What is a python full stack engineer?

Even if you use Python related tools and knowledge to complete the implementation of the front-end page, to the writing of the back-end code, and then to the management of the database, one person can handle everything about a company website and truly realize full-stack development.

Full-stack is just a concept, and it can be divided into many categories. A true full-stack engineer covers web development, DBA, crawler, testing, operation and maintenance. What should you learn? It's quite a huge amount. What you need to learn in terms of web development: front-end knowledge including HTML5 CSS3 JS Jquery Ajax. The back-end needs to be at least proficient in using Django and tornado, and of course flask is better. (Recommended learning: Python video tutorial)

Python full-stack engineers are a relatively popular type of talent. The Python language itself has full-end development capabilities, so the full range of Python There are also many stack engineers.

For Python full-stack engineers, they need to master the following knowledge structure:

First, the basic syntax of the Python language. It is not difficult to master the basic syntax of the Python language. It can even be said to be very simple. Because Python is a scripting language, the syntax is relatively straightforward.

Second, Python is used for web development.

Python is one of the three traditional solutions for web development (also including Java and PHP). Web development is something that full-stack engineers must master. To do web development with Python, you need to learn the corresponding framework, such as Django.

Third, Python does data analysis. Data analysis in Python is a relatively common application scenario. To do data analysis in Python, you need to learn the corresponding algorithm and implementation process. Libraries that will be used include Numpy, matplotlib, etc.

Fourth, Python is used as a crawler. Python crawler application is a very common application, and there are a large number of cases for reference.

Fifth, Python is used for machine learning applications. Python is currently very commonly used in the field of machine learning (artificial intelligence related), so it is necessary for Python full-stack engineers to master machine learning-related content. Algorithms that need to be mastered include decision trees, naive Bayes, regression, kNN classification, etc. At the same time, basic knowledge of linear algebra and probability theory is required.

Of course Python also has its shortcomings, that is, it is slower, slower than C, C, and Java. This is a limitation because in many fields there are extreme requirements for the running speed of the language. For example, if you take the missile interception program, every second counts. Obviously python will be passed in the first step. But for other areas, such as the calculation of bridge parameters, I believe there is not much difference between 20 minutes and 18 minutes.

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