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

This article mainly introduces "what are the shortcomings of Python". In daily operation, I believe that many people have doubts about the shortcomings of Python. The editor consulted all kinds of materials and sorted out simple and easy-to-use methods of operation. I hope it will be helpful for you to answer the doubts about "what are the shortcomings of Python?" Next, please follow the editor to study!

What makes Python so popular?

The main reason for the rapid development of Python is that it is easy to learn and powerful. This makes it very attractive to beginners, including those who are deterred by the difficult and unfamiliar grammar of languages such as C and C++.

The language fundamentally widely emphasizes the readability of the code. With its concise and expressive syntax, it allows developers to express ideas and concepts without writing a lot of code (for example, in low-level languages such as C or Java). Python is very simple and can be seamlessly integrated with other programming languages (such as offloading CPU-intensive tasks to C / C + +), which is an addition for multilingual developers.

Another reason for the wide range of uses of Python is the heavy use of it by large enterprises (including FAANG) and countless small businesses. Today, the Python package contains almost anything imaginable-- Numpy for scientific computing, Sklearn for machine learning, and Caer for computer vision.

Python also has its shortcomings.

It runs very slowly, very slowly.

It is clear that speed will be one of the main concerns of developers for a long time to come.

There are actually two reasons why Python is "slow"-Python is interpreted as the opposite of compilation, resulting in slower execution, and it is dynamically typed (Python automatically infers the data type of the variable during execution).

In fact, the saying that "Python is slow" has a great impact on beginners. This is true, but only part of the truth. Take the TensorFlow machine learning library available in Python as an example. These libraries are actually written in C++ and can be used in Python, which to some extent constitute the Python "decorator" around C++ implementation. The same is true of Numpy, and even Caer, to some extent.

It has a GIL (I)

One of the main reasons for the slow speed of Python is the existence of GIL (global interpreter lock), which can only execute one thread at a time. While this can improve single-threaded performance, it limits parallelism, and developers must implement multiprocessors rather than multithreaded programs to improve speed.

Not the optimal solution for memory-intensive tasks

Python automatically garbage collects objects when they are out of scope. It aims to eliminate many of the complex issues involved in memory management between C and C++. Due to the flexibility (or lack of flexibility) of specified data types, the amount of memory consumed by Python can explode rapidly. In addition, the runtime may pop up errors that Python doesn't pay attention to, eventually slowing down the development process.

Weak existence in Mobile Computing

With the huge shift from desktops to smartphones, it is clear that we need more powerful languages to build mobile software. Although Python is highly representative on desktop and server platforms, Python often fails in mobile development due to the lack of powerful mobile computing capabilities.

Much progress has been made in this area in recent years, but these newly added libraries still lag behind powerful competitors such as Kotlin,Swift and Java.

The rise of other languages

Recently, newer languages such as Julia,Rust and Swift have entered the game strongly. They draw on many excellent design concepts from Python,C/C + + and Java-Rust basically ensures memory security and parallelism at run time, and provides best-in-class interoperability with WebAssembly; Swift is almost as fast as C because it supports the LLVM compiler toolchain; and Julia provides asynchronous Icando O for Imax O-intensive tasks, and is very fast.

Python has always been a good programming language, and it has never surpassed Chand Clearing + and Java. It is a universal programming language that emphasizes human-readable, English-centric grammar and allows rapid development of programs and applications.

In the final analysis, Python, like other languages, is a tool. Sometimes, it is a good tool. Sometimes it's not. For the most part, it's just "not bad".

Will Python die as a programming language? The author doesn't think so.

So, is its charm disappearing? Maybe a little bit, but just a little bit.

At this point, the study of "what are the shortcomings of Python" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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