Gets a list of all CloudFront functions in your Amazon Web Services account.
You can optionally apply a filter to return only the functions that are in the specified stage, either DEVELOPMENT or LIVE.
You can optionally specify the maximum number of items to receive in the response. If the total number of items in the list exceeds the maximum that you specify, or the default maximum, the response is paginated. To get the next page of items, send a subsequent request that specifies the NextMarker value from the current response as the Marker value in the subsequent request.
Parameters:
-
marker
(Optional[string], default:
None
)
–
Use this field when paginating results to indicate where to begin in your list of functions. The response includes functions in the list that occur after the marker. To get the next page of the list, set this field's value to the value of NextMarker from the current page's response.
-
max_items
(Optional[integer], default:
None
)
–
The maximum number of functions that you want in the response.
-
stage
(Optional[FunctionStage], default:
None
)
–
An optional filter to return only the functions that are in the specified stage, either DEVELOPMENT or LIVE.
Raises:
Source code in docs_src/capo_cloudfront/_services/cloud_front.py
| def list_functions(
self,
*,
config_overrides: Optional[CloudFrontClientConfig] = None,
marker: Optional["capo_cloudfront.types.string.string"] = None,
max_items: Optional["capo_cloudfront.types.integer.integer"] = None,
stage: Optional["capo_cloudfront.types.function_stage.FunctionStage"] = None,
) -> "capo_cloudfront.types.list_functions_result.ListFunctionsResult":
"""<p>Gets a list of all CloudFront functions in your Amazon Web Services account.</p> <p>You can optionally apply a filter to return only the functions that are in the specified stage, either <code>DEVELOPMENT</code> or <code>LIVE</code>.</p> <p>You can optionally specify the maximum number of items to receive in the response. If the total number of items in the list exceeds the maximum that you specify, or the default maximum, the response is paginated. To get the next page of items, send a subsequent request that specifies the <code>NextMarker</code> value from the current response as the <code>Marker</code> value in the subsequent request.</p>
Args:
marker: <p>Use this field when paginating results to indicate where to begin in your list of functions. The response includes functions in the list that occur after the marker. To get the next page of the list, set this field's value to the value of <code>NextMarker</code> from the current page's response.</p>
max_items: <p>The maximum number of functions that you want in the response.</p>
stage: <p>An optional filter to return only the functions that are in the specified stage, either <code>DEVELOPMENT</code> or <code>LIVE</code>.</p>
Raises:
capo_cloudfront.errors.invalid_argument.InvalidArgument: <p>An argument is invalid.</p>
capo_cloudfront.errors.unsupported_operation.UnsupportedOperation: <p>This operation is not supported in this Amazon Web Services Region.</p>
capo_cloudfront.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_cloudfront.types.list_functions_request.ListFunctionsRequest]",
) -> OperationResponse[
"capo_cloudfront.types.list_functions_result.ListFunctionsResult"
]:
import capo_cloudfront._operations.cloudfront2020_05_31.list_functions
output, http_response = (
capo_cloudfront._operations.cloudfront2020_05_31.list_functions.list_functions(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("ListFunctions")
)
input_: capo_cloudfront.types.list_functions_request.ListFunctionsRequest = {}
if marker is not None:
input_["marker"] = marker
if max_items is not None:
input_["max_items"] = max_items
if stage is not None:
input_["stage"] = stage
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|