How to Achieve Robust Logging in Python Multiprocessing Applications?

Logging with Multiprocessing in Python: A Robust Solution

When utilizing Python's multiprocessing module, logging becomes more intricate due to the lack of process-shared locks for the multiprocessing-aware logger, potentially leading to scrambled sys.stderr output.

To address this challenge, an alternative approach is to create a custom log handler that directs output to the parent process via a pipe. This method relies on a queue to handle concurrency and recover from errors. The implementation provided ensures stable logging in production environments.

The custom handler, MultiProcessingLog, extends the logging.Handler class and leverages a RotatingFileHandler to handle file-based logging. It establishes a pipe between the parent and child processes, allowing for a centralized log storage.

Implementation Details:

The MultiProcessingLog handler employs a separate thread to receive log records from child processes and forward them to the RotatingFileHandler in the parent process. This ensures that log messages are correctly formatted and written to the intended destination.

To send log records, the send method is utilized, while the receive thread continuously monitors the pipe for new records and forwards them to the _handler.

To minimize the risk of unpickleable objects causing issues, the handler stringifies exc_info and args values in the log record before sending it over the pipe.

The emit method is overridden to wrap the _format_record call in a try-except block to ensure that any failures are handled appropriately.

This custom logging handler provides a reliable solution for managing logs in multiprocessing applications, offering centralized log storage and error recovery capabilities.

The above is the detailed content of How to Achieve Robust Logging in Python Multiprocessing Applications?. For more information, please follow other related articles on the PHP Chinese website!