airflow/utils/dag_processing.py
def start(self):
        """
        Use multiple processes to parse and generate tasks for the
        DAGs in parallel. By processing them in separate processes,
        we can get parallelism and isolation from potentially harmful
        user code.
        """

        self.log.info("Processing files using up to %s processes at a time ", self._parallelism)
        self.log.info("Process each file at most once every %s seconds", self._file_process_interval)
        self.log.info(
            "Checking for new files in %s every %s seconds", self._dag_directory, self.dag_dir_list_interval
        )

        if self._async_mode:
            self.log.debug("Starting DagFileProcessorManager in async mode")
            self.start_in_async()
        else:
            self.log.debug("Starting DagFileProcessorManager in sync mode")
            self.start_in_sync()
def start(self):
        """
        Use multiple processes to parse and generate tasks for the
        DAGs in parallel. By processing them in separate processes,
        we can get parallelism and isolation from potentially harmful
        user code.
        """

        self.log.info("Processing files using up to %s processes at a time ", self._parallelism)
        self.log.info("Process each file at most once every %s seconds", self._file_process_interval)
        self.log.info(
            "Checking for new files in %s every %s seconds", self._dag_directory, self.dag_dir_list_interval
        )

        if self._async_mode:
            self.log.debug("Starting DagFileProcessorManager in async mode")
            self.start_in_async()
        else:
            self.log.debug("Starting DagFileProcessorManager in sync mode")
            self.start_in_sync()
Use multiple processes to parse and generate tasks for the
        DAGs in parallel. By processing them in separate processes,
        we can get parallelism and isolation from potentially harmful
        user code.