Shulou(Shulou.com)06/03 Report--

This article mainly explains "how to write a more stable Python code". The content of the article is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn how to write a more stable Python code.

The language of Python is so simple that anyone can write code in half an hour and dare to write their own proficiency in Python on their resume after a few months of code. Or some people think that Python equals pandas,Python equals AI.

At present, there are many courses on Python introduction, AI based on Python implementation, data analysis, and back-end courses. But there are not many courses on advanced Python, and not many on how to avoid Python potholes.

However, if you look at the Python code written by many people, you will find that the code is ugly. The second is to misuse all kinds of features and grammatical candy. I don't know where to learn a few advanced usage, so I use dazzling skills everywhere.

The code that many people write is just code that works and "currently" produces the right results. This code has no optimization to speak of, slow, unstable, do not know which day in the future suddenly can not be used.

Many people complain that Python is slow, that global interpreter locks limit the performance of code, or that Python is a dynamic language, and that variables can be assigned casually, making the project difficult to maintain.

But in fact, I would say, it's easy to write Python code that works, but getting Python right is another matter. Many people regard the characteristics of Python as Bug and their ignorance as language defects. Many people abuse the features of Python and blame Python itself for being too flexible to maintain.

Common problems

Let's look at a few examples. When I first joined NetEase, there was a senior engineer in the data warehouse who brought him an intern who said that Python has a global interpreter lock, so its multithreading is actually single-threaded and does not need to consider concurrency conflicts. This statement is a complete misunderstanding of global interpreter locks, and people who say so have no idea what global interpreter locks do.

There are also a lot of try in the code. Except, one layer at a time. In this way, its code will never report an error after it is run. It looks very stable. But often run for a period of time, the output is far from expected. And have no idea what went wrong.

Some students installed the first Python in their computers using Anaconda. Later, another Python environment will be installed for other reasons. Resulting in the original environment can not be used normally. When I opened the PyCharm, I found it was full of red wavy lines. Use pip to install a third-party library. Obviously, it has been successfully installed and can be imported normally in the command-line interactive environment, but it will report an error as soon as it is run in PyCharm, indicating that the third-party library is missing.

There are students, do not know what to do, resulting in the module of Python can not be imported normally, or after import, the lack of corresponding functions, a run will report an error.

Thank you for your reading, the above is the content of "how to write a more stable Python code". After the study of this article, I believe you have a deeper understanding of how to write a more stable Python code, and the specific use needs to be verified in practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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