Whether it is a crawler that is done by entry-level players to professional players, or web program development, desktop program development, scientific computing, and image processing, Python is competent. Python provides us with a very complete basic code base, covering a large number of contents such as network, files, GUI, database, text, etc., and is vividly called "built-in batteries (Batteries included). Developed in Python, many functions do not have to be written from scratch, just use ready-made ones.
In addition to built-in libraries, Python also has a large number of third-party libraries, which are things developed by others for your direct use. Of course, if the code you develop is well encapsulated, it can also be used as a third-party library for others to use.
1. WEB development
Python has many free data function libraries, free web page template systems, and libraries for interacting with web servers, which can realize web development and build web frameworks. In this field, you should learn from multiple fields such as data, components, and security, understand its working principles from the bottom and be able to master any mainstream web framework in the industry. Python has many web frameworks, among which Django and Flask are the most famous. Django is a complete web framework that includes powerful backend management functions, ORM, template systems, etc., suitable for large-scale web application development. Flask is a miniature web framework with relatively simple functions and is suitable for the development of small applications or simple APIs.
2. Network programming
Provides rich modules to support sockets programming, which can facilitate and quickly develop distributed applications. Many large-scale software development programs such as Zope, Mnet and BitTorrent. Google uses it widely.
Network programming is another direction of Python learning. Network programming is everywhere in life and development. Wherever there is communication, there is a network. It can be called the "cornerstone" of all development. All programming developers must know the truth and why, so the network part will conduct in-depth analysis from the bottom layers of protocols, packets, unpacking, etc.
3. Crawler Development
Web crawlers, also known as web spiders, refer to script programs that crawl the required content on the network according to certain rules. As we all know, each web page usually contains the entrance to other web pages, and web crawlers enter other web addresses in turn to obtain the required content. Python is an indispensable part of the crawler field. All network data is used as resources and targeted data collection and processing are carried out through automated programs.
In the field of crawling, Python is almost dominant, using all network data as resources and targeted data collection and processing through automated programs. In this field, you should learn crawling strategies, high-performance asynchronous IO, distributed crawlers, etc., and conduct in-depth analysis of the source code of the Scrapy framework, so as to understand its principles and implement a custom crawler framework.
4. Automated operation and maintenance
Python is a comprehensive language that can meet most automation operation and maintenance needs. Both the front-end and the back-end can be done. If you work in this field, you should learn from the design level, framework selection, flexibility, scalability, troubleshooting, and how to optimize.
In many operating systems, Python is a standard system component. Most Linux distributions, as well as NetBSD, OpenBSD, and Mac OS X, integrate Python and can run Python directly in the terminal. There are some Linux distribution installers written in Python, such as Ubuntu's Ubiquity installer, Red Hat Linux, and Fedora's Anaconda installer. Gentoo Linux uses Python to write its Portage (package management system). The Python standard library contains multiple libraries that call operating system functions. Through the third-party software package pywin32, Python can access Windows' COM services and other Windows APIs. Using IronPython, Python can directly call the .Net Framework. Generally speaking, system management scripts written in Python are better than ordinary shell scripts in terms of readability, performance, code reuse and scalability.
5. Data Science
Data science, including machine learning, data analytics and data visualization. Use Python for machine learning: it can study artificial intelligence, robots, language recognition, image recognition, natural language processing and expert systems, etc.; use Python for data analysis/visualization: big data analysis, etc.
Python is widely used in the field of artificial intelligence. Due to its easy-to-use features, many newbies can easily start learning artificial intelligence. Python's machine learning libraries include scikit-learn, TensorFlow, PyTorch, etc. Among them, TensorFlow and PyTorch are the most popular deep learning frameworks. MASA and Google used Python extensively in the early days, accumulating a rich scientific computing library for Python. When the AI era came, Python stood out from many programming languages. Various artificial intelligence algorithms were written based on Python, especially after PyTorch, Python's position as the top language in the AI era was basically determined.
in conclusion
Python is a simple, easy to learn and promising programming language. Many people are interested in Python, but after learning the basic usage of Python, they will become confused, especially those who study by themselves, who don’t know the next direction of Python learning and what they can do after learning? Python has outstanding performance in all fields. With its powerful functions and simplicity and easy-to-learn characteristics, it has become one of the all-round programming languages.