Advanced guide to the Python Logging module: Customizing and optimizing logging

python Logging Module Advanced Guide

CustomLogLevel

Python The Logging module supports custom log levels, allowing developers to create specific levels as needed. To customize the log level, use the logging.addLevelName() function:

import logging

# 定义自定义日志等级
CUSTOM_LEVEL = 35

# 为自定义等级添加名称
logging.addLevelName(CUSTOM_LEVEL, "CUSTOM")

You can now use custom levels to log messages:

logging.log(CUSTOM_LEVEL, "自定义日志消息")

Create custom handler

Handlers are responsible for writing log messages to a file, console, or other destination. To create a custom handler, inherit from logging.Handler class:

class CustomHandler(logging.Handler):
def emit(self, record):
# 自定义日志记录逻辑
pass

Then add the custom handler to the logger:

logger = logging.getLogger()
logger.addHandler(CustomHandler())

Format log message

The formatter controls the layout of log messages. To create a custom formatter, inherit from logging.F<strong class="keylink">ORM</strong>atter Class:

class CustomFormatter(logging.Formatter):
def format(self, record):
# 自定义格式化逻辑
return formatted_message

Then attach the custom formatter to the handler:

handler = logging.FileHandler("log.txt")
formatter = CustomFormatter()
handler.setFormatter(formatter)

OptimizationLogging performance

To ensure that logging does not negatively impact application performance, consider the following optimization tips:

• Using asynchronous logging: Use logging.handlers.QueueHandler to move logging operations off the main thread.
• Minimize log message size: Use a custom formatter to include only necessary information.
• Optimize handlers: Use a high-speed handler (e.g. logging.handlers.RotatingFileHandler) or consider a third-party logging library (e.g. gunicorn.glogging) .
• Clean up log files regularly: Use the logging.FileHandler.maxBytes and logging.handlers.RotatingFileHandler.backupCount parameters to manage log file size.

Configuration Best Practices

To ensure the effectiveness of your logging configuration, follow these best practices:

• Set the logging level to the appropriate level: Use logging.DEBUG for detailed diagnostics, logging.INFO for general information, logging .ERROR Progress error.
• Using specificity filters: Use the logging.Filter class to filter log records from a specific source or with a specific message.
• Check log files regularly: Check log files regularly for errors or abnormalities.

in conclusion

By mastering advanced customization and optimization techniques, the Python Logging module can provide a comprehensive and efficient logging solution. By customizing log levels, creating custom handlers, formatting log messages, and optimizing logging performance, developers can meet the needs of their specific applications and ensure that logging provides valuable insights into their systems.

The above is the detailed content of Advanced guide to the Python Logging module: Customizing and optimizing logging. For more information, please follow other related articles on the PHP Chinese website!