12 Python Logging Best Practices To Debug Apps Faster

Basics

Organizing and implementing logging for large Python projects involves following certain best practices to maintain readability and manageability. Here's a general process and some guidelines:

1. Choose a logging framework: Python's built-in logging module is commonly used, but you may also consider external libraries like loguru or structlog for more advanced features.
2. Set up logging configuration: Define the logging settings like log level, format, and handlers in a central configuration file. This allows you to change the logging behavior without modifying code.
3. Use named loggers: Assign specific loggers to different modules or components in your project. This helps to identify the source of log messages easily.
4. Define log levels appropriately: Use different log levels (e.g., DEBUG, INFO, WARNING, ERROR, CRITICAL) to differentiate the importance of log messages. This allows you to control the amount of logging output.
5. Logging to a file: Configure a rotating log file handler to prevent the log file from becoming too large. This ensures you can maintain logs without overwhelming the disk.
6. Avoid excessive logging: Be mindful of what information you log, and avoid flooding the log with unnecessary details. Logging too much can impact performance and readability.
7. Use structured logging: If possible, consider using structured logging formats like JSON or key-value pairs. This makes it easier to parse and analyze logs later.
8. Centralize log message formatting: Keep a consistent log message format throughout the project. This aids in understanding and parsing the logs effectively.
9. Use exception logging: Log exceptions and errors with stack traces to debug issues effectively.

Log Message Locations: Principles

• Log messages should be placed near the code that generates them, providing context and clarity.
• Use module-level loggers to ensure each module has its own logger instance, making it easier to manage logging levels and filter messages based on their origin.
• Avoid placing log messages directly in the main body of the script or functions. Instead, place them within logical blocks to capture important events or actions.
• Be cautious about placing logging in loops or other frequently executed sections, as it can create excessive logging output.

By following these guidelines, you can keep your logging organized and maintain a clear, concise, and helpful log output without making it a mess.