What are the uses of python?

Python uses include: Web development, web crawlers, artificial intelligence, data analysis, automated operation and maintenance, system programming, graphics processing, mathematical processing, text processing, database programming, network programming, multimedia applications (such as game development )wait.

#Why do so many people learn Python? Many beginners have heard that Python is very popular, but why should they learn Python? Let’s talk about my insights.

Python language is the most enjoyable language I have used so far, because it is really beautiful. Although c, c, and java are also very powerful and great, but behind the greatness of each language They all have a certain historical background.

In the PC era, a large number of embedded devices, underlying codes, and desktop applications are all implemented in C and C. There is no doubt that they are closest to the underlying layer and the fastest.

With the large-scale rise of e-commerce around 2000, and gradually transitioning from the PC era to the Internet era, Java began to return as the king. In addition, with the explosion of mobile Internet in 2010 android began to become popular, Java became even more popular. .

Let’s talk about what python can do? What are the uses of python?

Uses of python

1. Web development

The birth history of Python is older than the Web Be early, because Python is an interpreted scripting language with high development efficiency, so it is very suitable for web development.

Python has hundreds of web development frameworks and many mature template technologies. Choosing Python to develop web applications not only has high development efficiency, but also runs quickly.

Commonly used web development frameworks include: Django, Flask, Tornado, etc.

Many well-known Internet companies use python as their main development language: Douban, Zhihu, Guoke.com, Google, NASA, YouTube, Facebook...

Due to the versatility of the backend server, in addition to In addition to narrowly defined websites, the server sides of many apps and games are also implemented in Python.

2. Web crawler

Many people’s enthusiasm for programming started out of curiosity and finally stagnated.

There is a technical gap between real-life development and no one to guide me. I don’t know what I can do at my current level? In this cycle of doubts, programming skills have stalled, and crawlers are one of the best ways to advance.

Web crawlers are a commonly used scenario in Python. Internationally, Google used the Python language extensively in the early days as the basis for web crawlers, which promoted the application development of the entire Python language. In the past, many people in China used collectors to search for online content. Now it is much easier to use Python to collect online information than before, such as:

crawl product discount information from major websites and compare to get the best choice;

Collect and classify speeches on social networks, generate emotional maps, and analyze language habits;

Crawl all comments on a certain type of songs from NetEase Cloud Music and generate word clouds;

Filter by conditions to obtain Douban's movie and book information and generate a table...

There are so many applications. Almost everyone can use crawlers to do some fun, interesting and useful things after learning crawlers.

3. Artificial intelligence

Artificial intelligence is a very hot direction now. The AI ​​boom makes the future of Python language full of unlimited potential. Most of the several very influential AI frameworks released now are implemented in Python. Why?

Because Python has many libraries that are very convenient for artificial intelligence, such as numpy and scipy for numerical calculations, sklearn for machine learning, pybrain for neural networks, and matplotlib for data visualization. In the broad field of artificial intelligence, data mining, machine learning, neural networks, deep learning, etc. are all mainstream programming languages ​​and have been widely supported and applied.

Most of the core algorithms of artificial intelligence still rely on C/C, because they are computationally intensive and require very fine optimization. They also require interfaces such as GPU and dedicated hardware, which only have C/C. can do it.

Python is the API binding of these libraries. Python is used because of the glue language characteristics of CPython. To develop a cross-language interface from other languages ​​to C/C, Python is the easiest and has higher thresholds than other languages. It's much lower, especially when using Cython.

4. Data analysis

In terms of data analysis and processing, Python has a very complete ecological environment. For distributed computing, data visualization, database operations, etc. involved in "big data" analysis, Python has mature modules that you can choose to complete its functions. For both Hadoop-MapReduce and Spark, you can directly use Python to complete computing logic, which is very convenient for both data scientists and data engineers.

5. Automated operation and maintenance

Python is also very important for server operation and maintenance. Since almost all Linux distributions currently come with a Python interpreter, using Python scripts for batch file deployment and operation adjustments has become a very good choice on Linux servers. Python also contains many convenient tools, from paramiko for controlling ssh/sftp, to supervisor for monitoring services, to build tools such as bazel, and even package management tools for C such as conan, Python provides a full range of tools Collection, and on this basis, combined with the Web, it will become very simple to develop tools that facilitate operation and maintenance.

6. Examples of other applications of Python

System programming: Provides API to facilitate system maintenance and management. It is one of the iconic languages ​​​​under Linux and is used by many systems The ideal programming tool for administrators.

Graphics processing: It is supported by graphics libraries such as PIL and Tkinter, which can facilitate graphics processing.

Mathematical processing: NumPy extensions provide a large number of interfaces to many standard mathematics libraries.

Text processing: The re module provided by Python can support regular expressions, and also provides SGML and XML analysis modules. Many programmers use Python to develop XML programs.

Database programming: Programmers can communicate with Microsoft SQL Server, Oracle, Sybase, DB2, MySQL, SQLite and other databases through modules that follow the PythonDB-API (Database Application Programming Interface) specification. Python comes with a Gadfly module, which provides a complete SQL environment.

Network programming: Provides rich modules to support socket programming, which can easily and quickly develop distributed applications. It is widely used by many large-scale software development projects such as Zope, Mnet and BitTorrent. Google.

Web programming: Application development language that supports the latest XML technology.

Multimedia application: Python's PyOpenGL module encapsulates the "OpenGL application programming interface" and can perform two-dimensional and three-dimensional image processing. The PyGame module can be used to write game software.

Hacker programming: Python has a hack library, which has built-in functions that you are familiar with or unfamiliar with, but it lacks a sense of accomplishment.

Recommended learning: Python video tutorial

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