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This article will explain in detail what basic knowledge Python full stack engineers should master. The editor thinks it is very practical, so I share it with you as a reference. I hope you can get something after reading this article.

Before we talk about Python full stack engineers, we need to figure out the full stack first. So what is the whole stack? From the realization of the front-end page, to the writing of the background code, and then to the management of the database, one person can take care of all the things of a company's website and really achieve full-stack development. To put it simply, the full stack is just a concept and comes in many categories. The real full-stack engineer covers web development, DBA, crawler, testing, operation and maintenance, and there is a lot to learn. What you need to learn in terms of web development direction: the front-end knowledge includes HTML5, CSS3, JS, Jquery, Ajax, and the back-end at least needs to be proficient in using Django and tornado. Flask is certainly better.

The Python full stack engineer is a kind of popular talent, and the Python language itself has the ability of full-end development, so there are many full-stack engineers in Python. So python full stack generally refers to people who use python to automate operation and maintenance and web front and back end as well as some project development in linux/windows environment.

For Python full stack engineers, there are five knowledge structures that need to be mastered:

First, the basic grammar of Python language. The basic syntax of the Python language is not difficult to master, or even very simple. Because Python is a scripting language, the syntax is relatively straightforward.

Second, Python does Web development.

Python is one of the three traditional solutions developed by Web (including Java and PHP), and Web development is a must for full stack engineers. Web development with Python requires learning the corresponding framework, such as Django.

Third, Python does data analysis. Python data analysis is a common application scenario, Python data analysis needs to learn the corresponding algorithm and implementation process. Libraries to be used include Numpy, matplotlib, and so on.

4. Python is a crawler. Python crawler application is a very common application, there are a large number of cases to refer to.

5. Python for machine learning applications. At present, Python is widely used in the field of machine learning (related to artificial intelligence), so it is necessary for Python full-stack engineers to master the contents related to machine learning. The algorithms that need to be mastered include decision tree, naive Bayesian, regression, kNN classification, etc., as well as basic knowledge of linear algebra and probability theory.

This is the end of this article on "what basic knowledge Python full stack engineers need to master". I hope the above content can be of some help to you, so that you can learn more knowledge. if you think the article is good, please share it for more people to see.

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