In early June, Guido van Rossum, the father of Python, gave a speech called "Python Language" at today's PyCon US conference. Recently, he accepted an interview with IT media Infoworld and talked about the future of Python. Let’s take a look at what Father Guido thinks of the future of Python.
The application of Python in the field of mobile computing
Guido: Mobile is still a difficult platform for Python, but it is not as difficult as the browser platform because Python can actually run on all brands of smartphones Up. You just need to find someone who knows how to build a mobile version of Python.
Standard CPython source code can almost be compiled into binaries that can run on Android and Apple phones. There are many people working hard in this area and constantly contributing patch packages. But progress has been slower than I would have liked. But then again, I don’t develop mobile apps myself, so I don’t have much motivation to get involved myself. But I'd love to see progress on this.
Python replaces JavaScript?
Guido: This is not our goal. Due to the structural issues of the browser platform, it is difficult for us to compete with JavaScript. The most we can do is translate Python into JavaScript. Typically, however, translated programs run slower than native Python programs and slower than similar programs written in JavaScript. Now some people are trying to translate Python into JavaScript and run Python in the browser.
Thoughts on WebAssembly
This might make it possible to run Python in the browser. If it replaces asm.js, it basically means that JavaScript is no longer the only language used on the Web platform, but becomes this thing similar to assembly language. This is a bit like Python. The underlying Python interpreter of the Python code you write is actually written in C language. During compilation, the Python code is translated into machine code, and some kind of assembly language is also involved.
If we can’t kill JavaScript in browsers, we might be able to make JavaScript the unifying translation object for any language that wants to run in a browser. In this case, perhaps Python and other languages, such as Ruby and PHP, can be efficiently translated into the underlying JavaScript.
WebAssembly is actually an opportunity for Python developers. I believe there will be a trial period where those who prefer development tools can have the opportunity to explore the best way to run Python on top of WebAssembly. After their experiment is successful and they start to promote it, we can say to Python developers, "You can now write browser client apps in Python." But now is not the time.
Python performance improvements
Guido: The performance of Python 3 has caught up and is much faster than in 2012. Alternatively, there are Python implementations like PyPy. There are some new versions of the Python interpreter that are also trying to improve speed.
In fact, the performance of Python is not as bad as people say, and because Python is mostly implemented in C language, many things can be done as fast as C language. I still think that Python is fast enough for most things.
Although there are no new features in Python 3 to improve speed, we have made many aspects of the language faster: for example, reference counting is faster than before. The main thing is to optimize the existing code, but as a user, it is difficult to notice the difference.
And if you urgently need to speed up a Python program, you can try using PyPy. It's mature enough to be worth trying.
Why is Python popular?
Guido: Mainly because it is easy to learn and use, and the community is open and developers are active and helpful.
How is Python development currently and in the future? What's the plan?
Guido: Currently, and over the past five years or so, it is mainly other people who are driving the development of Python. I occasionally provide guidance on whether a new idea is worth accepting, usually when designing to add new syntax. I rarely interfere when it comes to standard library development. Sometimes, I have to ask everyone to stop discussing and compromise.
My idea is to make the community self-perpetuating so that I can eventually retire or at least take a long vacation. I hope that in the future this language will absorb new ideas from other languages or other fields.
I finally want to talk about SciPy and NumPy. These two teams are promoting the use of Python as an alternative to Matlab. Our alternatives are open source and better, they can do it. They are taking Python into areas I never imagined before. They've developed things like Jupyter Notebooks for using interactive Python in the browser.

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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