Python developers should install the following plug-ins to improve efficiency when using VS Code: 1. The official Python plug-in provides smart prompts, code jumps, formatting, debugging and other functions, and supports virtual environment switching; 2. Pylance, a language server built on Pyright, greatly improves the automatic completion speed and provides type check; 3. Jupyter plug-in, supports writing and running Notebook files in VS Code; 4. Auto Docstring, can automatically generate structured function comments. These plug-ins respectively optimize the core links in the development process, which can significantly improve development efficiency and code quality.
Python developers use VS Code, and installing plug-ins can really achieve twice the result with half the effort. Native support alone is not enough, these extensions have to be used to improve efficiency, code quality, and even debug experience.
Python official extension: basic but must be installed
Microsoft's own Python plug-in (produced by Microsoft) is standard for almost every Python developer. It provides smart prompts, automatic completion, code jump, formatting, linting, debugging and other functions, and is also very compatible with many other plug-ins.
After you install the Python interpreter, this plug-in will automatically detect the environment and can also help you switch the virtual environment. If you write Django or Jupyter Notebook, it also supports it.
Key points:
- Automatically identify pipenv, venv, conda and other virtual environments
- Integrate lint tools such as Pylint, Flake8 (need to be installed by yourself)
- Supports running tests (unittest and pytest) in the editor
Pylance: Make smart prompts as fast as lightning
Pylance is a language server launched by Microsoft, built on Pyright, and is much faster than the default Jedi, especially in large projects.
If you think the automatic completion of the official plug-in is a bit stuck or the response is slow, you should replace it with Pylance. It also provides practical functions such as type checking, parameter prompts, document previews, etc.
How to enable it? Just set Python > Language Server to Pylance in the settings.
Jupyter: Write Notebook directly in VS Code
If you do data analytics or machine learning, the Jupyter plugin is your best partner. It allows you to create .ipynb files in VS Code, or write cells directly in .py files, and execute them like a Notebook.
You can select different kernels, view variables, plot results, and even debug a cell.
Common Tips:
- Splitting cell with
# %% - When viewing variable values, you can click "Variable Explorer"
- Supports exporting to HTML or PDF
Auto Docstring: Automatically generate comments, worry-free and standardized
Docstring is not added to write a function? That may not be a good habit. Auto Docstring can help you quickly generate comments in standard formats, such as Google, NumPy, or Sphinx formats.
You just enter three quotes and press Enter, and it can automatically generate structured instructions based on the function parameters. This is especially useful for teamwork or open source projects.
For example:
def add(a, b):
"""
"""When you press Enter after three quotes, it will turn out like this:
def add(a, b):
"""
[summary]
Args:
a ([type]): [description]
b ([type]): [description]
Returns:
[type]: [description]
"""Basically these are the most practical. Some developers also install plug-ins related to formatting tools such as Black, isort, and Ruff, but those are advanced content. If you get the above ones first, the development efficiency can be greatly improved.
The above is the detailed content of Best VS Code extensions for Python. For more information, please follow other related articles on the PHP Chinese website!
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