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get_classifiers

get_classifiers(
    *,
    config_overrides: Optional[GlueClientConfig] = None,
    max_results: Optional[PageSize] = None,
    next_token: Optional[Token] = None,
) -> GetClassifiersResponse

Lists all classifier objects in the Data Catalog.

Parameters:

  • max_results (Optional[PageSize], default: None ) –

    The size of the list to return (optional).

  • next_token (Optional[Token], default: None ) –

    An optional continuation token.

Raises:

Source code in docs_src/capo_glue/_services/glue.py
def get_classifiers(
    self,
    *,
    config_overrides: Optional[GlueClientConfig] = None,
    max_results: Optional["capo_glue.types.page_size.PageSize"] = None,
    next_token: Optional["capo_glue.types.token.Token"] = None,
) -> "capo_glue.types.get_classifiers_response.GetClassifiersResponse":
    """<p>Lists all classifier objects in the Data Catalog.</p>

    Args:
        max_results: <p>The size of the list to return (optional).</p>
        next_token: <p>An optional continuation token.</p>

    Raises:
        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.get_classifiers_request.GetClassifiersRequest]",
    ) -> OperationResponse[
        "capo_glue.types.get_classifiers_response.GetClassifiersResponse"
    ]:
        import capo_glue._operations.aws_glue.get_classifiers

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetClassifiers")
    )
    input_: capo_glue.types.get_classifiers_request.GetClassifiersRequest = {}
    if max_results is not None:
        input_["max_results"] = max_results
    if next_token is not None:
        input_["next_token"] = next_token

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