must be bound at the beginning by -----BEGIN
CERTIFICATE----- and at the end by -----END CERTIFICATE-----.
:param str connection_string: (optional) connection string of database.
"""
# pylint: disable=super-init-not-called
self.hostname = hostname
self.username = username
self.password = password
self.database_name = database_name
self.port = port
self.ssl = ssl
self.ssl_mode = ssl_mode
self.certificate_base64 = certificate_base64
self.connection_string = connection_string
@classmethod
def from_dict(cls, _dict: Dict) -> 'PostgresqlTrainingDataReferenceConnection':
"""Initialize a PostgresqlTrainingDataReferenceConnection object from a json dictionary."""
args = {}
if 'hostname' in _dict:
args['hostname'] = _dict.get('hostname')
else:
raise ValueError('Required property \'hostname\' not present in PostgresqlTrainingDataReferenceConnection JSON')
if 'username' in _dict:
args['username'] = _dict.get('username')
else:
raise ValueError('Required property \'username\' not present in PostgresqlTrainingDataReferenceConnection JSON')
if 'password' in _dict:
args['password'] = _dict.get('password')
else:
raise ValueError('Required property \'password\' not present in PostgresqlTrainingDataReferenceConnection JSON')
if 'database_name' in _dict:
args['database_name'] = _dict.get('database_name')
else:
raise ValueError('Required property \'database_name\' not present in PostgresqlTrainingDataReferenceConnection JSON')
if 'port' in _dict:
args['port'] = _dict.get('port')
if 'ssl' in _dict:
args['ssl'] = _dict.get('ssl')
if 'ssl_mode' in _dict:
args['ssl_mode'] = _dict.get('ssl_mode')
if 'certificate_base64' in _dict:
args['certificate_base64'] = _dict.get('certificate_base64')
if 'connection_string' in _dict:
args['connection_string'] = _dict.get('connection_string')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PostgresqlTrainingDataReferenceConnection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'hostname') and self.hostname is not None:
_dict['hostname'] = self.hostname
if hasattr(self, 'username') and self.username is not None:
_dict['username'] = self.username
if hasattr(self, 'password') and self.password is not None:
_dict['password'] = self.password
if hasattr(self, 'database_name') and self.database_name is not None:
_dict['database_name'] = self.database_name
if hasattr(self, 'port') and self.port is not None:
_dict['port'] = self.port
if hasattr(self, 'ssl') and self.ssl is not None:
_dict['ssl'] = self.ssl
if hasattr(self, 'ssl_mode') and self.ssl_mode is not None:
_dict['ssl_mode'] = self.ssl_mode
if hasattr(self, 'certificate_base64') and self.certificate_base64 is not None:
_dict['certificate_base64'] = self.certificate_base64
if hasattr(self, 'connection_string') and self.connection_string is not None:
_dict['connection_string'] = self.connection_string
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PostgresqlTrainingDataReferenceConnection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PostgresqlTrainingDataReferenceConnection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PostgresqlTrainingDataReferenceConnection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class SslModeEnum(str, Enum):
"""
ssl_mode.
"""
DISABLE = 'disable'
ALLOW = 'allow'
PREFER = 'prefer'
REQUIRE = 'require'
VERIFY_CA = 'verify-ca'
VERIFY_FULL = 'verify-full'
class PostgresqlTrainingDataReferenceLocation(TrainingDataReferenceLocation):
"""
Postgresql table name.
:attr str table_name: name of the table.
:attr str schema_name: (optional) name of the schema.
"""
def __init__(self,
table_name: str,
*,
schema_name: str = None) -> None:
"""
Initialize a PostgresqlTrainingDataReferenceLocation object.
:param str table_name: name of the table.
:param str schema_name: (optional) name of the schema.
"""
# pylint: disable=super-init-not-called
self.table_name = table_name
self.schema_name = schema_name
@classmethod
def from_dict(cls, _dict: Dict) -> 'PostgresqlTrainingDataReferenceLocation':
"""Initialize a PostgresqlTrainingDataReferenceLocation object from a json dictionary."""
args = {}
if 'table_name' in _dict:
args['table_name'] = _dict.get('table_name')
else:
raise ValueError('Required property \'table_name\' not present in PostgresqlTrainingDataReferenceLocation JSON')
if 'schema_name' in _dict:
args['schema_name'] = _dict.get('schema_name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PostgresqlTrainingDataReferenceLocation object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'table_name') and self.table_name is not None:
_dict['table_name'] = self.table_name
if hasattr(self, 'schema_name') and self.schema_name is not None:
_dict['schema_name'] = self.schema_name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PostgresqlTrainingDataReferenceLocation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PostgresqlTrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PostgresqlTrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class PrimaryStorageCredentialsLong(PrimaryStorageCredentials):
"""
PrimaryStorageCredentialsLong.
:attr str hostname:
:attr str username:
:attr str password:
:attr str db:
:attr int port: (optional)
:attr bool ssl: (optional)
:attr str sslmode: (optional) (postgresql only).
:attr str certificate_base64: (optional) DER-encoded certificate in Base64
encoding. The decoded content must be bound at the beginning by -----BEGIN
CERTIFICATE----- and at the end by -----END CERTIFICATE-----.
:attr dict additional_properties: (optional) any additional properties to be
included in connection url.
"""
def __init__(self,
hostname: str,
username: str,
password: str,
db: str,
*,
port: int = None,
ssl: bool = None,
sslmode: str = None,
certificate_base64: str = None,
additional_properties: dict = None) -> None:
"""
Initialize a PrimaryStorageCredentialsLong object.
:param str hostname:
:param str username:
:param str password:
:param str db:
:param int port: (optional)
:param bool ssl: (optional)
:param str sslmode: (optional) (postgresql only).
:param str certificate_base64: (optional) DER-encoded certificate in Base64
encoding. The decoded content must be bound at the beginning by -----BEGIN
CERTIFICATE----- and at the end by -----END CERTIFICATE-----.
:param dict additional_properties: (optional) any additional properties to
be included in connection url.
"""
# pylint: disable=super-init-not-called
self.hostname = hostname
self.username = username
self.password = password
self.db = db
self.port = port
self.ssl = ssl
self.sslmode = sslmode
self.certificate_base64 = certificate_base64
self.additional_properties = additional_properties
@classmethod
def from_dict(cls, _dict: Dict) -> 'PrimaryStorageCredentialsLong':
"""Initialize a PrimaryStorageCredentialsLong object from a json dictionary."""
args = {}
if 'hostname' in _dict:
args['hostname'] = _dict.get('hostname')
else:
raise ValueError('Required property \'hostname\' not present in PrimaryStorageCredentialsLong JSON')
if 'username' in _dict:
args['username'] = _dict.get('username')
else:
raise ValueError('Required property \'username\' not present in PrimaryStorageCredentialsLong JSON')
if 'password' in _dict:
args['password'] = _dict.get('password')
else:
raise ValueError('Required property \'password\' not present in PrimaryStorageCredentialsLong JSON')
if 'db' in _dict:
args['db'] = _dict.get('db')
else:
raise ValueError('Required property \'db\' not present in PrimaryStorageCredentialsLong JSON')
if 'port' in _dict:
args['port'] = _dict.get('port')
if 'ssl' in _dict:
args['ssl'] = _dict.get('ssl')
if 'sslmode' in _dict:
args['sslmode'] = _dict.get('sslmode')
if 'certificate_base64' in _dict:
args['certificate_base64'] = _dict.get('certificate_base64')
if 'additional_properties' in _dict:
args['additional_properties'] = _dict.get('additional_properties')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a PrimaryStorageCredentialsLong object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'hostname') and self.hostname is not None:
_dict['hostname'] = self.hostname
if hasattr(self, 'username') and self.username is not None:
_dict['username'] = self.username
if hasattr(self, 'password') and self.password is not None:
_dict['password'] = self.password
if hasattr(self, 'db') and self.db is not None:
_dict['db'] = self.db
if hasattr(self, 'port') and self.port is not None:
_dict['port'] = self.port
if hasattr(self, 'ssl') and self.ssl is not None:
_dict['ssl'] = self.ssl
if hasattr(self, 'sslmode') and self.sslmode is not None:
_dict['sslmode'] = self.sslmode
if hasattr(self, 'certificate_base64') and self.certificate_base64 is not None:
_dict['certificate_base64'] = self.certificate_base64
if hasattr(self, 'additional_properties') and self.additional_properties is not None:
_dict['additional_properties'] = self.additional_properties
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this PrimaryStorageCredentialsLong object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'PrimaryStorageCredentialsLong') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'PrimaryStorageCredentialsLong') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class RecordsListResponseDataRecordsResponseCollectionDict(RecordsListResponse):
"""
dict format.
:attr int total_count: (optional) Number of all rows which satisfy the query. It
is calculated and returned when include_total_count query param is set to
`true`.
:attr List[DataRecordResponse] records:
"""
def __init__(self,
records: List['DataRecordResponse'],
*,
total_count: int = None) -> None:
"""
Initialize a RecordsListResponseDataRecordsResponseCollectionDict object.
:param List[DataRecordResponse] records:
:param int total_count: (optional) Number of all rows which satisfy the
query. It is calculated and returned when include_total_count query param
is set to `true`.
"""
# pylint: disable=super-init-not-called
self.total_count = total_count
self.records = records
@classmethod
def from_dict(cls, _dict: Dict) -> 'RecordsListResponseDataRecordsResponseCollectionDict':
"""Initialize a RecordsListResponseDataRecordsResponseCollectionDict object from a json dictionary."""
args = {}
if 'total_count' in _dict:
args['total_count'] = _dict.get('total_count')
if 'records' in _dict:
args['records'] = [DataRecordResponse.from_dict(x) for x in _dict.get('records')]
else:
raise ValueError('Required property \'records\' not present in RecordsListResponseDataRecordsResponseCollectionDict JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RecordsListResponseDataRecordsResponseCollectionDict object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'total_count') and self.total_count is not None:
_dict['total_count'] = self.total_count
if hasattr(self, 'records') and self.records is not None:
_dict['records'] = [x.to_dict() for x in self.records]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RecordsListResponseDataRecordsResponseCollectionDict object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RecordsListResponseDataRecordsResponseCollectionDict') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RecordsListResponseDataRecordsResponseCollectionDict') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class RecordsListResponseDataRecordsResponseCollectionList(RecordsListResponse):
"""
list format.
:attr int total_count: (optional) Number of all rows which satisfy the query. It
is calculated and returned when include_total_count query param is set to
`true`.
:attr List[DataRecordResponseList] records:
"""
def __init__(self,
records: List['DataRecordResponseList'],
*,
total_count: int = None) -> None:
"""
Initialize a RecordsListResponseDataRecordsResponseCollectionList object.
:param List[DataRecordResponseList] records:
:param int total_count: (optional) Number of all rows which satisfy the
query. It is calculated and returned when include_total_count query param
is set to `true`.
"""
# pylint: disable=super-init-not-called
self.total_count = total_count
self.records = records
@classmethod
def from_dict(cls, _dict: Dict) -> 'RecordsListResponseDataRecordsResponseCollectionList':
"""Initialize a RecordsListResponseDataRecordsResponseCollectionList object from a json dictionary."""
args = {}
if 'total_count' in _dict:
args['total_count'] = _dict.get('total_count')
if 'records' in _dict:
args['records'] = [DataRecordResponseList.from_dict(x) for x in _dict.get('records')]
else:
raise ValueError('Required property \'records\' not present in RecordsListResponseDataRecordsResponseCollectionList JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RecordsListResponseDataRecordsResponseCollectionList object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'total_count') and self.total_count is not None:
_dict['total_count'] = self.total_count
if hasattr(self, 'records') and self.records is not None:
_dict['records'] = [x.to_dict() for x in self.records]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RecordsListResponseDataRecordsResponseCollectionList object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RecordsListResponseDataRecordsResponseCollectionList') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RecordsListResponseDataRecordsResponseCollectionList') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class S3TrainingDataReferenceConnection(TrainingDataReferenceConnection):
"""
S3TrainingDataReferenceConnection.
:attr str access_key_id:
:attr str secret_access_key:
:attr str region_name: (optional)
"""
def __init__(self,
access_key_id: str,
secret_access_key: str,
*,
region_name: str = None) -> None:
"""
Initialize a S3TrainingDataReferenceConnection object.
:param str access_key_id:
:param str secret_access_key:
:param str region_name: (optional)
"""
# pylint: disable=super-init-not-called
self.access_key_id = access_key_id
self.secret_access_key = secret_access_key
self.region_name = region_name
@classmethod
def from_dict(cls, _dict: Dict) -> 'S3TrainingDataReferenceConnection':
"""Initialize a S3TrainingDataReferenceConnection object from a json dictionary."""
args = {}
if 'access_key_id' in _dict:
args['access_key_id'] = _dict.get('access_key_id')
else:
raise ValueError('Required property \'access_key_id\' not present in S3TrainingDataReferenceConnection JSON')
if 'secret_access_key' in _dict:
args['secret_access_key'] = _dict.get('secret_access_key')
else:
raise ValueError('Required property \'secret_access_key\' not present in S3TrainingDataReferenceConnection JSON')
if 'region_name' in _dict:
args['region_name'] = _dict.get('region_name')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a S3TrainingDataReferenceConnection object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'access_key_id') and self.access_key_id is not None:
_dict['access_key_id'] = self.access_key_id
if hasattr(self, 'secret_access_key') and self.secret_access_key is not None:
_dict['secret_access_key'] = self.secret_access_key
if hasattr(self, 'region_name') and self.region_name is not None:
_dict['region_name'] = self.region_name
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this S3TrainingDataReferenceConnection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'S3TrainingDataReferenceConnection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'S3TrainingDataReferenceConnection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class S3TrainingDataReferenceLocation(TrainingDataReferenceLocation):
"""
S3 file location.
:attr str bucket:
:attr str file_name:
:attr bool firstlineheader: (optional)
:attr str infer_schema: (optional)
:attr str file_format: (optional)
"""
def __init__(self,
bucket: str,
file_name: str,
*,
firstlineheader: bool = None,
infer_schema: str = None,
file_format: str = None) -> None:
"""
Initialize a S3TrainingDataReferenceLocation object.
:param str bucket:
:param str file_name:
:param bool firstlineheader: (optional)
:param str infer_schema: (optional)
:param str file_format: (optional)
"""
# pylint: disable=super-init-not-called
self.bucket = bucket
self.file_name = file_name
self.firstlineheader = firstlineheader
self.infer_schema = infer_schema
self.file_format = file_format
@classmethod
def from_dict(cls, _dict: Dict) -> 'S3TrainingDataReferenceLocation':
"""Initialize a S3TrainingDataReferenceLocation object from a json dictionary."""
args = {}
if 'bucket' in _dict:
args['bucket'] = _dict.get('bucket')
else:
raise ValueError('Required property \'bucket\' not present in S3TrainingDataReferenceLocation JSON')
if 'file_name' in _dict:
args['file_name'] = _dict.get('file_name')
else:
raise ValueError('Required property \'file_name\' not present in S3TrainingDataReferenceLocation JSON')
if 'firstlineheader' in _dict:
args['firstlineheader'] = _dict.get('firstlineheader')
if 'infer_schema' in _dict:
args['infer_schema'] = _dict.get('infer_schema')
if 'file_format' in _dict:
args['file_format'] = _dict.get('file_format')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a S3TrainingDataReferenceLocation object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'bucket') and self.bucket is not None:
_dict['bucket'] = self.bucket
if hasattr(self, 'file_name') and self.file_name is not None:
_dict['file_name'] = self.file_name
if hasattr(self, 'firstlineheader') and self.firstlineheader is not None:
_dict['firstlineheader'] = self.firstlineheader
if hasattr(self, 'infer_schema') and self.infer_schema is not None:
_dict['infer_schema'] = self.infer_schema
if hasattr(self, 'file_format') and self.file_format is not None:
_dict['file_format'] = self.file_format
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this S3TrainingDataReferenceLocation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'S3TrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'S3TrainingDataReferenceLocation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class FileFormatEnum(str, Enum):
"""
file_format.
"""
CSV = 'csv'
[docs]
class SPSSCredentials(MLCredentials):
"""
SPSSCredentials.
:attr str url:
:attr str username:
:attr str password:
"""
# The set of defined properties for the class
_properties = frozenset(['url', 'username', 'password'])
def __init__(self,
url: str,
username: str,
password: str,
**kwargs) -> None:
"""
Initialize a SPSSCredentials object.
:param str url:
:param str username:
:param str password:
:param **kwargs: (optional) Any additional properties.
"""
# pylint: disable=super-init-not-called
self.url = url
self.username = username
self.password = password
for _key, _value in kwargs.items():
setattr(self, _key, _value)
@classmethod
def from_dict(cls, _dict: Dict) -> 'SPSSCredentials':
"""Initialize a SPSSCredentials object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
else:
raise ValueError('Required property \'url\' not present in SPSSCredentials JSON')
if 'username' in _dict:
args['username'] = _dict.get('username')
else:
raise ValueError('Required property \'username\' not present in SPSSCredentials JSON')
if 'password' in _dict:
args['password'] = _dict.get('password')
else:
raise ValueError('Required property \'password\' not present in SPSSCredentials JSON')
args.update({k:v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SPSSCredentials object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'username') and self.username is not None:
_dict['username'] = self.username
if hasattr(self, 'password') and self.password is not None:
_dict['password'] = self.password
for _key in [k for k in vars(self).keys() if k not in SPSSCredentials._properties]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SPSSCredentials object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SPSSCredentials') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SPSSCredentials') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class SageMakerCredentials(MLCredentials):
"""
SageMakerCredentials.
:attr str access_key_id:
:attr str secret_access_key:
:attr str region: (optional)
"""
# The set of defined properties for the class
_properties = frozenset(['access_key_id', 'secret_access_key', 'region'])
def __init__(self,
access_key_id: str,
secret_access_key: str,
*,
region: str = None,
**kwargs) -> None:
"""
Initialize a SageMakerCredentials object.
:param str access_key_id:
:param str secret_access_key:
:param str region: (optional)
:param **kwargs: (optional) Any additional properties.
"""
# pylint: disable=super-init-not-called
self.access_key_id = access_key_id
self.secret_access_key = secret_access_key
self.region = region
for _key, _value in kwargs.items():
setattr(self, _key, _value)
@classmethod
def from_dict(cls, _dict: Dict) -> 'SageMakerCredentials':
"""Initialize a SageMakerCredentials object from a json dictionary."""
args = {}
if 'access_key_id' in _dict:
args['access_key_id'] = _dict.get('access_key_id')
else:
raise ValueError('Required property \'access_key_id\' not present in SageMakerCredentials JSON')
if 'secret_access_key' in _dict:
args['secret_access_key'] = _dict.get('secret_access_key')
else:
raise ValueError('Required property \'secret_access_key\' not present in SageMakerCredentials JSON')
if 'region' in _dict:
args['region'] = _dict.get('region')
args.update({k:v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SageMakerCredentials object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'access_key_id') and self.access_key_id is not None:
_dict['access_key_id'] = self.access_key_id
if hasattr(self, 'secret_access_key') and self.secret_access_key is not None:
_dict['secret_access_key'] = self.secret_access_key
if hasattr(self, 'region') and self.region is not None:
_dict['region'] = self.region
for _key in [k for k in vars(self).keys() if k not in SageMakerCredentials._properties]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SageMakerCredentials object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SageMakerCredentials') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SageMakerCredentials') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class ScoringEndpointCredentialsAzureScoringEndpointCredentials(ScoringEndpointCredentials):
"""
ScoringEndpointCredentialsAzureScoringEndpointCredentials.
:attr str token:
"""
# The set of defined properties for the class
_properties = frozenset(['token'])
def __init__(self,
token: str,
**kwargs) -> None:
"""
Initialize a ScoringEndpointCredentialsAzureScoringEndpointCredentials object.
:param str token:
:param **kwargs: (optional) Any additional properties.
"""
# pylint: disable=super-init-not-called
self.token = token
for _key, _value in kwargs.items():
setattr(self, _key, _value)
@classmethod
def from_dict(cls, _dict: Dict) -> 'ScoringEndpointCredentialsAzureScoringEndpointCredentials':
"""Initialize a ScoringEndpointCredentialsAzureScoringEndpointCredentials object from a json dictionary."""
args = {}
if 'token' in _dict:
args['token'] = _dict.get('token')
else:
raise ValueError('Required property \'token\' not present in ScoringEndpointCredentialsAzureScoringEndpointCredentials JSON')
args.update({k:v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ScoringEndpointCredentialsAzureScoringEndpointCredentials object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'token') and self.token is not None:
_dict['token'] = self.token
for _key in [k for k in vars(self).keys() if k not in ScoringEndpointCredentialsAzureScoringEndpointCredentials._properties]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ScoringEndpointCredentialsAzureScoringEndpointCredentials object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ScoringEndpointCredentialsAzureScoringEndpointCredentials') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ScoringEndpointCredentialsAzureScoringEndpointCredentials') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class SparkStructFieldObject(SparkStructField):
"""
SparkStructFieldObject.
:attr str name:
:attr object type:
:attr bool nullable:
:attr dict metadata: (optional)
"""
def __init__(self,
name: str,
type: object,
nullable: bool,
*,
metadata: dict = None) -> None:
"""
Initialize a SparkStructFieldObject object.
:param str name:
:param object type:
:param bool nullable:
:param dict metadata: (optional)
"""
# pylint: disable=super-init-not-called
self.name = name
self.type = type
self.nullable = nullable
self.metadata = metadata
@classmethod
def from_dict(cls, _dict: Dict) -> 'SparkStructFieldObject':
"""Initialize a SparkStructFieldObject object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in SparkStructFieldObject JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in SparkStructFieldObject JSON')
if 'nullable' in _dict:
args['nullable'] = _dict.get('nullable')
else:
raise ValueError('Required property \'nullable\' not present in SparkStructFieldObject JSON')
if 'metadata' in _dict:
args['metadata'] = _dict.get('metadata')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SparkStructFieldObject object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'nullable') and self.nullable is not None:
_dict['nullable'] = self.nullable
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SparkStructFieldObject object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SparkStructFieldObject') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SparkStructFieldObject') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class SparkStructFieldPrimitive(SparkStructField):
"""
SparkStructFieldPrimitive.
:attr str name:
:attr str type:
:attr bool nullable:
:attr dict metadata: (optional)
"""
def __init__(self,
name: str,
type: str,
nullable: bool,
*,
metadata: dict = None) -> None:
"""
Initialize a SparkStructFieldPrimitive object.
:param str name:
:param str type:
:param bool nullable:
:param dict metadata: (optional)
"""
# pylint: disable=super-init-not-called
self.name = name
self.type = type
self.nullable = nullable
self.metadata = metadata
@classmethod
def from_dict(cls, _dict: Dict) -> 'SparkStructFieldPrimitive':
"""Initialize a SparkStructFieldPrimitive object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError('Required property \'name\' not present in SparkStructFieldPrimitive JSON')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError('Required property \'type\' not present in SparkStructFieldPrimitive JSON')
if 'nullable' in _dict:
args['nullable'] = _dict.get('nullable')
else:
raise ValueError('Required property \'nullable\' not present in SparkStructFieldPrimitive JSON')
if 'metadata' in _dict:
args['metadata'] = _dict.get('metadata')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SparkStructFieldPrimitive object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'nullable') and self.nullable is not None:
_dict['nullable'] = self.nullable
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SparkStructFieldPrimitive object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SparkStructFieldPrimitive') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SparkStructFieldPrimitive') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class UnknownCredentials(MLCredentials):
"""
Unknown service provider credentials.
"""
def __init__(self,
**kwargs) -> None:
"""
Initialize a UnknownCredentials object.
:param **kwargs: (optional) Any additional properties.
"""
# pylint: disable=super-init-not-called
for _key, _value in kwargs.items():
setattr(self, _key, _value)
@classmethod
def from_dict(cls, _dict: Dict) -> 'UnknownCredentials':
"""Initialize a UnknownCredentials object from a json dictionary."""
return cls(**_dict)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a UnknownCredentials object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
return vars(self)
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this UnknownCredentials object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'UnknownCredentials') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'UnknownCredentials') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class UserPreferencesGetResponseUserPreferenceValueObject(UserPreferencesGetResponse):
"""
user preference object value.
"""
def __init__(self) -> None:
"""
Initialize a UserPreferencesGetResponseUserPreferenceValueObject object.
"""
# pylint: disable=super-init-not-called
@classmethod
def from_dict(cls, _dict: Dict) -> 'UserPreferencesGetResponseUserPreferenceValueObject':
"""Initialize a UserPreferencesGetResponseUserPreferenceValueObject object from a json dictionary."""
return cls(**_dict)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a UserPreferencesGetResponseUserPreferenceValueObject object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
return vars(self)
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this UserPreferencesGetResponseUserPreferenceValueObject object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'UserPreferencesGetResponseUserPreferenceValueObject') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'UserPreferencesGetResponseUserPreferenceValueObject') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class UserPreferencesGetResponseUserPreferenceValueString(UserPreferencesGetResponse):
"""
user preference string value - response string wrapped in an object.
:attr str value: (optional) response string value.
"""
def __init__(self,
*,
value: str = None) -> None:
"""
Initialize a UserPreferencesGetResponseUserPreferenceValueString object.
:param str value: (optional) response string value.
"""
# pylint: disable=super-init-not-called
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'UserPreferencesGetResponseUserPreferenceValueString':
"""Initialize a UserPreferencesGetResponseUserPreferenceValueString object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a UserPreferencesGetResponseUserPreferenceValueString object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this UserPreferencesGetResponseUserPreferenceValueString object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'UserPreferencesGetResponseUserPreferenceValueString') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'UserPreferencesGetResponseUserPreferenceValueString') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class UserPreferencesUpdateRequestUserPreferenceValueObject(UserPreferencesUpdateRequest):
"""
user preference object value.
"""
def __init__(self) -> None:
"""
Initialize a UserPreferencesUpdateRequestUserPreferenceValueObject object.
"""
# pylint: disable=super-init-not-called
@classmethod
def from_dict(cls, _dict: Dict) -> 'UserPreferencesUpdateRequestUserPreferenceValueObject':
"""Initialize a UserPreferencesUpdateRequestUserPreferenceValueObject object from a json dictionary."""
return cls(**_dict)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a UserPreferencesUpdateRequestUserPreferenceValueObject object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
return vars(self)
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this UserPreferencesUpdateRequestUserPreferenceValueObject object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'UserPreferencesUpdateRequestUserPreferenceValueObject') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'UserPreferencesUpdateRequestUserPreferenceValueObject') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class UserPreferencesUpdateRequestUserPreferenceValueString(UserPreferencesUpdateRequest):
"""
user preference string value - response string wrapped in an object.
:attr str value: (optional) response string value.
"""
def __init__(self,
*,
value: str = None) -> None:
"""
Initialize a UserPreferencesUpdateRequestUserPreferenceValueString object.
:param str value: (optional) response string value.
"""
# pylint: disable=super-init-not-called
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'UserPreferencesUpdateRequestUserPreferenceValueString':
"""Initialize a UserPreferencesUpdateRequestUserPreferenceValueString object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a UserPreferencesUpdateRequestUserPreferenceValueString object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this UserPreferencesUpdateRequestUserPreferenceValueString object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'UserPreferencesUpdateRequestUserPreferenceValueString') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'UserPreferencesUpdateRequestUserPreferenceValueString') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class WMLCredentialsCP4D(MLCredentials):
"""
WMLCredentials format for OpenScale on Cloud Pak for Data.
:attr str url: (optional) Required if wml_location is cpd_remote or
cloud_remote.
:attr str apikey: (optional) Required if wml_location is cpd_remote or
cloud_remote.
:attr str username: (optional) Required if wml_location is cpd_remote.
:attr str uid: (optional) User ID of a user in the Cloud Pak for Data. If not
set, the uid extracted from the access token in Authorization header is used.
This parameter is only applicable if wml_location is cpd_local.
:attr str wml_location: (optional) If wml_location is not selected, we treat the
service provider as cpd_local for backward compatibility.
"""
# The set of defined properties for the class
_properties = frozenset(['url', 'apikey', 'username', 'uid', 'wml_location'])
def __init__(self,
*,
url: str = None,
apikey: str = None,
username: str = None,
uid: str = None,
wml_location: str = None,
**kwargs) -> None:
"""
Initialize a WMLCredentialsCP4D object.
:param str url: (optional) Required if wml_location is cpd_remote or
cloud_remote.
:param str apikey: (optional) Required if wml_location is cpd_remote or
cloud_remote.
:param str username: (optional) Required if wml_location is cpd_remote.
:param str uid: (optional) User ID of a user in the Cloud Pak for Data. If
not set, the uid extracted from the access token in Authorization header is
used. This parameter is only applicable if wml_location is cpd_local.
:param str wml_location: (optional) If wml_location is not selected, we
treat the service provider as cpd_local for backward compatibility.
:param **kwargs: (optional) Any additional properties.
"""
# pylint: disable=super-init-not-called
self.url = url
self.apikey = apikey
self.username = username
self.uid = uid
self.wml_location = wml_location
for _key, _value in kwargs.items():
setattr(self, _key, _value)
@classmethod
def from_dict(cls, _dict: Dict) -> 'WMLCredentialsCP4D':
"""Initialize a WMLCredentialsCP4D object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
if 'apikey' in _dict:
args['apikey'] = _dict.get('apikey')
if 'username' in _dict:
args['username'] = _dict.get('username')
if 'uid' in _dict:
args['uid'] = _dict.get('uid')
if 'wml_location' in _dict:
args['wml_location'] = _dict.get('wml_location')
args.update({k:v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a WMLCredentialsCP4D object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'apikey') and self.apikey is not None:
_dict['apikey'] = self.apikey
if hasattr(self, 'username') and self.username is not None:
_dict['username'] = self.username
if hasattr(self, 'uid') and self.uid is not None:
_dict['uid'] = self.uid
if hasattr(self, 'wml_location') and self.wml_location is not None:
_dict['wml_location'] = self.wml_location
for _key in [k for k in vars(self).keys() if k not in WMLCredentialsCP4D._properties]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this WMLCredentialsCP4D object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'WMLCredentialsCP4D') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'WMLCredentialsCP4D') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]
class WmlLocationEnum(str, Enum):
"""
If wml_location is not selected, we treat the service provider as cpd_local for
backward compatibility.
"""
CPD_LOCAL = 'cpd_local'
CPD_REMOTE = 'cpd_remote'
CLOUD_REMOTE = 'cloud_remote'
[docs]
class WMLCredentialsCloud(MLCredentials):
"""
WMLCredentialsCloud.
:attr str apikey: (optional)
:attr str token: (optional)
:attr str url:
:attr str instance_id:
"""
# The set of defined properties for the class
_properties = frozenset(['apikey', 'token', 'url', 'instance_id'])
def __init__(self,
url: str,
instance_id: str,
*,
apikey: str = None,
token: str = None,
**kwargs) -> None:
"""
Initialize a WMLCredentialsCloud object.
:param str url:
:param str instance_id:
:param str apikey: (optional)
:param str token: (optional)
:param **kwargs: (optional) Any additional properties.
"""
# pylint: disable=super-init-not-called
self.apikey = apikey
self.token = token
self.url = url
self.instance_id = instance_id
for _key, _value in kwargs.items():
setattr(self, _key, _value)
@classmethod
def from_dict(cls, _dict: Dict) -> 'WMLCredentialsCloud':
"""Initialize a WMLCredentialsCloud object from a json dictionary."""
args = {}
if 'apikey' in _dict:
args['apikey'] = _dict.get('apikey')
if 'token' in _dict:
args['token'] = _dict.get('token')
if 'url' in _dict:
args['url'] = _dict.get('url')
else:
raise ValueError('Required property \'url\' not present in WMLCredentialsCloud JSON')
if 'instance_id' in _dict:
args['instance_id'] = _dict.get('instance_id')
else:
raise ValueError('Required property \'instance_id\' not present in WMLCredentialsCloud JSON')
args.update({k:v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a WMLCredentialsCloud object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'apikey') and self.apikey is not None:
_dict['apikey'] = self.apikey
if hasattr(self, 'token') and self.token is not None:
_dict['token'] = self.token
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'instance_id') and self.instance_id is not None:
_dict['instance_id'] = self.instance_id
for _key in [k for k in vars(self).keys() if k not in WMLCredentialsCloud._properties]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this WMLCredentialsCloud object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'WMLCredentialsCloud') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'WMLCredentialsCloud') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean(DetectorPropertyDefaultValue):
"""
DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean.
:attr bool value:
"""
def __init__(self,
value: bool) -> None:
"""
Initialize a DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean object.
:param bool value:
"""
# pylint: disable=super-init-not-called
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean':
"""Initialize a DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError('Required property \'value\' not present in DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueBoolean') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber(DetectorPropertyDefaultValue):
"""
DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber.
:attr float value:
"""
def __init__(self,
value: float) -> None:
"""
Initialize a DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber object.
:param float value:
"""
# pylint: disable=super-init-not-called
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber':
"""Initialize a DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError('Required property \'value\' not present in DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueNumber') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
class DetectorPropertyDefaultValueDetectorPropertyDefaultValueString(DetectorPropertyDefaultValue):
"""
DetectorPropertyDefaultValueDetectorPropertyDefaultValueString.
:attr str value:
"""
def __init__(self,
value: str) -> None:
"""
Initialize a DetectorPropertyDefaultValueDetectorPropertyDefaultValueString object.
:param str value:
"""
# pylint: disable=super-init-not-called
self.value = value
@classmethod
def from_dict(cls, _dict: Dict) -> 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueString':
"""Initialize a DetectorPropertyDefaultValueDetectorPropertyDefaultValueString object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError('Required property \'value\' not present in DetectorPropertyDefaultValueDetectorPropertyDefaultValueString JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DetectorPropertyDefaultValueDetectorPropertyDefaultValueString object from a json dictionary."""
return cls.from_dict(_dict)
def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DetectorPropertyDefaultValueDetectorPropertyDefaultValueString object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueString') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DetectorPropertyDefaultValueDetectorPropertyDefaultValueString') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other