Many programs have the need to record logs, and the information contained in the logs includes normal program access logs, and may also include errors, warnings and other information output. Python's logging module provides a standard log interface through which you can store Various formats of logs. The recorded logs can be divided into 5 levels: debug, info, warning, error, and critical. Let’s take a look at how to use it.
First introduction to the module:
#logging初识 import logging logging.warning("user [James] attempted wrong password more than 3 times") logging.critical("server is down") # WARNING:root:user [James] attempted wrong password more than 3 times # CRITICAL:root:server is down
The above code is the simplest way, brackets The content inside is the printed information, and the method after logging. is the log level. Let’s take a look at the detailed information of the five levels of logging. If you want to write the log to a file, it is also very simple:
#日志打印到文件中 import logging logging.basicConfig(filename="example.log",level=logging.INFO, format="%(asctime)s %(message)s", datefmt="%m/%d/%Y %H:%M:%S [%A]") # H 24小时格式 I 12小时格式 A 周几完整 a 周几简写 p AM/PM logging.debug("This message should go to the log file") logging.info("So should this") logging.warning("And this ,too")
logging .basicConfig defines the input file path, input log information level, input format, and the format can be customized; after executing the code, the example.log file will generate the following information:
10/31/2016 17:16:17 [Monday] So should this 10/31/2016 17:16:17 [Monday] And this ,tooAmong them, level=loggin in the following sentence. INFO means to set the logging level to INFO, that is to say, only logs with INFO or higher level than INFO will be recorded to the file. In this example, the first log will not be recorded. Yes, if you want to record debug logs, just change the log level to DEBUG. If you want to print the log on the screen and in the file log at the same time, you need to know some complicated knowledge: The logging library takes a modular approach and offers several categories of components: loggers, handlers, filters, and formatters.Loggers expose the interface that application code directly uses.Handlers send the log records (created by loggers) to the appropriate destination. Filters provide a finer grained facility for determining which log records to output.Formatters specify the layout of log records in the final output.
#!/usr/bin/env python # -*- coding:utf-8 -*- #-Author-Lian import logging #创建logger logger = logging.getLogger("test_log") #创建logger对象 括号内容随便写 logger.setLevel(logging.INFO) #全局日志级别 ch = logging.StreamHandler() #日志打印到屏幕上 ch.setLevel(logging.DEBUG) #指定ch日志打印级别 fh = logging.FileHandler("access.log") #日志存进文件 fh.setLevel(logging.WARNING) #指定fh日志输入级别 formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s") #定义日志格式,可写多个 #添加日志格式到ch,fh ch.setFormatter(formatter) fh.setFormatter(formatter) #添加ch,fh到logger中 logger.addHandler(ch) logger.addHandler(fh) logger.debug('debug message') logger.info('info message') logger.warn('warn message') logger.error('error message') logger.critical('critical message')The global log level is the bottom line of the entire program. If you want to print, the local log level cannot be higher than this The level couldn’t be lower Screen printing information
2016-10-31 17:23:42,988 - test_log - INFO - info message 2016-10-31 17:23:42,988 - test_log - WARNING - warn message 2016-10-31 17:23:42,988 - test_log - ERROR - error message 2016-10-31 17:23:42,988 - test_log - CRITICAL - critical messageaccess.log:
2016-10-31 17:02:06,223 - test_log - WARNING - warn message 2016-10-31 17:02:06,224 - test_log - ERROR - error message 2016-10-31 17:02:06,224 - test_log - CRITICAL - critical messageAll log formats:
Several important formats: %(lineno)d Output print log code line, %(process) d outputs the process ID of the printing log, %(thread)d outputs the thread ID of the printing log

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.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

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.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

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.


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

SublimeText3 English version
Recommended: Win version, supports code prompts!

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft

SAP NetWeaver Server Adapter for Eclipse
Integrate Eclipse with SAP NetWeaver application server.

SublimeText3 Linux new version
SublimeText3 Linux latest version

Dreamweaver CS6
Visual web development tools