How to write to a file, using the logging Python module?

Advanced configuration

Making the most out of handlers

To gain granular control over your log files, not only setting the severity level but also defining a custom log format, FileHandler comes to your rescue:

import logging

# Get a shiny new logger, name it as you please
logger = logging.getLogger('CodingNightmare')
logger.setLevel(logging.DEBUG)  # Capturing every tiny thing

# Handlers, aka your loyal log minions
file_handler = logging.FileHandler('coding_nightmare.log', 'a') # Append and NOT obliterate
file_handler.setLevel(logging.ERROR)  # We only care about errors here

# Define the format of your nightmares
log_format = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s', datefmt='%H:%M:%S')
file_handler.setFormatter(log_format)

# Add your minion to the logger
logger.addHandler(file_handler)

# Now, unleash the logs!
logger.error('Found a bug? Blame it on the intern.')
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Organize your logging practices

Learn how to coordinate multiple loggers and handlers to power-charge your logging implementation.

Guardrails and adjustments

Import JSON, not problems:

Leveraging a configuration file for maintaining your loggers, handlers, and formatters can neatly separate logging infrastructure from your business logic. This practice comes handy for complex applications:

import logging.config

logging.config.dictConfig('logging.json')
logger = logging.getLogger('MyLifeInCode')

logger.info('If life gives you problems, import solutions')
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Traps & Treatments

Make sure the log file's path is accessible and implement exception handling to prevent crashes or lost logs:

try:
    file_handler = logging.FileHandler('/path/to/your/monologues.log')
except (PermissionError, FileNotFoundError) as e:
    print(f'Error while logging: {e}')
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Clean exit

Lastly, reminder to implement logging.shutdown() to ensure all logs have reached their destiny and handlers are properly closed. It's especially crucial if your program interacts with shared resources or operates in a multiprocessing environment.