What software should beginners use to write python
The following are several commonly used Python code editors and Python integrated development tools.
Recommended learning: Python video tutorial
1. Python code editor
1. Sublime Text
Sublime Text is a very popular code editor that supports Python code editing and is compatible with all platforms. It has rich plug-ins that extend syntax and editing functions. It is fast, compact, and has good compatibility. Very popular among programmers!
2. Vim
Vim and Vi are model editors that separate text viewing from text editing. VIM has done a lot on top of the original VI. With improvements, including extensible models and in-place code building, VIMScripts can be used for a variety of Python development tasks!
3. Visual Studio Code
Visual Studio Code is a full-featured code editor compatible with Linux, Mac OS Configuring almost any task, support for Python can be installed in Visual Studio Code. The installation is successful with just a quick click of a button, and Python installations and libraries are automatically recognized.
2. Python Integrated Development Environment
1. PyCharm
PyCharm is the only comprehensive development environment specifically for Python. The functional integrated development environment also has a paid version and a free open source version. PyCharm supports quick installation and use in Windows, Mac OS X systems, and Linux systems.
PyCharm directly supports the Python development environment. You can open a new file and start writing code. You can also run and debug Python programs directly in PyCharm. It also supports source code management and projects, and it has many conveniences. And support community, you can quickly learn to use it!
2. Spyder
Spyder is an open source Python integrated development environment optimized for data science workflow. It is included in the Anaconda software package Among the manager releases, Spyder has most of the features that an integrated development environment should have, such as a code editor with powerful syntax highlighting, Python code completion, and an integrated file browser. It also has features that are not found in other Python editing environments. The variable browser function is very suitable for data scientists using Python.
3. Thonny
Thonny is an integrated development environment for novices, applicable to all mainstream platforms. By default, Thonny will be bundled with Python The version is installed together, which is very convenient for novices to use!
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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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