Class TablesClient (0.9.0)

TablesClient(
    project=None,
    region="us-central1",
    credentials=None,
    client=None,
    prediction_client=None,
    gcs_client=None,
    **kwargs
)

AutoML Tables API helper.

This is intended to simplify usage of the auto-generated python client, in particular for the AutoML Tables product <https://cloud.google.com/automl-tables/>_.

Methods

TablesClient

TablesClient(
    project=None,
    region="us-central1",
    credentials=None,
    client=None,
    prediction_client=None,
    gcs_client=None,
    **kwargs
)

Constructor.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The project ID of the GCP project all future calls will default to. Most methods take `project` as an optional parameter, and can override your choice of `project` supplied here.
`region`	`Optional[str]` The region all future calls will default to. Most methods take `region` as an optional parameter, and can override your choice of `region` supplied here. Note, only `us-central1` is supported to-date.
`transport`	`Union[.AutoMlGrpcTransport, Callable[[.Credentials, type], .AutoMlGrpcTransport]` A transport instance, responsible for actually making the API calls. The default transport uses the gRPC protocol. This argument may also be a callable which returns a transport instance. Callables will be sent the credentials as the first argument and the default transport class as the second argument.
`channel`	`grpc.Channel` DEPRECATED. A `Channel` instance through which to make calls. This argument is mutually exclusive with `credentials`; providing both will raise an exception.
`credentials`	`google.auth.credentials.Credentials` The authorization credentials to attach to requests. These credentials identify this application to the service. If none are specified, the client will attempt to ascertain the credentials from the environment. This argument is mutually exclusive with providing a transport instance to `transport`; doing so will raise an exception.
`client_config`	`dict` DEPRECATED. A dictionary of call options for each method. If not specified, the default configuration is used.
`client_options`	`Union[dict, google.api_core.client_options.ClientOptions]` Client options used to set user options on the client. API Endpoint should be set through client_options.

batch_predict

batch_predict(
    pandas_dataframe=None,
    bigquery_input_uri=None,
    bigquery_output_uri=None,
    gcs_input_uris=None,
    gcs_output_uri_prefix=None,
    model=None,
    model_name=None,
    model_display_name=None,
    project=None,
    region=None,
    credentials=None,
    inputs=None,
    **kwargs
)

Makes a batch prediction on a model. This does not require the model to be deployed.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the model. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`credentials`	`Optional[google.auth.credentials.Credentials]` The authorization credentials to attach to requests. These credentials identify this application to the service. If none are specified, the client will attempt to ascertain the credentials from the environment.
`pandas_dataframe`	`Optional[pandas.DataFrame]` A Pandas Dataframe object containing the data you want to predict off of. The data will be converted to CSV, and this CSV will be staged to GCS in `gs://{project}-automl-tables-staging/{uploaded_csv_name}` This must be supplied if neither `gcs_input_uris` nor `bigquery_input_uri` is supplied.
`gcs_input_uris`	`Optional(Union[List[str], str])` Either a list of or a single GCS URI containing the data you want to predict off of. This must be supplied if neither `pandas_dataframe` nor `bigquery_input_uri` is supplied.
`gcs_output_uri_prefix`	`Optional[str]` The folder in GCS you want to write output to. This must be supplied if `bigquery_output_uri` is not.
`bigquery_input_uri`	`Optional[str]` The BigQuery table to input data from. This must be supplied if neither `pandas_dataframe` nor `gcs_input_uris` is supplied.
`bigquery_output_uri`	`Optional[str]` The BigQuery table to output data to. This must be supplied if `gcs_output_uri_prefix` is not.
`model_display_name`	`Optional[str]` The human-readable name given to the model you want to predict with. This must be supplied if `model` or `model_name` are not supplied.
`model_name`	`Optional[str]` The AutoML-assigned name given to the model you want to predict with. This must be supplied if `model_display_name` or `model` are not supplied.
`model`	`Optional[model]` The `model` instance you want to predict with . This must be supplied if `model_display_name` or `model_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

Returns

Type	Description
`google.api_core.operation.Operation`	An operation future that can be used to check for completion synchronously or asynchronously.

clear_test_train_column

clear_test_train_column(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    project=None,
    region=None,
    **kwargs
)

Clears the test/train (ml_use) column which designates which data belongs to the test and train sets.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the table. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to update the test/train column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the test/train column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to update the test/train column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the test/train column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_display_name` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to update the test/train column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the test/train column of. This must be supplied if `table_spec_name`, `dataset_name` or `dataset_display_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

clear_time_column

clear_time_column(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    project=None,
    region=None,
    **kwargs
)

Clears the time column which designates which data will be of type timestamp and will be used for the timeseries data.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the table. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to update the time column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the time column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to update the time column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the time column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_display_name` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to update the time column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the time column of. This must be supplied if `table_spec_name`, `dataset_name` or `dataset_display_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

clear_weight_column

clear_weight_column(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    project=None,
    region=None,
    **kwargs
)

Clears the weight column for a given dataset.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the table. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to update the weight column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the weight column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to update the weight column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the weight column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_display_name` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to update the weight column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the weight column of. This must be supplied if `table_spec_name`, `dataset_name` or `dataset_display_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

create_dataset

create_dataset(
    dataset_display_name, metadata={}, project=None, region=None, **kwargs
)

Create a dataset. Keep in mind, importing data is a separate step.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that will own the dataset. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`dataset_display_name`	`str` A human-readable name to refer to this dataset by.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

create_model

create_model(
    model_display_name,
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    train_budget_milli_node_hours=None,
    optimization_objective=None,
    project=None,
    region=None,
    model_metadata=None,
    include_column_spec_names=None,
    exclude_column_spec_names=None,
    disable_early_stopping=False,
    **kwargs
)

Create a model. This will train your model on the given dataset.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that will own the model. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`model_display_name`	`str` A human-readable name to refer to this model by.
`train_budget_milli_node_hours`	`int` The amount of time (in thousandths of an hour) to spend training. This value must be between 1,000 and 72,000 inclusive (between 1 and 72 hours).
`optimization_objective`	`str` The metric AutoML tables should optimize for.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to train your model on. This must be supplied if `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to train your model on. This must be supplied if `dataset_display_name` or `dataset` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to train your model on. This must be supplied if `dataset_display_name` or `dataset_name` are not supplied.
`model_metadata`	`Optional[Dict]` Optional model metadata to supply to the client.
`include_column_spec_names`	`Optional[str]` The list of the names of the columns you want to include to train your model on.
`exclude_column_spec_names`	`Optional[str]` The list of the names of the columns you want to exclude and not train your model on.
`disable_early_stopping`	`Optional[bool]` True if disable early stopping. By default, the early stopping feature is enabled, which means that AutoML Tables might stop training before the entire training budget has been used.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

Returns

Type	Description
`google.api_core.operation.Operation`	An operation future that can be used to check for completion synchronously or asynchronously.

delete_dataset

delete_dataset(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    project=None,
    region=None,
    **kwargs
)

Deletes a dataset. This does not delete any models trained on this dataset.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the dataset. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to delete. This must be supplied if `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to delete. This must be supplied if `dataset_display_name` or `dataset` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to delete. This must be supplied if `dataset_display_name` or `dataset_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

Returns

Type	Description
`google.api_core.operation.Operation`	An operation future that can be used to check for completion synchronously or asynchronously.

delete_model

delete_model(
    model=None,
    model_display_name=None,
    model_name=None,
    project=None,
    region=None,
    **kwargs
)

Deletes a model. Note this will not delete any datasets associated with this model.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the model. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`model_display_name`	`Optional[str]` The human-readable name given to the model you want to delete. This must be supplied if `model` or `model_name` are not supplied.
`model_name`	`Optional[str]` The AutoML-assigned name given to the model you want to delete. This must be supplied if `model_display_name` or `model` are not supplied.
`model`	`Optional[model]` The `model` instance you want to delete. This must be supplied if `model_display_name` or `model_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

Returns

Type	Description
`google.api_core.operation.Operation`	An operation future that can be used to check for completion synchronously or asynchronously.

deploy_model

deploy_model(
    model=None,
    model_name=None,
    model_display_name=None,
    project=None,
    region=None,
    **kwargs
)

Deploys a model. This allows you make online predictions using the model you've deployed.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the model. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`model_display_name`	`Optional[str]` The human-readable name given to the model you want to deploy. This must be supplied if `model` or `model_name` are not supplied.
`model_name`	`Optional[str]` The AutoML-assigned name given to the model you want to deploy. This must be supplied if `model_display_name` or `model` are not supplied.
`model`	`Optional[model]` The `model` instance you want to deploy. This must be supplied if `model_display_name` or `model_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

Returns

Type	Description
`google.api_core.operation.Operation`	An operation future that can be used to check for completion synchronously or asynchronously.

export_data

export_data(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    gcs_output_uri_prefix=None,
    bigquery_output_uri=None,
    project=None,
    region=None,
    **kwargs
)

Exports data from a dataset.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the dataset. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to export data from. This must be supplied if `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to export data from. This must be supplied if `dataset_display_name` or `dataset` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to export data from. This must be supplied if `dataset_display_name` or `dataset_name` are not supplied.
`gcs_output_uri_prefix`	`Optional[Union[str, Sequence[str]]]` A single `gs://..` prefixed URI to export to. This must be supplied if `bigquery_output_uri` is not.
`bigquery_output_uri`	`Optional[str]` A URI pointing to the BigQuery table containing the data to export. This must be supplied if `gcs_output_uri_prefix` is not.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

Returns

Type	Description
`google.api_core.operation.Operation`	An operation future that can be used to check for completion synchronously or asynchronously.

get_column_spec

get_column_spec(column_spec_name, project=None, region=None, **kwargs)

Gets a single column spec in a particular project and region.

.. rubric:: Example

Parameters

Name	Description
`column_spec_name`	`str` This is the fully-qualified name generated by the AutoML API for this column spec.
`project`	`Optional[str]` The ID of the project that owns the column. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

get_dataset

get_dataset(
    project=None, region=None, dataset_name=None, dataset_display_name=None, **kwargs
)

Gets a single dataset in a particular project and region.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the dataset. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`dataset_name`	`Optional[str]` This is the fully-qualified name generated by the AutoML API for this dataset. This is not to be confused with the human-assigned `dataset_display_name` that is provided when creating a dataset. Either `dataset_name` or `dataset_display_name` must be provided.
`dataset_display_name`	`Optional[str]` This is the name you provided for the dataset when first creating it. Either `dataset_name` or `dataset_display_name` must be provided.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

get_model

get_model(
    project=None, region=None, model_name=None, model_display_name=None, **kwargs
)

Gets a single model in a particular project and region.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the model. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`model_name`	`Optional[str]` This is the fully-qualified name generated by the AutoML API for this model. This is not to be confused with the human-assigned `model_display_name` that is provided when creating a model. Either `model_name` or `model_display_name` must be provided.
`model_display_name`	`Optional[str]` This is the name you provided for the model when first creating it. Either `model_name` or `model_display_name` must be provided.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

get_model_evaluation

get_model_evaluation(model_evaluation_name, project=None, region=None, **kwargs)

Gets a single evaluation model in a particular project and region.

.. rubric:: Example

Parameters

Name	Description
`model_evaluation_name`	`str` This is the fully-qualified name generated by the AutoML API for this model evaluation.
`project`	`Optional[str]` The ID of the project that owns the model. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

get_table_spec

get_table_spec(table_spec_name, project=None, region=None, **kwargs)

Gets a single table spec in a particular project and region.

.. rubric:: Example

Parameters

Name	Description
`table_spec_name`	`str` This is the fully-qualified name generated by the AutoML API for this table spec.
`project`	`Optional[str]` The ID of the project that owns the table. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

import_data

import_data(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    pandas_dataframe=None,
    gcs_input_uris=None,
    bigquery_input_uri=None,
    project=None,
    region=None,
    credentials=None,
    **kwargs
)

Imports data into a dataset.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the dataset. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`credentials`	`Optional[google.auth.credentials.Credentials]` The authorization credentials to attach to requests. These credentials identify this application to the service. If none are specified, the client will attempt to ascertain the credentials from the environment.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to import data into. This must be supplied if `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to import data into. This must be supplied if `dataset_display_name` or `dataset` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to import data into. This must be supplied if `dataset_display_name` or `dataset_name` are not supplied.
`pandas_dataframe`	`Optional[pandas.DataFrame]` A Pandas Dataframe object containing the data to import. The data will be converted to CSV, and this CSV will be staged to GCS in `gs://{project}-automl-tables-staging/{uploaded_csv_name}` This parameter must be supplied if neither `gcs_input_uris` nor `bigquery_input_uri` is supplied.
`gcs_input_uris`	`Optional[Union[str, Sequence[str]]]` Either a single `gs://..` prefixed URI, or a list of URIs referring to GCS-hosted CSV files containing the data to import. This must be supplied if neither `bigquery_input_uri` nor `pandas_dataframe` is supplied.
`bigquery_input_uri`	`Optional[str]` A URI pointing to the BigQuery table containing the data to import. This must be supplied if neither `gcs_input_uris` nor `pandas_dataframe` is supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

Returns

Type	Description
`google.api_core.operation.Operation`	An operation future that can be used to check for completion synchronously or asynchronously.

list_column_specs

list_column_specs(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    table_spec_name=None,
    table_spec_index=0,
    project=None,
    region=None,
    **kwargs
)

Lists column specs.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the columns. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`table_spec_name`	`Optional[str]` The AutoML-assigned name for the table whose specs you want to read. If not supplied, the client can determine this name from a source `Dataset` object.
`table_spec_index`	`Optional[int]` If no `table_spec_name` was provided, we use this index to determine which table to read column specs from.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to read specs from. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to read specs from. This must be supplied if `table_spec_name`, `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to read specs from. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to read specs from. This must be supplied if `table_spec_name`, `dataset` or `dataset_display_name` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to read specs from. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to read specs from. This must be supplied if `table_spec_name`, `dataset_name` or `dataset_display_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

list_datasets

list_datasets(project=None, region=None, **kwargs)

List all datasets in a particular project and region.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the datasets. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

list_model_evaluations

list_model_evaluations(
    project=None,
    region=None,
    model=None,
    model_display_name=None,
    model_name=None,
    **kwargs
)

List all model evaluations for a given model.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the model. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`model_display_name`	`Optional[str]` The human-readable name given to the model you want to list evaluations for. This must be supplied if `model` or `model_name` are not supplied.
`model_name`	`Optional[str]` The AutoML-assigned name given to the model you want to list evaluations for. This must be supplied if `model_display_name` or `model` are not supplied.
`model`	`Optional[model]` The `model` instance you want to list evaluations for. This must be supplied if `model_display_name` or `model_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

list_models

list_models(project=None, region=None, **kwargs)

List all models in a particular project and region.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the models. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

list_table_specs

list_table_specs(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    project=None,
    region=None,
    **kwargs
)

Lists table specs.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the dataset. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to read specs from. This must be supplied if `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to read specs from. This must be supplied if `dataset_display_name` or `dataset` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to read specs from. This must be supplied if `dataset_display_name` or `dataset_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

predict

predict(
    inputs,
    model=None,
    model_name=None,
    model_display_name=None,
    feature_importance=False,
    project=None,
    region=None,
    **kwargs
)

Makes a prediction on a deployed model. This will fail if the model was not deployed.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the model. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`inputs`	`Union[List[str], Dict[str, str]]` Either the sorted list of column values to predict with, or a key-value map of column display name to value to predict with.
`model_display_name`	`Optional[str]` The human-readable name given to the model you want to predict with. This must be supplied if `model` or `model_name` are not supplied.
`model_name`	`Optional[str]` The AutoML-assigned name given to the model you want to predict with. This must be supplied if `model_display_name` or `model` are not supplied.
`model`	`Optional[model]` The `model` instance you want to predict with . This must be supplied if `model_display_name` or `model_name` are not supplied.
`feature_importance`	`bool` True if enable feature importance explainability. The default is False.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

set_target_column

set_target_column(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    table_spec_name=None,
    table_spec_index=0,
    column_spec_name=None,
    column_spec_display_name=None,
    project=None,
    region=None,
    **kwargs
)

Sets the target column for a given table.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the table. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`column_spec_name`	`Optional[str]` The name AutoML-assigned name for the column you want to set as the target column.
`column_spec_display_name`	`Optional[str]` The human-readable name of the column you want to set as the target column. If this is supplied in place of `column_spec_name`, you also need to provide either a way to lookup the source dataset (using one of the `dataset*` kwargs), or the `table_spec_name` of the table this column belongs to.
`table_spec_name`	`Optional[str]` The AutoML-assigned name for the table whose target column you want to set . If not supplied, the client can determine this name from a source `Dataset` object.
`table_spec_index`	`Optional[int]` If no `table_spec_name` or `column_spec_name` was provided, we use this index to determine which table to set the target column on.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to update the target column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the target column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to update the target column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the target column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_display_name` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to update the target column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the target column of. This must be supplied if `table_spec_name`, `dataset_name` or `dataset_display_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

set_test_train_column

set_test_train_column(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    table_spec_name=None,
    table_spec_index=0,
    column_spec_name=None,
    column_spec_display_name=None,
    project=None,
    region=None,
    **kwargs
)

Sets the test/train (ml_use) column which designates which data belongs to the test and train sets. This column must be categorical.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the table. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`column_spec_name`	`Optional[str]` The name AutoML-assigned name for the column you want to set as the test/train column.
`column_spec_display_name`	`Optional[str]` The human-readable name of the column you want to set as the test/train column. If this is supplied in place of `column_spec_name`, you also need to provide either a way to lookup the source dataset (using one of the `dataset*` kwargs), or the `table_spec_name` of the table this column belongs to.
`table_spec_name`	`Optional[str]` The AutoML-assigned name for the table whose test/train column you want to set . If not supplied, the client can determine this name from a source `Dataset` object.
`table_spec_index`	`Optional[int]` If no `table_spec_name` or `column_spec_name` was provided, we use this index to determine which table to set the test/train column on.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to update the test/train column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the test/train column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to update the test/train column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the test/train column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_display_name` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to update the test/train column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the test/train column of. This must be supplied if `table_spec_name`, `dataset_name` or `dataset_display_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

set_time_column

set_time_column(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    table_spec_name=None,
    table_spec_index=0,
    column_spec_name=None,
    column_spec_display_name=None,
    project=None,
    region=None,
    **kwargs
)

Sets the time column which designates which data will be of type timestamp and will be used for the timeseries data. This column must be of type timestamp.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the table. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`column_spec_name`	`Optional[str]` The name AutoML-assigned name for the column you want to set as the time column.
`column_spec_display_name`	`Optional[str]` The human-readable name of the column you want to set as the time column. If this is supplied in place of `column_spec_name`, you also need to provide either a way to lookup the source dataset (using one of the `dataset*` kwargs), or the `table_spec_name` of the table this column belongs to.
`table_spec_name`	`Optional[str]` The AutoML-assigned name for the table whose time column you want to set . If not supplied, the client can determine this name from a source `Dataset` object.
`table_spec_index`	`Optional[int]` If no `table_spec_name` or `column_spec_name` was provided, we use this index to determine which table to set the time column on.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to update the time column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the time column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to update the time column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the time column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_display_name` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to update the time column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the time column of. This must be supplied if `table_spec_name`, `dataset_name` or `dataset_display_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

set_weight_column

set_weight_column(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    table_spec_name=None,
    table_spec_index=0,
    column_spec_name=None,
    column_spec_display_name=None,
    project=None,
    region=None,
    **kwargs
)

Sets the weight column for a given table.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the table. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`column_spec_name`	`Optional[str]` The name AutoML-assigned name for the column you want to set as the weight column.
`column_spec_display_name`	`Optional[str]` The human-readable name of the column you want to set as the weight column. If this is supplied in place of `column_spec_name`, you also need to provide either a way to lookup the source dataset (using one of the `dataset*` kwargs), or the `table_spec_name` of the table this column belongs to.
`table_spec_name`	`Optional[str]` The AutoML-assigned name for the table whose weight column you want to set . If not supplied, the client can determine this name from a source `Dataset` object.
`table_spec_index`	`Optional[int]` If no `table_spec_name` or `column_spec_name` was provided, we use this index to determine which table to set the weight column on.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to update the weight column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the weight column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to update the weight column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the weight column of. This must be supplied if `table_spec_name`, `dataset` or `dataset_display_name` are not supplied.
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to update the weight column of. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update the weight column of. This must be supplied if `table_spec_name`, `dataset_name` or `dataset_display_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

undeploy_model

undeploy_model(
    model=None,
    model_name=None,
    model_display_name=None,
    project=None,
    region=None,
    **kwargs
)

Undeploys a model.

.. rubric:: Example

Parameters

Name	Description
`project`	`Optional[str]` The ID of the project that owns the model. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.
`model_display_name`	`Optional[str]` The human-readable name given to the model you want to undeploy. This must be supplied if `model` or `model_name` are not supplied.
`model_name`	`Optional[str]` The AutoML-assigned name given to the model you want to undeploy. This must be supplied if `model_display_name` or `model` are not supplied.
`model`	`Optional[model]` The `model` instance you want to undeploy. This must be supplied if `model_display_name` or `model_name` are not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.

Returns

Type	Description
`google.api_core.operation.Operation`	An operation future that can be used to check for completion synchronously or asynchronously.

update_column_spec

update_column_spec(
    dataset=None,
    dataset_display_name=None,
    dataset_name=None,
    table_spec_name=None,
    table_spec_index=0,
    column_spec_name=None,
    column_spec_display_name=None,
    type_code=None,
    nullable=None,
    project=None,
    region=None,
    **kwargs
)

Updates a column's specs.

.. rubric:: Example

Parameters

Name	Description
`dataset`	`Optional[Dataset]` The `Dataset` instance you want to update specs on. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update specs on. This must be supplied if `table_spec_name`, `dataset_name` or `dataset_display_name` are not supplied.
`dataset_display_name`	`Optional[str]` The human-readable name given to the dataset you want to update specs on. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update specs on. This must be supplied if `table_spec_name`, `dataset` or `dataset_name` are not supplied.
`dataset_name`	`Optional[str]` The AutoML-assigned name given to the dataset you want to update specs one. If no `table_spec_name` is supplied, this will be used together with `table_spec_index` to infer the name of table to update specs on. This must be supplied if `table_spec_name`, `dataset` or `dataset_display_name` are not supplied.
`table_spec_name`	`Optional[str]` The AutoML-assigned name for the table whose specs you want to update. If not supplied, the client can determine this name from a source `Dataset` object.
`table_spec_index`	`Optional[int]` If no `table_spec_name` was provided, we use this index to determine which table to update column specs on.
`column_spec_name`	`Optional[str]` The name AutoML-assigned name for the column you want to update.
`column_spec_display_name`	`Optional[str]` The human-readable name of the column you want to update. If this is supplied in place of `column_spec_name`, you also need to provide either a way to lookup the source dataset (using one of the `dataset*` kwargs), or the `table_spec_name` of the table this column belongs to.
`type_code`	`Optional[str]` The desired 'type_code' of the column. For more information on the available types, please see the documentation: https://cloud.google.com/automl-tables/docs/reference/rpc/google.cloud.automl.v1beta1#typecode
`nullable`	`Optional[bool]` Set to `True` or `False` to specify if this column's value must expected to be present in all rows or not.
`project`	`Optional[str]` The ID of the project that owns the columns. If you have initialized the client with a value for `project` it will be used if this parameter is not supplied. Keep in mind, the service account this client was initialized with must have access to this project.
`region`	`Optional[str]` If you have initialized the client with a value for `region` it will be used if this parameter is not supplied.

Exceptions

Type	Description
`google.api_core.exceptions.GoogleAPICallError`	If the request failed for any reason.
`google.api_core.exceptions.RetryError`	If the request failed due to a retryable error and retry attempts failed.
`ValueError`	If required parameters are missing.