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This article mainly talks about "what are the problems related to python". Interested friends may wish to have a look. The method introduced in this paper is simple, fast and practical. Now let the editor take you to learn "what are the problems related to python"?

What is python?

Python is a cross-platform computer programming language. Is a high-level combination of interpretive, compiled, interactive and object-oriented scripting language. Originally designed for automated scripting (shell), as versions are constantly updated and new features of the language are added, the more they are used for independent, large-scale project development.

What can python be used for?

There are about four directions to consider.

1, web direction, because one of the stages of python learning is python full-stack development, mainly learning back-end framework + project combat, after 100 choose to be a web full-stack development engineer is also completely possible.

2, the direction of artificial intelligence, various algorithms of artificial intelligence are based on python, to put it bluntly, if you want to learn artificial intelligence but do not understand python, it is equivalent to want to learn English but do not know words, now AI is also the trend of the times.

3, the direction of data analysis, master the relevant concepts involved in data analysis, understand how to obtain data and feature engineering, and be familiar with the use of relevant modules, all these will be mastered in python learning, Tao and now the salary of data analysis engineers is particularly good, you can choose this direction if you want to work without tiring to earn money.

4, the direction of web crawler, a module in python learning is about web crawler learning, including the working principle and design idea of web crawler, weight anti-crawler mechanism, distributed crawler framework and so on. In the future, you can work as a web crawler engineer or data acquisition engineer.

Why is python so popular now?

1. Easy to learn

Python is an easy language to learn because it is a very advanced language, several levels higher than languages like C and C++, and can be learned even by a student fresh out of primary school. It does not need to manage memory allocation, does not need to define the type of variables to use, built-in many data types to use directly, without thinking about how to create these types, such as lists, dictionaries, strings and other advanced functions. In addition, the code written with it can be run directly without the need for compilation. In addition, the code written with it is very short, and the amount of typing can be much less.

two。 High development efficiency

Python is the most efficient language for development. It is 6 times more efficient than C #. To put it simply, if a C developer works for 6 days, a developer using Python only needs to work one day, which means that a Python developer can work only one day a week. It is twice as efficient as C++, and it is 1.5 times more efficient than Java and C#. There is such a high development efficiency, of course, is the price of performance, but from the current hardware technology progress, the current CPU computing power is generally excess, and more and more hardware costs are reduced, but labor costs are becoming more and more expensive. In fact, from the perspective of social progress, the tools are becoming more and more advanced, but the complexity of human brain management has not increased, so it is obviously more difficult to improve.

3. Easy to debug and run

Whether it is in the Windows platform or the Linux platform, it is the same development and debugging. Cross-platform operation is more convenient, if you do not use the platform-different API interface, just write the code, you can run on the Windows platform or Linux platform.

4. Open source and free

Python is free to use both commercially and educatively, meaning you can learn it and use it at zero cost. Python has many fully functional development libraries that can be used.

5. Testing domain requirements

Testing is that there is a considerable amount of work in software development, such as module testing. When developers complete the function of a module and need to test whether the module is correct, they need to build a pile of test code before it can be verified. At this point, if you use C++ or Java to write these features, it is obviously not as fast as using Python, as can be seen from the previous efficiency. As a result, it usually becomes a development model: the released software is developed using C++ or Java, but the tested code is developed using Python. For example, the embedded system involves network communication. If we need to send and receive network data to the embedded system constantly, we can use Python to build a test environment. In this way, we can verify the embedded system, improve the code quality, reduce the debugging time between the embedded system and other systems, and later maintenance time.

In addition, by using Python language to write a large number of scripts, we can improve the level of automated testing, each release of a version, you can test the previous test cases, fully automated, which will greatly improve the requirements for rapid software release. Like the test cases I have seen, there are tens of thousands of test cases, and if you test them manually, the verification is very slow and not comprehensive. At present, after the use of fully automated testing, running 24 hours a day, one computer is equivalent to the workload of 10 testing staff, which shows how much efficiency has been improved. In the testing field, the job requirements of Python will continue to increase in the foreseeable future, requiring all testers to master this useful tool.

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