abacusai.client
Module Contents
Classes
Options for configuring the ApiClient |
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Factory class to build exceptions raised by APIs |
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Abstract Base API Client |
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Abacus.AI Read Only API Client. Only contains GET methods |
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Abacus.AI API Client |
Functions
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Attributes
- abacusai.client.DEFAULT_SERVER = 'https://api.abacus.ai'
- abacusai.client._request_context
- abacusai.client._requests_retry_session(retries=5, backoff_factor=0.1, status_forcelist=(502, 503, 504), session=None, retry_500=False)
- Parameters:
retry_500 (bool) –
- abacusai.client._discover_service_url(service_discovery_url, client_version, deployment_id, deployment_token)
- abacusai.client._cached_endpoints
- class abacusai.client.ClientOptions(exception_on_404=True, server=DEFAULT_SERVER)
Options for configuring the ApiClient
- exception abacusai.client.ApiException(message, http_status, exception=None, request_id=None)
Bases:
ExceptionDefault ApiException raised by APIs
- Parameters:
- __str__()
Return str(self).
- exception abacusai.client.MissingParameterError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionMissing parameter error raised by APIs. This is usually raised when a required parameter is missing in the request.
- exception abacusai.client.InvalidParameterError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionRaised when an invalid parameter is provided.
- exception abacusai.client.InvalidEnumParameterError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionRaised when an invalid enumeration parameter is provided.
- exception abacusai.client.PaymentMethodRequired(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionRaised when a payment method is required.
- exception abacusai.client.InvalidRequest(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionInvalid request error raised by APIs. This is usually raised when the request is invalid or malformed.
- exception abacusai.client.GenericPermissionDeniedError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionGeneric permission denied error raised by APIs. This is usually raised when permission is denied.
- exception abacusai.client.PermissionDeniedError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionPermission denied error raised by APIs. This is usually raised when a specific operation is not permitted.
- exception abacusai.client.PaidPlanRequired(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionPaid plan required error raised by APIs. This is usually raised when a paid plan is required for an operation.
- exception abacusai.client.Generic404Error(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionGeneric 404 error raised by APIs. This is usually raised when a resource is not found.
- exception abacusai.client.DataNotFoundError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionData not found error raised by APIs. This is usually raised when specific data is not found.
- exception abacusai.client.MethodNotAllowed(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionMethod not allowed error raised by APIs. This is usually raised when a specific http method is not allowed for a resource.
- exception abacusai.client.RequestTimeoutError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionException raised when a timeout occurs during API request.
- exception abacusai.client.ConflictError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionException raised when a conflict occurs during API request.
- exception abacusai.client.AlreadyExistsError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionException raised when the entity being created already exists.
- exception abacusai.client.NotReadyError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionNot ready exception raised by APIs. This is usually raised when the operation requested is not ready.
- exception abacusai.client.FailedDependencyError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionFailed dependency exception raised by APIs. This is usually raised when the operation failed due to a dependency error.
- exception abacusai.client.TooManyRequestsError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionToo many requests exception raised by APIs. This is usually raised when the rate limit for requests has been exceeded.
- exception abacusai.client.InstanceNotModifiedError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionInstanceNotModifiedError exception raised by APIs. This is usually raised when an instance is not modified.
- exception abacusai.client.GatewayTimeoutError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionGateway timeout error raised by APIs. This is usually raised when a request times out waiting for a response from the gateway.
- exception abacusai.client.InternalServerError(message, http_status, exception=None, request_id=None)
Bases:
ApiExceptionInternal server error raised by APIs. This is usually raised when the server encounters an unexpected error while processing the request.
- class abacusai.client._ApiExceptionFactory
Factory class to build exceptions raised by APIs
- class abacusai.client.BaseApiClient(api_key=None, server=None, client_options=None, skip_version_check=False)
Abstract Base API Client
- Parameters:
api_key (str) – The api key to use as authentication to the server
server (str) – The base server url to use to send API requets to
client_options (ClientOptions) – Optional API client configurations
skip_version_check (bool) – If true, will skip checking the server’s current API version on initializing the client
- client_version = '0.77.8'
- _get_prediction_endpoint(deployment_id, deployment_token)
- _get_streaming_endpoint(streaming_token, model_id=None, feature_group_id=None)
- _clean_api_objects(obj)
- _call_api(action, method, query_params=None, body=None, files=None, parse_type=None, streamable_response=False, server_override=None, timeout=None, retry_500=False)
- Parameters:
retry_500 (bool) –
- _build_class(return_class, values)
- _request(url, method, query_params=None, headers=None, body=None, files=None, stream=False, timeout=None, retry_500=False)
- Parameters:
retry_500 (bool) –
- _poll(obj, wait_states, delay=15, timeout=300, poll_args={}, status_field=None)
- _upload_from_pandas(upload, df, clean_column_names=False)
- Return type:
- _upload_from_spark(upload, df)
- Return type:
- class abacusai.client.ReadOnlyClient(api_key=None, server=None, client_options=None, skip_version_check=False)
Bases:
BaseApiClientAbacus.AI Read Only API Client. Only contains GET methods
- Parameters:
api_key (str) – The api key to use as authentication to the server
server (str) – The base server url to use to send API requets to
client_options (ClientOptions) – Optional API client configurations
skip_version_check (bool) – If true, will skip checking the server’s current API version on initializing the client
- list_api_keys()
Lists all of the user’s API keys
- list_organization_users()
Retrieves a list of all users in the organization, including pending users who have been invited.
- describe_user()
Retrieve the current user’s information, such as their name, email address, and admin status.
- Returns:
An object containing information about the current user.
- Return type:
- list_organization_groups()
Lists all Organizations Groups
- Returns:
A list of all the organization groups within this organization.
- Return type:
- describe_organization_group(organization_group_id)
Returns the specific organization group passed in by the user.
- Parameters:
organization_group_id (str) – The unique identifier of the organization group to be described.
- Returns:
Information about a specific organization group.
- Return type:
- describe_webhook(webhook_id)
Describe the webhook with a given ID.
- list_deployment_webhooks(deployment_id)
List all the webhooks attached to a given deployment.
- list_use_cases()
Retrieves a list of all use cases with descriptions. Use the given mappings to specify a use case when needed.
- describe_problem_type(problem_type)
Describes a problem type
- Parameters:
problem_type (str) – The problem type to get details on
- Returns:
The problem type requirements
- Return type:
- describe_use_case_requirements(use_case)
This API call returns the feature requirements for a specified use case.
- Parameters:
use_case (str) – This contains the Enum String for the use case whose dataset requirements are needed.
- Returns:
The feature requirements of the use case are returned, including all the feature groups required for the use case along with their descriptions and feature mapping details.
- Return type:
- describe_project(project_id)
Returns a description of a project.
- list_projects(limit=100, start_after_id=None)
Retrieves a list of all projects in the current organization.
- get_project_feature_group_config(feature_group_id, project_id)
Gets a feature group’s project config
- Parameters:
- Returns:
The feature group’s project configuration.
- Return type:
- validate_project(project_id, feature_group_ids=None)
Validates that the specified project has all required feature group types for its use case and that all required feature columns are set.
- Parameters:
- Returns:
The project validation. If the specified project is missing required columns or feature groups, the response includes an array of objects for each missing required feature group and the missing required features in each feature group.
- Return type:
- infer_feature_mappings(project_id, feature_group_id)
Infer the feature mappings for the feature group in the project based on the problem type.
- Parameters:
- Returns:
A dict that contains the inferred feature mappings.
- Return type:
- verify_and_describe_annotation(feature_group_id, feature_name=None, doc_id=None, feature_group_row_identifier=None)
Get the latest annotation entry for a given feature group, feature, and document along with verification information.
- Parameters:
feature_group_id (str) – The ID of the feature group the annotation is on.
feature_name (str) – The name of the feature the annotation is on.
doc_id (str) – The ID of the primary document the annotation is on. At least one of the doc_id or feature_group_row_identifier must be provided in order to identify the correct annotation.
feature_group_row_identifier (str) – The key value of the feature group row the annotation is on (cast to string). Usually the feature group’s primary / identifier key value. At least one of the doc_id or feature_group_row_identifier must be provided in order to identify the correct annotation.
- Returns:
The latest annotation entry for the given feature group, feature, document, and/or annotation key value. Includes the verification information.
- Return type:
- get_annotations_status(feature_group_id, feature_name=None, check_for_materialization=False)
Get the status of the annotations for a given feature group and feature.
- Parameters:
- Returns:
The status of the annotations for the given feature group and feature.
- Return type:
- get_feature_group_schema(feature_group_id, project_id=None)
Returns a schema for a given FeatureGroup in a project.
- get_point_in_time_feature_group_creation_options()
Returns the options that can be used to generate PIT features.
- Returns:
List of possible generated aggregation function options.
- Return type:
- describe_feature_group(feature_group_id)
Describe a Feature Group.
- Parameters:
feature_group_id (str) – A unique string identifier associated with the feature group.
- Returns:
The feature group object.
- Return type:
- describe_feature_group_by_table_name(table_name)
Describe a Feature Group by its table name.
- Parameters:
table_name (str) – The unique table name of the Feature Group to look up.
- Returns:
The Feature Group.
- Return type:
- list_feature_groups(limit=100, start_after_id=None, feature_group_template_id=None, is_including_detached_from_template=False)
List all the feature groups
- Parameters:
limit (int) – The number of feature groups to retrieve.
start_after_id (str) – An offset parameter to exclude all feature groups up to a specified ID.
feature_group_template_id (str) – If specified, limit the results to feature groups attached to this template ID.
is_including_detached_from_template (bool) – When feature_group_template_id is specified, include feature groups that have been detached from that template ID.
- Returns:
All the feature groups in the organization associated with the specified project.
- Return type:
- describe_project_feature_group(project_id, feature_group_id)
Describe a feature group associated with a project
- Parameters:
- Returns:
The project feature group object.
- Return type:
- list_project_feature_groups(project_id, filter_feature_group_use=None)
List all the feature groups associated with a project
- Parameters:
project_id (str) – The unique ID associated with the project.
filter_feature_group_use (str) – The feature group use filter, when given as an argument only allows feature groups present in this project to be returned if they are of the given use. Possible values are: ‘USER_CREATED’, ‘BATCH_PREDICTION_OUTPUT’.
- Returns:
All the Feature Groups in a project.
- Return type:
- list_python_function_feature_groups(name, limit=100)
List all the feature groups associated with a python function.
- Parameters:
- Returns:
All the feature groups associated with the specified Python function ID.
- Return type:
- execute_async_feature_group_operation(query=None)
Starts the execution of fg operation
- Parameters:
query (str) – The SQL to be executed.
- Returns:
A dict that contains the execution status
- Return type:
- get_execute_feature_group_operation_result_part_count(feature_group_operation_run_id)
Gets the number of parts in the result of the execution of fg operation
- download_execute_feature_group_operation_result_part_chunk(feature_group_operation_run_id, part, offset=0, chunk_size=10485760)
Downloads a chunk of the result of the execution of fg operation
- Parameters:
- Return type:
- get_feature_group_version_export_download_url(feature_group_export_id)
Get a link to download the feature group version.
- Parameters:
feature_group_export_id (str) – Unique identifier of the Feature Group Export to get a signed URL for.
- Returns:
Instance containing the download URL and expiration time for the Feature Group Export.
- Return type:
- describe_feature_group_export(feature_group_export_id)
A feature group export
- Parameters:
feature_group_export_id (str) – Unique identifier of the feature group export.
- Returns:
The feature group export object.
- Return type:
- list_feature_group_exports(feature_group_id)
Lists all of the feature group exports for the feature group
- Parameters:
feature_group_id (str) – Unique identifier of the feature group
- Returns:
List of feature group exports
- Return type:
- get_feature_group_export_connector_errors(feature_group_export_id)
Returns a stream containing the write errors of the feature group export database connection, if any writes failed to the database connector.
- Parameters:
feature_group_export_id (str) – Unique identifier of the feature group export to get the errors for.
- Return type:
- list_feature_group_modifiers(feature_group_id)
List the users who can modify a given feature group.
- Parameters:
feature_group_id (str) – Unique string identifier of the feature group.
- Returns:
Information about the modification lock status and groups/organizations added to the feature group.
- Return type:
- get_materialization_logs(feature_group_version, stdout=False, stderr=False)
Returns logs for a materialized feature group version.
- Parameters:
- Returns:
A function logs object.
- Return type:
- list_feature_group_versions(feature_group_id, limit=100, start_after_version=None)
Retrieves a list of all feature group versions for the specified feature group.
- Parameters:
- Returns:
A list of feature group versions.
- Return type:
- describe_feature_group_version(feature_group_version)
Describe a feature group version.
- Parameters:
feature_group_version (str) – The unique identifier associated with the feature group version.
- Returns:
The feature group version.
- Return type:
- get_feature_group_version_metrics(feature_group_version, selected_columns=None, include_charts=False, include_statistics=True)
Get metrics for a specific feature group version.
- Parameters:
feature_group_version (str) – A unique string identifier associated with the feature group version.
selected_columns (list) – A list of columns to order first.
include_charts (bool) – A flag indicating whether charts should be included in the response. Default is false.
include_statistics (bool) – A flag indicating whether statistics should be included in the response. Default is true.
- Returns:
The metrics for the specified feature group version.
- Return type:
- describe_feature_group_template(feature_group_template_id)
Describe a Feature Group Template.
- Parameters:
feature_group_template_id (str) – The unique identifier of a feature group template.
- Returns:
The feature group template object.
- Return type:
- list_feature_group_templates(limit=100, start_after_id=None, feature_group_id=None, should_include_system_templates=False)
List feature group templates, optionally scoped by the feature group that created the templates.
- Parameters:
limit (int) – Maximum number of templates to be retrieved.
start_after_id (str) – Offset parameter to exclude all templates up to the specified feature group template ID.
feature_group_id (str) – If specified, limit to templates created from this feature group.
should_include_system_templates (bool) – If True, will include built-in templates.
- Returns:
All the feature groups in the organization, optionally limited by the feature group that created the template(s).
- Return type:
- list_project_feature_group_templates(project_id, limit=100, start_after_id=None, should_include_all_system_templates=False)
List feature group templates for feature groups associated with the project.
- Parameters:
project_id (str) – Unique string identifier to limit to templates associated with this project, e.g. templates associated with feature groups in this project.
limit (int) – Maximum number of templates to be retrieved.
start_after_id (str) – Offset parameter to exclude all templates till the specified feature group template ID.
should_include_all_system_templates (bool) – If True, will include built-in templates.
- Returns:
All the feature groups in the organization, optionally limited by the feature group that created the template(s).
- Return type:
- suggest_feature_group_template_for_feature_group(feature_group_id)
Suggest values for a feature gruop template, based on a feature group.
- Parameters:
feature_group_id (str) – Unique identifier associated with the feature group to use for suggesting values to use in the template.
- Returns:
The suggested feature group template.
- Return type:
- get_dataset_schema(dataset_id)
Retrieves the column schema of a dataset.
- Parameters:
dataset_id (str) – Unique string identifier of the dataset schema to look up.
- Returns:
List of column schema definitions.
- Return type:
- set_dataset_database_connector_config(dataset_id, database_connector_id, object_name=None, columns=None, query_arguments=None, sql_query=None)
Sets database connector config for a dataset. This method is currently only supported for streaming datasets.
- Parameters:
dataset_id (str) – Unique String Identifier of the dataset_id.
database_connector_id (str) – Unique String Identifier of the Database Connector to import the dataset from.
object_name (str) – If applicable, the name/ID of the object in the service to query.
columns (str) – The columns to query from the external service object.
query_arguments (str) – Additional query arguments to filter the data.
sql_query (str) – The full SQL query to use when fetching data. If present, this parameter will override object_name, columns and query_arguments.
- get_dataset_version_metrics(dataset_version, selected_columns=None, include_charts=False, include_statistics=True)
Get metrics for a specific dataset version.
- Parameters:
dataset_version (str) – A unique string identifier associated with the dataset version.
selected_columns (list) – A list of columns to order first.
include_charts (bool) – A flag indicating whether charts should be included in the response. Default is false.
include_statistics (bool) – A flag indicating whether statistics should be included in the response. Default is true.
- Returns:
The metrics for the specified Dataset version.
- Return type:
- get_file_connector_instructions(bucket, write_permission=False)
Retrieves verification information to create a data connector to a cloud storage bucket.
- Parameters:
- Returns:
An object with a full description of the cloud storage bucket authentication options and bucket policy. Returns an error message if the parameters are invalid.
- Return type:
- list_database_connectors()
Retrieves a list of all database connectors along with their associated attributes.
- Returns:
An object containing the database connector and its attributes.
- Return type:
- list_file_connectors()
Retrieves a list of all connected services in the organization and their current verification status.
- Returns:
A list of cloud storage buckets connected to the organization.
- Return type:
- list_database_connector_objects(database_connector_id)
Lists querable objects in the database connector.
- get_database_connector_object_schema(database_connector_id, object_name=None)
Get the schema of an object in an database connector.
- list_application_connectors()
Retrieves a list of all application connectors along with their associated attributes.
- Returns:
A list of application connectors.
- Return type:
- list_application_connector_objects(application_connector_id)
Lists querable objects in the application connector.
- list_streaming_connectors()
Retrieves a list of all streaming connectors along with their corresponding attributes.
- Returns:
A list of StreamingConnector objects.
- Return type:
- list_streaming_tokens()
Retrieves a list of all streaming tokens.
- Returns:
A list of streaming tokens and their associated attributes.
- Return type:
- get_recent_feature_group_streamed_data(feature_group_id)
Returns recently streamed data to a streaming feature group.
- Parameters:
feature_group_id (str) – Unique string identifier associated with the feature group.
- list_uploads()
Lists all pending uploads
- describe_upload(upload_id)
Retrieves the current upload status (complete or inspecting) and the list of file parts uploaded for a specified dataset upload.
- list_datasets(limit=100, start_after_id=None, exclude_streaming=False)
Retrieves a list of all datasets in the organization.
- describe_dataset(dataset_id)
Retrieves a full description of the specified dataset, with attributes such as its ID, name, source type, etc.
- describe_dataset_version(dataset_version)
Retrieves a full description of the specified dataset version, including its ID, name, source type, and other attributes.
- Parameters:
dataset_version (str) – Unique string identifier associated with the dataset version.
- Returns:
The dataset version.
- Return type:
- list_dataset_versions(dataset_id, limit=100, start_after_version=None)
Retrieves a list of all dataset versions for the specified dataset.
- Parameters:
- Returns:
A list of dataset versions.
- Return type:
- get_dataset_version_logs(dataset_version)
Retrieves the dataset import logs.
- Parameters:
dataset_version (str) – The unique version ID of the dataset version.
- Returns:
The logs for the specified dataset version.
- Return type:
- get_docstore_document(doc_id)
Return a document store document by id.
- Parameters:
doc_id (str) – Unique Docstore string identifier for the document.
- Return type:
- get_docstore_image(doc_id, max_width=None, max_height=None)
Return a document store image by id.
- Parameters:
doc_id (str) – A unique Docstore string identifier for the image.
max_width (int) – Rescales the returned image so the width is less than or equal to the given maximum width, while preserving the aspect ratio.
max_height (int) – Rescales the returned image so the height is less than or equal to the given maximum height, while preserving the aspect ratio.
- Return type:
- get_docstore_page_data(doc_id, page)
Returns the extracted page data for a document page.
- describe_train_test_data_split_feature_group(model_id)
Get the train and test data split for a trained model by its unique identifier. This is only supported for models with custom algorithms.
- Parameters:
model_id (str) – The unique ID of the model. By default, the latest model version will be returned if no version is specified.
- Returns:
The feature group containing the training data and fold information.
- Return type:
- describe_train_test_data_split_feature_group_version(model_version)
Get the train and test data split for a trained model by model version. This is only supported for models with custom algorithms.
- Parameters:
model_version (str) – The unique version ID of the model version.
- Returns:
The feature group version containing the training data and folds information.
- Return type:
- list_models(project_id)
Retrieves the list of models in the specified project.
- describe_model(model_id)
Retrieves a full description of the specified model.
- get_model_metrics(model_id, model_version=None, return_graphs=False, validation=False)
Retrieves metrics for all the algorithms trained in this model version.
If only the model’s unique identifier (model_id) is specified, the latest trained version of the model (model_version) is used.
- Parameters:
model_id (str) – Unique string identifier for the model.
model_version (str) – Version of the model.
return_graphs (bool) – If true, will return the information used for the graphs on the model metrics page such as PR Curve per label.
validation (bool) – If true, will return the validation metrics instead of the test metrics.
- Returns:
An object containing the model metrics and explanations for what each metric means.
- Return type:
- query_test_point_predictions(model_version, algorithm, to_row, from_row=0, sql_where_clause='')
Query the test points predictions data for a specific algorithm.
- Parameters:
- Returns:
TestPointPrediction
- Return type:
- list_model_versions(model_id, limit=100, start_after_version=None)
Retrieves a list of versions for a given model.
- Parameters:
- Returns:
An array of model versions.
- Return type:
- describe_model_version(model_version)
Retrieves a full description of the specified model version.
- Parameters:
model_version (str) – Unique string identifier of the model version.
- Returns:
A model version.
- Return type:
- get_feature_importance_by_model_version(model_version)
Gets the feature importance calculated by various methods for the model.
- Parameters:
model_version (str) – Unique string identifier for the model version.
- Returns:
Feature importances for the model.
- Return type:
- get_training_data_logs(model_version)
Retrieves the data preparation logs during model training.
- Parameters:
model_version (str) – The unique version ID of the model version.
- Returns:
A list of logs.
- Return type:
- get_training_logs(model_version, stdout=False, stderr=False)
Returns training logs for the model.
- Parameters:
- Returns:
A function logs object.
- Return type:
- describe_model_artifacts_export(model_artifacts_export_id)
Get the description and status of the model artifacts export.
- Parameters:
model_artifacts_export_id (str) – A unique string identifier for the export.
- Returns:
Object describing the export and its status.
- Return type:
- list_model_artifacts_exports(model_id, limit=25)
List all the model artifacts exports.
- Parameters:
- Returns:
List of model artifacts exports.
- Return type:
- list_model_monitors(project_id)
Retrieves the list of model monitors in the specified project.
- Parameters:
project_id (str) – Unique string identifier associated with the project.
- Returns:
A list of model monitors.
- Return type:
- describe_model_monitor(model_monitor_id)
Retrieves a full description of the specified model monitor.
- Parameters:
model_monitor_id (str) – Unique string identifier associated with the model monitor.
- Returns:
Description of the model monitor.
- Return type:
- get_prediction_drift(model_monitor_version)
Gets the label and prediction drifts for a model monitor.
- Parameters:
model_monitor_version (str) – Unique string identifier for a model monitor version created under the project.
- Returns:
Object describing training and prediction output label and prediction distributions.
- Return type:
- get_model_monitor_summary(model_monitor_id)
Gets the summary of a model monitor across versions.
- Parameters:
model_monitor_id (str) – A unique string identifier associated with the model monitor.
- Returns:
An object describing integrity, bias violations, model accuracy and drift for the model monitor.
- Return type:
- list_model_monitor_versions(model_monitor_id, limit=100, start_after_version=None)
Retrieves a list of versions for a given model monitor.
- Parameters:
- Returns:
A list of model monitor versions.
- Return type:
- describe_model_monitor_version(model_monitor_version)
Retrieves a full description of the specified model monitor version.
- Parameters:
model_monitor_version (str) – The unique version ID of the model monitor version.
- Returns:
A model monitor version.
- Return type:
- model_monitor_version_metric_data(model_monitor_version, metric_type, actual_values_to_detail=None)
Provides the data needed for decile metrics associated with the model monitor.
- Parameters:
- Returns:
Data associated with the metric.
- Return type:
- list_organization_model_monitors(only_starred=False)
Gets a list of Model Monitors for an organization.
- Parameters:
only_starred (bool) – Whether to return only starred Model Monitors. Defaults to False.
- Returns:
A list of Model Monitors.
- Return type:
- get_model_monitor_chart_from_organization(chart_type, limit=15)
Gets a list of model monitor summaries across monitors for an organization.
- Parameters:
- Returns:
List of ModelMonitorSummaryForOrganization objects describing accuracy, bias, drift, or integrity for all model monitors in an organization.
- Return type:
- get_model_monitor_summary_from_organization()
Gets a consolidated summary of model monitors for an organization.
- Returns:
A list of ModelMonitorSummaryForOrganization objects describing accuracy, bias, drift, and integrity for all model monitors in an organization.
- Return type:
- list_eda(project_id)
Retrieves the list of Exploratory Data Analysis (EDA) in the specified project.
- describe_eda(eda_id)
Retrieves a full description of the specified EDA object.
- list_eda_versions(eda_id, limit=100, start_after_version=None)
Retrieves a list of versions for a given EDA object.
- Parameters:
- Returns:
A list of EDA versions.
- Return type:
- describe_eda_version(eda_version)
Retrieves a full description of the specified EDA version.
- Parameters:
eda_version (str) – Unique string identifier of the EDA version.
- Returns:
An EDA version.
- Return type:
- get_eda_collinearity(eda_version)
Gets the Collinearity between all features for the Exploratory Data Analysis.
- Parameters:
eda_version (str) – Unique string identifier associated with the EDA instance.
- Returns:
An object with a record of correlations between each feature for the EDA.
- Return type:
- get_eda_data_consistency(eda_version, transformation_feature=None)
Gets the data consistency for the Exploratory Data Analysis.
- Parameters:
- Returns:
Object with duplication, deletion, and transformation data for data consistency analysis for an EDA.
- Return type:
- get_collinearity_for_feature(eda_version, feature_name=None)
Gets the Collinearity for the given feature from the Exploratory Data Analysis.
- Parameters:
- Returns:
Object with a record of correlations for the provided feature for an EDA.
- Return type:
- get_feature_association(eda_version, reference_feature_name, test_feature_name)
Gets the Feature Association for the given features from the feature group version within the eda_version.
- Parameters:
eda_version (str) – Unique string identifier associated with the EDA instance.
reference_feature_name (str) – Name of the feature for feature association (on x-axis for the plots generated for the Feature association in the product).
test_feature_name (str) – Name of the feature for feature association (on y-axis for the plots generated for the Feature association in the product).
- Returns:
An object with a record of data for the feature association between the two given features for an EDA version.
- Return type:
- get_eda_forecasting_analysis(eda_version)
Gets the Forecasting analysis for the Exploratory Data Analysis.
- Parameters:
eda_version (str) – Unique string identifier associated with the EDA version.
- Returns:
Object with forecasting analysis that includes sales_across_time, cummulative_contribution, missing_value_distribution, history_length, num_rows_histogram, product_maturity data.
- Return type:
- list_holdout_analysis(project_id, model_id=None)
List holdout analyses for a project. Optionally, filter by model.
- Parameters:
- Returns:
The holdout analyses
- Return type:
- describe_holdout_analysis(holdout_analysis_id)
Get a holdout analysis.
- Parameters:
holdout_analysis_id (str) – ID of the holdout analysis to get
- Returns:
The holdout analysis
- Return type:
- list_holdout_analysis_versions(holdout_analysis_id)
List holdout analysis versions for a holdout analysis.
- Parameters:
holdout_analysis_id (str) – ID of the holdout analysis to list holdout analysis versions for
- Returns:
The holdout analysis versions
- Return type:
- describe_holdout_analysis_version(holdout_analysis_version, get_metrics=False)
Get a holdout analysis version.
- Parameters:
- Returns:
The holdout analysis version
- Return type:
- describe_monitor_alert(monitor_alert_id)
Describes a given monitor alert id
- Parameters:
monitor_alert_id (str) – Unique identifier of the monitor alert.
- Returns:
Object containing information about the monitor alert.
- Return type:
- describe_monitor_alert_version(monitor_alert_version)
Describes a given monitor alert version id
- Parameters:
monitor_alert_version (str) – Unique string identifier for the monitor alert.
- Returns:
An object describing the monitor alert version.
- Return type:
- list_monitor_alerts_for_monitor(model_monitor_id)
Retrieves the list of monitor alerts for a specified monitor.
- Parameters:
model_monitor_id (str) – The unique ID associated with the model monitor.
- Returns:
A list of monitor alerts.
- Return type:
- list_monitor_alert_versions_for_monitor_version(model_monitor_version)
Retrieves the list of monitor alert versions for a specified monitor instance.
- Parameters:
model_monitor_version (str) – The unique ID associated with the model monitor.
- Returns:
A list of monitor alert versions.
- Return type:
- get_model_monitoring_logs(model_monitor_version, stdout=False, stderr=False)
Returns monitoring logs for the model.
- Parameters:
- Returns:
A function logs.
- Return type:
- get_drift_for_feature(model_monitor_version, feature_name, nested_feature_name=None)
Gets the feature drift associated with a single feature in an output feature group from a prediction.
- Parameters:
- Returns:
An object describing the training and prediction output feature distributions.
- Return type:
- get_outliers_for_feature(model_monitor_version, feature_name=None, nested_feature_name=None)
Gets a list of outliers measured by a single feature (or overall) in an output feature group from a prediction.
- Parameters:
- Return type:
Dict
- describe_prediction_operator(prediction_operator_id)
Describe an existing prediction operator.
- Parameters:
prediction_operator_id (str) – The unique ID of the prediction operator. Returns
- Return type:
- list_prediction_operators(project_id)
List all the prediction operators inside a project.
- Parameters:
project_id (str) – The unique ID of the project. Returns
- Return type:
- list_prediction_operator_versions(prediction_operator_id)
List all the prediction operator versions for a prediction operator.
- Parameters:
prediction_operator_id (str) – The unique ID of the prediction operator.
- Returns:
A list of prediction operator version objects.
- Return type:
- describe_deployment(deployment_id)
Retrieves a full description of the specified deployment.
- Parameters:
deployment_id (str) – Unique string identifier associated with the deployment.
- Returns:
Description of the deployment.
- Return type:
- list_deployments(project_id)
Retrieves a list of all deployments in the specified project.
- Parameters:
project_id (str) – The unique identifier associated with the project.
- Returns:
An array of deployments.
- Return type:
- list_deployment_tokens(project_id)
Retrieves a list of all deployment tokens associated with the specified project.
- Parameters:
project_id (str) – The unique ID associated with the project.
- Returns:
A list of deployment tokens.
- Return type:
- get_api_endpoint(deployment_token=None, deployment_id=None, streaming_token=None, feature_group_id=None, model_id=None)
Returns the API endpoint specific to an organization. This function can be utilized using either an API Key or a deployment ID and token for authentication.
- Parameters:
deployment_token (str) – Token used for authenticating access to deployed models.
deployment_id (str) – Unique identifier assigned to a deployment created under the specified project.
streaming_token (str) – Token used for authenticating access to streaming data.
feature_group_id (str) – Unique identifier assigned to a feature group.
model_id (str) – Unique identifier assigned to a model.
- Returns:
The API endpoint specific to the organization.
- Return type:
- get_model_training_types_for_deployment(model_id, model_version=None, algorithm=None)
Returns types of models that can be deployed for a given model instance ID.
- Parameters:
- Returns:
Model training types for deployment.
- Return type:
- describe_refresh_policy(refresh_policy_id)
Retrieve a single refresh policy
- Parameters:
refresh_policy_id (str) – The unique ID associated with this refresh policy.
- Returns:
An object representing the refresh policy.
- Return type:
- describe_refresh_pipeline_run(refresh_pipeline_run_id)
Retrieve a single refresh pipeline run
- Parameters:
refresh_pipeline_run_id (str) – Unique string identifier associated with the refresh pipeline run.
- Returns:
A refresh pipeline run object.
- Return type:
- list_refresh_policies(project_id=None, dataset_ids=[], feature_group_id=None, model_ids=[], deployment_ids=[], batch_prediction_ids=[], model_monitor_ids=[], prediction_metric_ids=[], notebook_ids=[])
List the refresh policies for the organization
- Parameters:
project_id (str) – Optionally, a Project ID can be specified so that all datasets, models, deployments, batch predictions, prediction metrics, model monitors, and notebooks are captured at the instant this policy was created.
dataset_ids (list) – Comma-separated list of Dataset IDs.
feature_group_id (str) – Feature Group ID for which we wish to see the refresh policies attached.
model_ids (list) – Comma-separated list of Model IDs.
deployment_ids (list) – Comma-separated list of Deployment IDs.
batch_prediction_ids (list) – Comma-separated list of Batch Prediction IDs.
model_monitor_ids (list) – Comma-separated list of Model Monitor IDs.
prediction_metric_ids (list) – Comma-separated list of Prediction Metric IDs.
notebook_ids (list) – Comma-separated list of Notebook IDs.
- Returns:
List of all refresh policies in the organization.
- Return type:
- list_refresh_pipeline_runs(refresh_policy_id)
List the the times that the refresh policy has been run
- Parameters:
refresh_policy_id (str) – Unique identifier associated with the refresh policy.
- Returns:
List of refresh pipeline runs for the given refresh policy ID.
- Return type:
- download_batch_prediction_result_chunk(batch_prediction_version, offset=0, chunk_size=10485760)
Returns a stream containing the batch prediction results.
- Parameters:
- Return type:
- get_batch_prediction_connector_errors(batch_prediction_version)
Returns a stream containing the batch prediction database connection write errors, if any writes failed for the specified batch prediction job.
- Parameters:
batch_prediction_version (str) – Unique string identifier of the batch prediction job to get the errors for.
- Return type:
- list_batch_predictions(project_id)
Retrieves a list of batch predictions in the project.
- Parameters:
project_id (str) – Unique string identifier of the project.
- Returns:
List of batch prediction jobs.
- Return type:
- describe_batch_prediction(batch_prediction_id)
Describe the batch prediction.
- Parameters:
batch_prediction_id (str) – The unique identifier associated with the batch prediction.
- Returns:
The batch prediction description.
- Return type:
- list_batch_prediction_versions(batch_prediction_id, limit=100, start_after_version=None)
Retrieves a list of versions of a given batch prediction
- Parameters:
- Returns:
List of batch prediction versions.
- Return type:
- describe_batch_prediction_version(batch_prediction_version)
Describes a Batch Prediction Version.
- Parameters:
batch_prediction_version (str) – Unique string identifier of the Batch Prediction Version.
- Returns:
The Batch Prediction Version.
- Return type:
- get_data(feature_group_id, primary_key=None, num_rows=None)
Gets the feature group rows.
If primary key is set, row corresponding to primary_key is returned. If num_rows is set, we return maximum of num_rows latest updated rows.
- Parameters:
- Return type:
- list_pending_feature_group_documents(feature_group_id)
Lists all pending documents added to feature group.
- Parameters:
feature_group_id (str) – The unique ID associated with the feature group.
- Return type:
- describe_python_function(name)
Describe a Python Function.
- Parameters:
name (str) – The name to identify the Python function.
- Returns:
The Python function object.
- Return type:
- list_python_functions(function_type='FEATURE_GROUP')
List all python functions within the organization.
- Parameters:
function_type (str) – Optional argument to specify the type of function to list Python functions for; defaults to FEATURE_GROUP.
- Returns:
A list of PythonFunction objects.
- Return type:
- list_pipelines(project_id=None)
Lists the pipelines for an organization or a project
- describe_pipeline_version(pipeline_version)
Describes a specified pipeline version
- Parameters:
pipeline_version (str) – Unique string identifier for the pipeline version
- Returns:
Object describing the pipeline version
- Return type:
- describe_pipeline_step(pipeline_step_id)
Deletes a step from a pipeline.
- Parameters:
pipeline_step_id (str) – The ID of the pipeline step.
- Returns:
An object describing the pipeline step.
- Return type:
- describe_pipeline_step_by_name(pipeline_id, step_name)
Describes a pipeline step by the step name.
- Parameters:
- Returns:
An object describing the pipeline step.
- Return type:
- describe_pipeline_step_version(pipeline_step_version)
Describes a pipeline step version.
- Parameters:
pipeline_step_version (str) – The ID of the pipeline step version.
- Return type:
- list_pipeline_version_logs(pipeline_version)
Gets the logs for the steps in a given pipeline version.
- Parameters:
pipeline_version (str) – The id of the pipeline version.
- Returns:
Object describing the logs for the steps in the pipeline.
- Return type:
- get_step_version_logs(pipeline_step_version)
Gets the logs for a given step version.
- Parameters:
pipeline_step_version (str) – The id of the pipeline step version.
- Returns:
Object describing the pipeline step logs.
- Return type:
- describe_graph_dashboard(graph_dashboard_id)
Describes a given graph dashboard.
- Parameters:
graph_dashboard_id (str) – Unique identifier for the graph dashboard.
- Returns:
An object containing information about the graph dashboard.
- Return type:
- list_graph_dashboards(project_id=None)
Lists the graph dashboards for a project
- Parameters:
project_id (str) – Unique string identifier for the project to list graph dashboards from.
- Returns:
A list of graph dashboards.
- Return type:
- delete_graph_from_dashboard(graph_reference_id)
Deletes a python plot function from a dashboard
- Parameters:
graph_reference_id (str) – Unique String Identifier for the graph
- describe_graph_for_dashboard(graph_reference_id)
Describes a python plot to a graph dashboard
- Parameters:
graph_reference_id (str) – Unique string identifier for the python function id for the graph
- Returns:
An object describing the graph dashboard.
- Return type:
- describe_algorithm(algorithm)
Retrieves a full description of the specified algorithm.
- list_algorithms(problem_type=None, project_id=None)
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- Parameters:
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