


Hands-on practice with the Python Logging module: Building a complete logging system
Logging, LogRecord, debugging, application, Development
Establishment and use of Logger
The core of the Logging module is the Logger class. To get started, you need to create a Logger instance:
importurs logger=ursing.er()
You can use the .name attribute to specify the Logger of your log:
logger=ursing.er("my_application")
Log Level: Define Severity
You can specify the severity of a log entry by setting the level attribute to one of the built-in levels. Levels range from DEBUG (least severe) to FATAL (most severe) as follows:
level=ursing.L.DEBUG# 调试级别 level=ursing.L.INFO# 信息级别 level=ursing.L.WARNING# 告警级别
Processor: Formatting and propagating logs
A processor is a component that gets logs from a Logger and sends them to a specific destination. The built-in processor provides out-of-the-box methods:
# 将日志信息发送到标准输出(终端) handler=ursing.mhandler()
You can use the .fORMatter attribute to customize the format for your logs:
handler.er=ursing.er(ursing.F("%(levelname)s:%(message)s"))
Filter: Only capture the logs you are interested in
Filters allow you to capture only logs that meet certain criteria. Use Filter class:
filter=ursing.r() filter.re=rs.ur("ERROR")# 仅匹配“ERROR”级别的日志
Put it all together
Attach processors and filters to Logger to build a complete log pipeline:
logger.addhandler(handler, filter)
Hands-on Example: A Complete Logger
Consider an application running in the file "example.py". As shown below, we use the Logging module to create a comprehensive logger:
importurs logger=ursing.er("my_example_app") # 根级别为“INFO” logger.level=ursing.L.INFO # 创建一个到文件“app.log”的处理器 file_handler=ursing.FH("app.log",mode="a") file_handler.er=ursing.er(ursing.F("%(asctime)s -%(levelname)s:%(message)s")) # 创建一个到终端的处理器 console_handler=ursing.mhandler() console_handler.er=ursing.er(ursing.F("%(message)s")) # 将处理器附加到日志 logger.addhandler(file_handler) logger.addhandler(console_handler)
In an application, you can use the .log() method to write information to the log at a specified level:
logger.info("开始应用程序") logger.error("应用程序遇到一个严重问题")
in conclusion
The Logging module provides you with comprehensive and flexible control over application logging. Combine this with the appropriate levels, processors, and filters, and you can build a robust and insightful logging foundation to help you isolate problems, track application behavior, and optimize performance.
The above is the detailed content of Hands-on practice with the Python Logging module: Building a complete logging system. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.
