search
HomeBackend DevelopmentPython TutorialWhich one should I learn first, linux or python?

Many Python newbies often ask whether they need to learn Linux to learn Python? Doesn’t Python support Windows and Linux operating systems? Why learn Linux when you can develop under Windows?

Which one should I learn first, linux or python?

Friends who ask this question may not have really started Python development or have not really participated in some of the company's project deployment and launch processes. For the above questions, the preferred answer is yes. Yes, Python development can be developed under Windows, but Linux learning is still necessary. (Recommended learning: Python video tutorial)

Online servers are generally

Generally in a production environment, servers are basically Linux. For example, CentOS, Red Hat, Ubuntu and other Linux systems, why are most servers using Linux? For example, one of them must be security. We have heard that Windows often crashes, and people who are invaded by ransomware viruses have to pay Bitcoin, but these do not happen often under Linux. There are many other reasons that can be found online, so the Python scripts in the production environment are It is deployed on the Linux system, but when developing, considering the convenience of operation, Windows or Mac not only have a graphical interface, but also have better performance, and the operation is easier and faster. After all, anyone who has used Ubuntu knows that, Installing a virtual machine still requires certain computer performance. If the computer configuration cannot keep up, it will be very laggy when using Ubuntu. Generally, server-level systems have a character-based interface, which is the legendary black screen. If you It is also possible to develop on a Linux server, but it is more troublesome and requires high coding level and operational proficiency.

Deployment

Online deployment often encounters the problem of debugging the code after deploying it to the server. Generally, during the debugging process, developers will frequently switch back and forth. Directory, search for files, use VI to modify the code, these regular operations are all necessary skills for a Python development engineer. VI also uses various Linux commands, which is convenient and direct, without having to transfer the code offline and modify it. After that, it is transmitted to the server. Hackers use commands directly under Linux because they want to attack and modify the code data of the other party's server. They must understand all operations under Linux, and for hackers, using commands is easier than using graphics. The interface is more efficient

Linux is more convenient

Linux is more convenient for developers. You have the highest authority in the Linux system. Various configurations inside, The tools are at your disposal, but under Windows, the modifications you can make to the system are relatively cumbersome. Using Linux, the modification of various configuration files only requires a few commands, and the installation of tools only requires a few commands. If you modify the configuration under Windows, you may need to look for the file everywhere, which is also a shortcoming of the graphical interface.

To summarize, the Python language can also be learned and developed under Windows, but it is more convenient under Linux. For example, if you want to use Python to develop a website (the popular and mature Python Web framework today), you need to use the Linux platform. After all, the Linux platform is more commonly used to build such a website; secondly, if you want to use a Python crawler to crawl data, It is also more convenient on the Linux system; also, if you want to learn network security penetration testing, it is also necessary to write Python automated test scripts on Linux.

For more Python related technical articles, please visit the Python Tutorial column to learn!

The above is the detailed content of Which one should I learn first, linux or python?. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

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 vs. C  : Memory Management and ControlPython vs. C : Memory Management and ControlApr 19, 2025 am 12:17 AM

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 for Scientific Computing: A Detailed LookPython for Scientific Computing: A Detailed LookApr 19, 2025 am 12:15 AM

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.

Python and C  : Finding the Right ToolPython and C : Finding the Right ToolApr 19, 2025 am 12:04 AM

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 for Data Science and Machine LearningPython for Data Science and Machine LearningApr 19, 2025 am 12:02 AM

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.

Learning Python: Is 2 Hours of Daily Study Sufficient?Learning Python: Is 2 Hours of Daily Study Sufficient?Apr 18, 2025 am 12:22 AM

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.

Python for Web Development: Key ApplicationsPython for Web Development: Key ApplicationsApr 18, 2025 am 12:20 AM

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 vs. C  : Exploring Performance and EfficiencyPython vs. C : Exploring Performance and EfficiencyApr 18, 2025 am 12:20 AM

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.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Tools

mPDF

mPDF

mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

VSCode Windows 64-bit Download

VSCode Windows 64-bit Download

A free and powerful IDE editor launched by Microsoft

EditPlus Chinese cracked version

EditPlus Chinese cracked version

Small size, syntax highlighting, does not support code prompt function

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use