What development tools are used for python? The following article will give you some Python development tools, I hope it will be helpful to you.
python development tools
1, PyCharm
PyCharm is a Python IDE developed by JetBrains. PyCharm is used for the functions that general IDEs have, such as debugging, syntax highlighting, project management, code jumps, smart prompts, automatic completion, unit testing, version control... In addition, PyCharm also provides some good functions. Developed in Django, it also supports Google App Engine. What’s even cooler is that PyCharm supports IronPython!
2. Visual Studio PTVS
As we all know, Visual Studio is a powerful tool for developing Windows platform products and is the preferred IDE for C#, ASP.NET, etc. development. In fact, Visual Studio can also be used as a Python IDE. You only need to install the PTVS (Python Tools for Vistul Studio) plug-in on the basis of Visual Studio to quickly turn Visual Studio into a Python IDE for use.
3. Eclipse PyDev
Relying on the powerful eclipse, PyDev is particularly dazzling. Powerful debugging functions and a comfortable editing environment make PyDev win the favor of many people. However, eclipse is a resource hog, and PyDev has nothing to do about it. But now computers are very fast, and running eclipse is simply a small case, so you don’t have to worry too much.
In addition to its powerful debugging functions, PyDev's code reading capabilities, relying on eclipse, are unmatched by any other IDE. For example, holding down the CTRL key and clicking on a class will automatically jump to the definition of the class. This Very useful for reading code. Now the PyDev extension is also open source, so some (I don't know) advanced functions have also been integrated into PyDev.
4. Sublime Text
Sublime Text is one of the most popular editors among developers. It has multiple functions, supports multiple languages, and is very popular in the developer community. popular. Sublime has its own package manager that developers can use to install components, plugins, and additional styles, all of which improve your coding experience. Sublime can also be used with plug-ins to easily create a convenient IDE-like python debugging environment.
5. Spyder
Spyder (originally known as Pydee) is a powerful interactive Python language development environment, which is part of python(x,y). The complete python(x,y) has more than 400M and integrates python third-party libraries commonly used in scientific accounting. Provides advanced code editing, interactive testing, debugging and other features, supporting Windows, Linux and OS X systems.
6. Ulipad
Ulipad is a professional Python editor written by limodou, a Chinese. It is based on the GUI (graphical interface) developed by wxpython. It was formerly NewEdit. The automatic completion function is very convenient, but it does not integrate the interface designer wxGlade. Open source, you can use SVN to download the latest source code, relying on wxPython. Light, compact and powerful, it is very suitable for beginners.
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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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