search
HomeBackend DevelopmentPython TutorialWhy is python web not popular?

Why is python web not popular?

PHP is almost useless at the language level, and the quality of the specific implementation is mediocre, but it wins in the most critical deployment: no other language is as suitable for large-scale as PHP How to deploy. Basically after installing Apache/mod_php, deploying PHP applications is as simple as copying files.

Even if alternatives such as nginx/FastCGI are used for performance reasons, the extra work is only in the initial configuration. Once the configuration is complete, subsequent deployments are all about file copying. After the server is restarted, apache/nginx will usually be automatically started. The fastcgi manager is responsible for starting the php-cgi process, etc. The file-based calling method of PHP applications does not require more maintenance.

This is critical for web hosting platforms such as Dreamhost: they typically have a single server to handle thousands of low-traffic users, and these users do not have root privileges to run other processes.

Related recommendations: "Python Video Tutorial"

The life cycle of PHP scripts is very short, there is no resident process, and it is terminated after each call. For application authors The requirements are lower and there is no need to consider too much resource management issues.

This is very different from the deployment of Python and the like: most Python network applications such as Django, Tornado, etc. require a separate resident process (Apache/mod_python seems to be a failure and has long been discontinued. updated).

These processes require additional maintenance work to manage their start and stop, and additional monitoring processes are required to handle restarts after unexpected exits. This requires users to have a deeper understanding of the system.

The resident process needs to occupy system memory, and it is usually impossible to run hundreds or thousands of applications on one server. For service providers like Dreamhost, it is not suitable for handling tasks such as WordPress blogs. Simple application. Resident processes also require the author to have a deeper understanding of system resource management, garbage collection mechanisms, etc. to avoid problems such as memory leaks and excessive resource usage.

Now the simplest Python network application deployment should be App Engine, which adopts a life cycle similar to PHP (request processing is limited to 30 seconds, the timeout is terminated, and the resident process cannot run), which greatly simplifies the difficulty of management. , but it is not accessible in China...

So in terms of popularity, Python will not surpass PHP because a large number of service providers cannot use Python to support the existing user scale. But this popularity means little to startups and professionals. Many core network applications are not suitable for implementation using PHP's short-lived request processing mechanism (such as quasi-real-time push reminders, web page instant chat, etc.), but are more suitable for processing by resident processes. These are where language implementations such as Python and Ruby exert their power.

The power of Python lies in the simplicity and elegance of the language, as well as its powerful expression ability. Hackers like to use Python as a way to express their thinking.

In web development, Python deployment is a problem, but for commercial websites, it is not a problem to handle a VPS by yourself. The versatility of Python ensures the completion of various unconventional applications.

Simply put, if you just need a Web1.0 content display website, consider PHP. For Web2.0, you can consider Python and RoR.

The above is the detailed content of Why is python web not popular?. 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  : Understanding the Key DifferencesPython vs. C : Understanding the Key DifferencesApr 21, 2025 am 12:18 AM

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Python vs. C  : Which Language to Choose for Your Project?Python vs. C : Which Language to Choose for Your Project?Apr 21, 2025 am 12:17 AM

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

Reaching Your Python Goals: The Power of 2 Hours DailyReaching Your Python Goals: The Power of 2 Hours DailyApr 20, 2025 am 12:21 AM

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Maximizing 2 Hours: Effective Python Learning StrategiesMaximizing 2 Hours: Effective Python Learning StrategiesApr 20, 2025 am 12:20 AM

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Choosing Between Python and C  : The Right Language for YouChoosing Between Python and C : The Right Language for YouApr 20, 2025 am 12:20 AM

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python vs. C  : A Comparative Analysis of Programming LanguagesPython vs. C : A Comparative Analysis of Programming LanguagesApr 20, 2025 am 12:14 AM

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

2 Hours a Day: The Potential of Python Learning2 Hours a Day: The Potential of Python LearningApr 20, 2025 am 12:14 AM

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

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.

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

Video Face Swap

Video Face Swap

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

Hot Tools

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.

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

PhpStorm Mac version

PhpStorm Mac version

The latest (2018.2.1) professional PHP integrated development tool

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools