What is the main use of python

Introduction to the five main applications of Python:

1. Web development

The birth history of Python is earlier than the Web , because Python is an interpreted scripting language with high development efficiency, 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.

2. Web crawler

Web crawler is a commonly used scenario in Python. Internationally, Google used Python language extensively in the early days as the basis of web crawler, which led to Application development of the entire Python language.

For example: crawl product discount information from major websites and compare to obtain the best choice; collect and classify speeches on social networks, generate emotional maps, and analyze language habits; crawl a certain type of songs from NetEase Cloud Music All comments are generated to generate a word cloud; there are so many applications that almost everyone can use crawlers to do some fun, interesting and useful things after learning crawlers.

3. Artificial Intelligence

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

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.

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