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Python development software can be divided into two types according to its different uses. One is the Python code editor and the other is the Python integrated development tool. The combined use of the two can greatly To improve the programming efficiency of Python developers, the following are several commonly used Python code editors and Python integrated development tools.
1. Python code editor
1. Sublime Text
Sublime Text is a very popular code editor that supports Python code editing , compatible with all platforms at the same time, and rich plug-ins extend the grammar and editing functions. It is fast, compact, has good compatibility, and is very popular among programmers!
2. Vim
Vim and Vi are model editors that separate text viewing from text editing. VIM has made many improvements over the original VI, including extensible models. and in-place code building, VIMScripts can be used for a variety of Python development tasks!
3. Atom
Atom is called the "21st century hackable text editor". It is compatible with all platforms and has a stylish interface, file system browser and extension market. Use Built with Electron, its runtime-installed extensions support the Python language!
4. GNU Emacs
GNU Emacs is a lifetime free code editor compatible with any platform, customized using the powerful Lisp programming language and providing a variety of custom scripts for Python development , is an extensible, customizable, automatic recording, and real-time display editor that has always been around UNIX.
5. Visual Studio Code
Visual Studio Code is a full-featured code editor compatible with Linux, Mac OS X and Windows platforms. It is extensible and configurable for almost all tasks. For Python support, you can install the plug-in in Visual Studio Code. It can be installed successfully with a quick click of the button, and Python installations and libraries can be automatically recognized.
2. Python Integrated Development Environment
1. PyCharm
PyCharm is the only full-featured integrated development environment specifically for Python. Likewise With both paid and free open source versions, PyCharm supports quick installation and use in Windows, Mac OS X, 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. Eclipse PyDev
PyDev is a plug-in for the Eclipse integrated development environment. It supports Python debugging, code completion and interactive Python console. It is very convenient to install PyDev in Eclipse. Just You need to select "Help" from Eclipse, click "Eclipse Marketplace" and then search for PyDev, click Install, and restart Eclipse when necessary. For experienced Eclipse developers, PyDev can be easily used!
3. Visual Studio
Visual Studio is a full-featured integrated development platform that provides free and paid versions. It can support the development of various platforms and comes with its own extension plug-ins. market. Python programming can be performed in Visual Studio, and Python IntelliSense, debugging and other tools are supported. It is worth noting that Visual Studio does not support the Linux platform!
4. Spyder
Spyder is an open source Python integrated development environment optimized for data science workflows. It is included with the Anaconda package manager distribution. Spyder has Most integrated development environments should have functions, such as a code editor with powerful syntax highlighting, Python code completion, and an integrated file browser. It also has a variable browser function that is not available in other Python editing environments, making it very suitable. Data scientists using Python.
5. Thonny
Thonny is an integrated development environment for novices. It is suitable for all mainstream platforms. By default, Thonny will be installed together with the bundled Python version, which is very convenient. Used by novices!
Note: Novices should not download and install Python software directly. The installation is very troublesome. You will also need to install various libraries later. It is easier and more convenient to directly install Anaconda, the integrated version of Python, which is already integrated. Various libraries are available for your use in artificial intelligence.
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