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Editor to share with you what Python text editors, I believe that most people do not know much, so share this article for your reference, I hope you can learn a lot after reading this article, let's go to know it!

1 、 Sublime

Let's start with my favorite text editor, Sublime. Sublime is a free text editor with a paid version that you can use to write, edit, and debug code in almost any programming language. When you first downloaded and installed Sublime, it was just a plain, somewhat tedious text editor. However, the power of Sublime is that you can install add-ons based on the programming language you want to use.

The best part about Sublime plugins is that you can customize them to match your needs, from color to overall appearance, as well as connectivity to GitHub or other platforms. It takes less than 30 minutes to set up Sublime as the perfect development environment, and then you can get to work.

2 、 Spyder

Next is Spyder, the scientific Python development environment. Spyder is a free open source IDE development, especially for Python. Compared with other ide, the biggest advantage of Spyder is that it is lightweight. Spyder is a good choice for data science and machine learning applications because it has an interactive coding mode that allows you to analyze data in real time.

Spyder also provides the ability to examine the entire code base or divide it into parts for a closer look. It also integrates many commonly used data science packages, such as NumPy, Pandas, SciPy, and IPython. However, perhaps the biggest advantage of using IDE is their integrated debugger. Spyder has a wonderful graphical debugger that makes your testing and error location tasks smooth and easy.

3 、 Atom

Our next text editor is Atom. Atom is an open source text editor developed by GitHub. Atom was developed to support many commonly used programming languages, such as Java and Ruby on Rails. However, it can be customized to provide a good user experience when writing Python code. In addition, Atom provides a number of plug-ins that make it one of the best editors to use when building data science applications, such as the data Atom package that allows SQL queries to be executed.

In addition to powerful software packages, one of the advantages of Atom is its community. Atom has one of the most active communities that have been working on it to make it more suitable for developers. Needless to say, Atom has a powerful Git integration that makes project version control tracking easy.

4 、 Visual Studio Code

Visual Studio Code (VS Code) is one of the most complete and widely used ide. VS Code is a very popular IDE used by Python, C, c #, and JavaScript developers. VS Code is free, lightweight, and open source. But it also offers paid versions for companies.

VS Code has many advantages, especially for beginners, because when you define a function or class or have a small syntax error, it provides hits and pointers to help you. VS Code also has a good integration with PyLint, and PyLint is a Python checker for checking code errors. Another advantage of using VS Code is that it is very easy to perform unit tests and REPL (read-evaluate-print loop) operations.

5 、 PyCharm

If you are learning Python, you may use the next IDE on our list. PyCharm is probably the most famous Python IDE. It was originally developed for Python, which is its biggest advantage. Although it is good to support multiple programming languages, building a specific IDE for one language usually provides a more robust development environment.

PyCharm provides many Python features, such as code / error highlighting, Git integration, and a powerful graphical debugger. The PyCharm Code Editor also allows you to customize its appearance and color to match your comfort. In addition, PyCharm has many plug-ins that you can add to extend its functionality.

6 、 Jupyter Notebooks

Last but not least, the most popular in the data science community is Jupyter Notebook. When I created this list, I couldn't help but mention Jupyter Notebook. Jupyter is an open source, free development environment that is widely used in the programming community because it is versatile, robust, and easy to share code files.

Jupyter Notebook enables developers to mix code bits with markdown, HTML, and LaTeX text. Jupyter notebook is a server-based structure that is easy to use and operate in browsers. Due to the use of IPython, it has a powerful visualization ability, which makes it a favorite, especially in data science and quantum computing. The extension to Jupyter Notebook is Jupyter Lab, which provides more features, such as a visual debugger.

These are all the contents of the article "what are the text editors in Python?" Thank you for reading! I believe we all have a certain understanding, hope to share the content to help you, if you want to learn more knowledge, welcome to follow the industry information channel!

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