list_ml_transforms ¶

def list_ml_transforms(
    self,
    *,
    config_overrides: Optional[GlueClientConfig] = None,
    next_token: Optional["capo_glue.types.pagination_token.PaginationToken"] = None,
    max_results: Optional["capo_glue.types.page_size.PageSize"] = None,
    filter: Optional[
        "capo_glue.types.transform_filter_criteria.TransformFilterCriteria"
    ] = None,
    sort: Optional[
        "capo_glue.types.transform_sort_criteria.TransformSortCriteria"
    ] = None,
    tags: Optional["capo_glue.types.tags_map.TagsMap"] = None,
) -> "capo_glue.types.list_ml_transforms_response.ListMLTransformsResponse":
    """<p> Retrieves a sortable, filterable list of existing Glue machine learning transforms in this Amazon Web Services account, or the resources with the specified tag. This operation takes the optional <code>Tags</code> field, which you can use as a filter of the responses so that tagged resources can be retrieved as a group. If you choose to use tag filtering, only resources with the tags are retrieved. </p>

    Args:
        next_token: <p>A continuation token, if this is a continuation request.</p>
        max_results: <p>The maximum size of a list to return.</p>
        filter: <p>A <code>TransformFilterCriteria</code> used to filter the machine learning transforms.</p>
        sort: <p>A <code>TransformSortCriteria</code> used to sort the machine learning transforms.</p>
        tags: <p>Specifies to return only these tagged resources.</p>

    Raises:
        capo_glue.errors.entity_not_found_exception.EntityNotFoundException: <p>A specified entity does not exist</p>
        capo_glue.errors.internal_service_exception.InternalServiceException: <p>An internal service error occurred.</p>
        capo_glue.errors.invalid_input_exception.InvalidInputException: <p>The input provided was not valid.</p>
        capo_glue.errors.operation_timeout_exception.OperationTimeoutException: <p>The operation timed out.</p>
        capo_glue.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_glue.types.list_ml_transforms_request.ListMLTransformsRequest]",
    ) -> OperationResponse[
        "capo_glue.types.list_ml_transforms_response.ListMLTransformsResponse"
    ]:
        import capo_glue._operations.aws_glue.list_ml_transforms

        output, http_response = (
            capo_glue._operations.aws_glue.list_ml_transforms.list_ml_transforms(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListMLTransforms")
    )
    input_: capo_glue.types.list_ml_transforms_request.ListMLTransformsRequest = {}
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results
    if filter is not None:
        input_["filter"] = filter
    if sort is not None:
        input_["sort"] = sort
    if tags is not None:
        input_["tags"] = tags

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