What is python mainly engaged in?

Python is mainly engaged in the following tasks: 1. Web development; 2. Web crawlers; 3. Data analysis; 4. AI artificial intelligence and machine learning; 5. Game development; 6. System operation and maintenance direction, etc. .

Many beginners may ask, what can they be used for after learning Python? Generally, they will think of crawlers first.

I don’t mean crawlers. That kind of bug, crawlers are actually similar to Baidu spiders and Google spiders. They will automatically crawl the content on the web page.

Of course, learning Python can make your development a lot easier:

1. You can do web application development. In China, Douban has used Python as the basic language for web development from the beginning. Zhihu’s entire architecture is also based on the Python language, which makes web development develop very well in China. YouTube, the world's largest video website, is also developed in Python. The very famous Instagram is also developed in Python

2. Web crawlers, crawlers are mostly operated. For example, Google's crawler was written in Python in the early days. There is a library called Requests. This library is a library that simulates HTTP requests. It is very famous! Anyone who has learned Python doesn't know this library. ,Data analysis and calculation after crawling are the areas that Python is best at, and it is very easy to integrate. However, the most popular web crawler framework in Python is the very powerful scrapy.

3. Data analysis. Generally, after we use a crawler to crawl a large amount of data, we need to process the data for analysis, otherwise the crawler will crawl in vain. Our ultimate goal is Analyze data. In this regard, the libraries for data analysis are also very rich, and various graphical analysis charts can be made. It is also very convenient. Visualization libraries such as Seaborn can plot data using only one or two lines, while using Pandas, numpy, and scipy can simply perform calculations such as screening and regression on large amounts of data. In subsequent complex calculations, it is very simple to connect machine learning-related algorithms, provide a Web access interface, or implement a remote calling interface.

4. AI artificial intelligence and machine learning. Artificial intelligence is very popular now. Various training courses are advertising and recruiting students like crazy. Machine learning is especially popular now. For deep learning, most of its tool frameworks provide Python interfaces. Python has always had a good reputation in the field of scientific computing. Its concise and clear syntax and rich computing tools are deeply loved by developers in this field. To put it bluntly, it is because Python is easy to learn and has rich frameworks. Many frameworks are very friendly to Python, and this is why I learn so many Python!

#The above are the directions related to Python, you can choose what you are interested in to learn!

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