To use Python's logging module effectively, configure the logger to set levels and formats. Use different log levels (DEBUG, INFO, WARNING, ERROR, CRITICAL) to categorize messages for better clarity.

Python's logging module is a powerful tool for tracking events that occur during program execution. To use it effectively, start by configuring the logging system early in your application. Set the logging level to determine the severity of messages you want to capture; common levels include DEBUG, INFO, WARNING, ERROR, and CRITICAL. For example, you can configure the logging level with logging.basicConfig(level=logging.INFO), which will capture INFO level messages and above. Additionally, format your log messages to include useful information, such as timestamps, log levels, and module names, by using the format parameter in the basicConfig() function. Use logging throughout your code to provide insights into execution flow and to catch issues as they arise. Rather than using print statements, which can be intrusive, logging allows for configurable output that can be directed to files or external systems. Finally, consider structuring your logging statements in a way that helps categorize and filter messages based on severity, making it easier to analyze logs during debugging or post-mortem analysis. By following these best practices, you can leverage Python's logging module to enhance your application's maintainability and observability.