Logging Best Practices for Multiple Processes

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Time to talk about logging best practices for multiple processes in Python. Because who doesn’t love a good ol’ log file that looks like a ransom note from a serial killer?

But seriously, Time to get going with some tips and tricks for handling logs when you have more than one process running at the same time.

To start: use a logging library! There are plenty of options out there (like `logging`, `loguru`, or `rich`), but we’re going to stick with good ol’ `logging`. It’s built-in, it’s reliable, and it’s easy to configure.

Now that you have your logging library set up, how to handle logs for multiple processes. The key is to use a separate logger for each process (or thread) so that they don’t interfere with each other. This can be done by creating a new logger object and passing it as an argument when you start your process or thread:

# Import necessary libraries
import logging
from multiprocessing import Process

# Define a function for the child process
def my_process(logger):
    # do some stuff here...
    logger.debug("This is a debug message from the child process")

# Check if the script is being run directly
if __name__ == '__main__':
    # Create a new logger object with the name of the current module
    logger = logging.getLogger(__name__)
    # Set the logging level to DEBUG
    logger.setLevel(logging.DEBUG)
    # Define a formatter for the log messages
    formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')

    # Create a file handler to save the logs to a file
    file_handler = logging.FileHandler("mylogfile.txt")
    # Set the logging level for the file handler to DEBUG
    file_handler.setLevel(logging.DEBUG)
    # Set the formatter for the file handler
    file_handler.setFormatter(formatter)

    # Create a console handler to print the logs to the console
    console_handler = logging.StreamHandler()
    # Set the logging level for the console handler to INFO
    console_handler.setLevel(logging.INFO)
    # Set the formatter for the console handler
    console_handler.setFormatter(formatter)

    # Add the file handler and console handler to the logger
    logger.addHandler(file_handler)
    logger.addHandler(console_handler)

    # Create a new process, passing in the logger as an argument
    p1 = Process(target=my_process, args=(logger,))
    # Start the process
    p1.start()

In this example, we’re creating a new `Process` object and passing the logger as an argument to the target function (`my_process`) so that it can use its own logger instead of sharing with the main process. This ensures that each process has its own log file and doesn’t interfere with other processes.

Another important tip is to make sure your logs are formatted consistently across all processes. You don’t want one process logging in a different format than another, as this can cause confusion when you try to read the logs later on. To ensure consistency, use a consistent logger configuration for each process (as shown above).

Finally, be careful with your log messages! Make sure they are clear and concise so that other team members or future versions of yourself can easily understand what’s going on. Avoid using overly technical language or jargon, as this can make it harder to read the logs later on. And always include relevant context in your log messages (like the name of the function being executed) so that you know exactly where the message came from.

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