


The learning process of Python is indispensable with Python environment development tools. These Python development tools can help developers improve the efficiency of Python development. An efficient code editor or IDE should provide plug-ins, tools and other features that can help developers develop efficiently. Let’s follow the editor to learn about some popular Python environment development tools.
1. VIM
VIM is a very advanced text editor that is very popular in the python developer community. It is an open source software and follows the GPL license, so you can use it for free.
Although VIM is the best text editor, it provides no less functionality than this. After correct configuration, it can become a full-featured Python development environment. In addition, VIM is also a lightweight, modular, and fast-response tool, which is very suitable for those very good programmers - people who never use a mouse for programming.
The initial configuration will take some time, because you need to install some VIM plug-ins and configure them to work properly. In the end, you will find that it is all worth the effort. If you are looking for a python IDE under Linux system, then VIM will be your best choice.
VIM download URL: https://vim.sourceforge.io/scripts/script.php?script_id=31
2. Wing IDE
WingIDE is another commercial The Python integrated development environment for professional developers can run on Windows, OS X and Linux systems, and supports the latest versions of Python, including stackless Python (an enhanced version of Python). Wing IDE is divided into three versions: free basic version, personal version, and more powerful professional version.
The debugging function is a highlight of Wing IDE, including multi-thread debugging, thread code debugging, automatic sub-process debugging, breakpoints, single-step code debugging, code data inspection and other functions. In addition, it also provides in-tree Remote debugging function on Berry Pi.
In terms of code management, Wing IDE can be very flexibly integrated with tools such as Git, subversion, perforce, cvs, Bazaar, and Mercurial.
In addition, Wing IDE also supports other python frameworks, such as Maya, MotionBbuilder, Zope, PyQt, PySide, pyGTK, PySide, Django, matplotlib, etc.
Wing IDE download URL: http://www.archaeopteryx.com/
3. Emacs - Python Editor cum IDE
Emacs has its own ecosystem, It is an extensible and highly customizable GNU text editor. It can be configured as a fully functional free python integrated development environment.
Emacs is very popular in python development, and it provides python out of the box through python-mode. Emacs can add more advanced features through additional extension packages.
Emacs download URL: http://www.gnu.org/software/emacs/
4. PyCharm – the best commercial python IDE
PyCharm is a professional python integrated development environment with two versions. One is a free community version and the other is a more advanced professional version for enterprise developers.
Most of the features are available in the free version, including intelligent code completion, intuitive project navigation, error checking and repair, code quality inspection following PEP8 specifications, intelligent refactoring, graphical Debugger and runner. It can also be integrated with IPythonnotebook and supports Anaconda and other scientific computing packages, such as matplotlib and NumPy.
The professional version of PyCharm supports more advanced features, such as remote development functions, database support, and support for web development frameworks.
PyCharm download URL: http://www.jetbrains.com/pycharm/download/#section=windows
The IDEs mentioned above each have their own styles. , but all try to achieve a common requirement, namely rapid development of scalable and manageable code. You can choose any IDE that suits your needs, and you can easily get a python integrated development environment that supports Windows, Mac or Linux environments.
For more related knowledge, please visit the Python tutorial column of php Chinese website.
The above is the detailed content of introductory knowledge of Python. For more information, please pay attention to Python related articles on php Chinese website!
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Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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