def process_indexed_function()

in azure_functions_worker/loader.py [0:0]

• 28 lines of code
• 3 McCabe index (conditional complexity)

def process_indexed_function(functions_registry: functions.Registry,
                             indexed_functions, function_dir):
    """
    fx_metadata_results is a list of the RpcFunctionMetadata for
    all the functions in the particular app.

    fx_binding_logs represents a dictionary of each function in
    the app and its corresponding bindings. The raw bindings and
    binding logs are generated from the base extension if the
    function is using deferred bindings. If not, the raw bindings
    come from the azure-functions sdk and no additional binding
    logs are generated.
    """
    fx_metadata_results = []
    fx_bindings_logs = {}
    for indexed_function in indexed_functions:
        function_info = functions_registry.add_indexed_function(
            function=indexed_function)

        binding_protos = build_binding_protos(indexed_function)
        retry_protos = build_retry_protos(indexed_function)

        raw_bindings, bindings_logs = get_fx_raw_bindings(
            indexed_function=indexed_function,
            function_info=function_info)

        function_metadata = protos.RpcFunctionMetadata(
            name=function_info.name,
            function_id=function_info.function_id,
            managed_dependency_enabled=False,  # only enabled for PowerShell
            directory=function_dir,
            script_file=indexed_function.function_script_file,
            entry_point=function_info.name,
            is_proxy=False,  # not supported in V4
            language=PYTHON_LANGUAGE_RUNTIME,
            bindings=binding_protos,
            raw_bindings=raw_bindings,
            retry_options=retry_protos,
            properties={METADATA_PROPERTIES_WORKER_INDEXED: "True"})

        fx_bindings_logs.update({indexed_function: bindings_logs})
        fx_metadata_results.append(function_metadata)

    return fx_metadata_results, fx_bindings_logs