4. Pickle the DAG and save it to the DB (if necessary).
        5. Mark any DAGs which are no longer present as inactive
        6. Record any errors importing the file into ORM
        :param file_path: the path to the Python file that should be executed
        :param callback_requests: failure callback to execute
        :param pickle_dags: whether serialize the DAGs found in the file and
            save them to the db
        :param session: Sqlalchemy ORM Session
        :return: number of dags found, count of import errors
        """
        self.log.info("Processing file %s for tasks to queue", file_path)
        try:
            dagbag = DagBag(file_path, include_examples=False)
        except Exception:
            self.log.exception("Failed at reloading the DAG file %s", file_path)
            Stats.incr("dag_file_refresh_error", 1, 1, tags={"file_path": file_path})
            return 0, 0
        if len(dagbag.dags) > 0:
            self.log.info("DAG(s) %s retrieved from %s", dagbag.dags.keys(), file_path)
        else:
            self.log.warning("No viable dags retrieved from %s", file_path)
            DagFileProcessor.update_import_errors(
                file_last_changed=dagbag.file_last_changed,
                import_errors=dagbag.import_errors,
                session=session,
            )
            if callback_requests: