Python Logging Snippet

Python Logging Snippet

This snippet sets up a logger that writes log messages to both the console and a file, with different log levels to capture various types of information.

import logging
import os

# Create a directory for logs if it doesn't exist
if not os.path.exists('logs'):
    os.makedirs('logs')

# Configure the logger
logging.basicConfig(
    level=logging.DEBUG,  # Set the logging level
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler('logs/app.log'),  # Log to a file
        logging.StreamHandler()               # Log to the console
    ]
)

# Get the logger instance
logger = logging.getLogger('MyAppLogger')

# Example usage of the logger
def divide_numbers(x, y):
    try:
        logger.debug(f"Attempting to divide {x} by {y}")
        result = x / y
        logger.info(f"Division successful: {result}")
        return result
    except ZeroDivisionError as e:
        logger.error("Division by zero error", exc_info=True)
    except Exception as e:
        logger.exception("An unexpected error occurred")

# Demonstrate logging in action
if __name__ == "__main__":
    divide_numbers(10, 2)  # Normal operation
    divide_numbers(10, 0)  # Division by zero

Explanation

• Log Levels: The logger is configured with different log levels:

- DEBUG: Detailed information, typically of interest only when diagnosing problems.

- INFO: Confirmation that things are working as expected.

- ERROR: A more serious problem, which prevented the program from completing a function.

- EXCEPTION: Similar to ERROR, but logs exception information.

• Logging Handlers: The logging module is configured to handle logging in two ways:

- FileHandler: Writes logs to a file (logs/app.log), useful for long-term storage and analysis.

- StreamHandler: Outputs logs to the console, providing immediate feedback.

• Logging Format: The format for log messages includes the timestamp, logger name, log level, and message.

• Error Handling: The code demonstrates how to log exceptions with stack traces using exc_info=True or the exception() method.

Usage

• Add Logging to Your Application: Use this snippet to quickly integrate logging into any Python application.

• Monitor Application Behavior: By capturing logs, you can gain insights into application behavior, identify issues, and understand the flow of operations.

• Debugging: Use DEBUG and INFO logs to follow the logic and data flow through your application.

• Auditing: Keep track of important operations, errors, and exceptions for auditing purposes.

Logging is a fundamental aspect of software development, helping developers understand and maintain complex systems effectively. This snippet provides a robust starting point for adding logging capabilities to your applications.