Python uses logging to record logs

Logging is a crucial aspect of Python application development. It helps us track application runtime status, debug problems, and analyze performance bottlenecks. Python’s standard library provides a module called `logging` that makes implementing logging functionality easy.

1. Import the logging module

First, we need to import the logging module:

import logging

2. Configure logging

Before using logging, we need to configure it. The most basic configuration includes setting the log level, log format, and log output location. For example, we can configure logging like this:

logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s', filename='app.log')

The code above sets the log level to DEBUG, the log format includes time, log level and log information, and outputs the log to a file named app.log.

3. Record logs

After configuring logging, we can start recording logs. Logging provides various methods for recording different levels of logs, such as debug(), info(), warning(), error(), and critical(). For example:

logging.debug('This is a debug message')
logging.info('This is an info message')
logging.warning('This is a warning message')
logging.error('This is an error message')
logging.critical('This is a critical message')

The code above records different levels of log information. In practical applications, we can choose the appropriate method to record logs as needed.

4. Summary

By following the steps above, we can easily use the logging module to record logs in Python applications. Of course, logging also provides many other advanced features, such as log filtering and log processors, which can be explored and used in greater depth according to specific needs.