def update_execution(filename: str) -> jsonify:
service_type = request.args.get(Constants.TYPE_PARAM_NAME)
description = request.json[Constants.DESCRIPTION_FIELD_NAME]
class_method_name = request.json[Constants.METHOD_FIELD_NAME]
method_parameters = request.json[Constants.METHOD_PARAMETERS_FIELD_NAME]
storage = None
if service_type == Constants.EXPLORE_TENSORFLOW_TYPE or \
service_type == Constants.EXPLORE_SCIKITLEARN_TYPE:
storage = explore_storage
elif service_type == Constants.TRANSFORM_TENSORFLOW_TYPE or \
Constants.TRANSFORM_SCIKITLEARN_TYPE:
storage = transform_storage
data = Data(database, storage)
request_errors = analyse_patch_request_errors(request_validator, data,
filename, class_method_name,
method_parameters)
if request_errors is not None:
return request_errors
module_path, class_name = data.get_module_and_class(filename)
class_parameters = data.get_class_parameters(filename)
parameters = Parameters(database, data)
metadata_creator = Metadata(database)
execution = Execution(database, filename, service_type, storage,
metadata_creator, module_path, class_name,
class_parameters, parameters)
execution.update(class_method_name, method_parameters, description)
response_params = None
if service_type == Constants.TRANSFORM_TENSORFLOW_TYPE or \
service_type == Constants.TRANSFORM_SCIKITLEARN_TYPE:
response_params = Constants.MICROSERVICE_URI_GET_PARAMS
return (
jsonify({
Constants.MESSAGE_RESULT:
f'{Constants.MICROSERVICE_URI_SWITCHER[service_type]}'
f'{filename}{response_params}'
}),
Constants.HTTP_STATUS_CODE_SUCCESS_CREATED,
)
