def _generate_ingestion_message()

in collection_manager/collection_manager/services/CollectionProcessor.py [0:0]

• 16 lines of code
• 2 McCabe index (conditional complexity)

    def _generate_ingestion_message(granule_path: str, collection: Collection) -> str:

        config_dict = {
            'granule': {
                'resource': granule_path
            },
            'slicer': {
                'name': 'sliceFileByStepSize',
                'dimension_step_sizes': dict(collection.slices)
            },
            'processors': CollectionProcessor._get_default_processors(collection)
        }

        if collection.preprocess is not None:
            config_dict['preprocess'] = json.loads(collection.preprocess)

        config_str = yaml.dump(config_dict)
        logger.debug(f"Templated dataset config:\n{config_str}")
        return config_str