update_data_source ¶

update_data_source(
    data_source_id: EntityId,
    data_source_name: EntityName,
    *,
    config_overrides: Optional[MachineLearningClientConfig] = None,
) -> UpdateDataSourceOutput

Updates the DataSourceName of a DataSource.

You can use the GetDataSource operation to view the contents of the updated data element.

Parameters:

data_source_id (EntityId) –

The ID assigned to the DataSource during creation.
data_source_name (EntityName) –

A new user-supplied name or description of the DataSource that will replace the current description.

Raises:

InternalServerException –

An error on the server occurred when trying to process a request.
InvalidInputException –

An error on the client occurred. Typically, the cause is an invalid input value.
ResourceNotFoundException –

A specified resource cannot be located.
UnknownServiceError –

The service returned an error code this client does not model.

Source code in docs_src/capo_machine_learning/_services/machine_learning.py

def update_data_source(
    self,
    data_source_id: "capo_machine_learning.types.entity_id.EntityId",
    data_source_name: "capo_machine_learning.types.entity_name.EntityName",
    *,
    config_overrides: Optional[MachineLearningClientConfig] = None,
) -> "capo_machine_learning.types.update_data_source_output.UpdateDataSourceOutput":
    """<p>Updates the <code>DataSourceName</code> of a <code>DataSource</code>.</p> <p>You can use the <code>GetDataSource</code> operation to view the contents of the updated data element.</p>

    Args:
        data_source_id: <p>The ID assigned to the <code>DataSource</code> during creation.</p>
        data_source_name: <p>A new user-supplied name or description of the <code>DataSource</code> that will replace the current description. </p>

    Raises:
        capo_machine_learning.errors.internal_server_exception.InternalServerException: <p>An error on the server occurred when trying to process a request.</p>
        capo_machine_learning.errors.invalid_input_exception.InvalidInputException: <p>An error on the client occurred. Typically, the cause is an invalid input value.</p>
        capo_machine_learning.errors.resource_not_found_exception.ResourceNotFoundException: <p>A specified resource cannot be located.</p>
        capo_machine_learning.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_machine_learning.types.update_data_source_input.UpdateDataSourceInput]",
    ) -> OperationResponse[
        "capo_machine_learning.types.update_data_source_output.UpdateDataSourceOutput"
    ]:
        import capo_machine_learning._operations.amazon_ml_20141212.update_data_source

        output, http_response = (
            capo_machine_learning._operations.amazon_ml_20141212.update_data_source.update_data_source(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UpdateDataSource")
    )
    input_: capo_machine_learning.types.update_data_source_input.UpdateDataSourceInput = {
        "data_source_id": data_source_id,
        "data_source_name": data_source_name,
    }

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output