This article mainly introduces what plug-in software needs to be installed before installing python. It has certain reference value and friends in need can refer to it. I hope you will gain a lot after reading this article. Let the editor take you to understand it together.
Python
The Python plug-in must be installed because it was developed by Microsoft's VSCode development team and is at the level of a son. Although VSCode can highlight Python code without installing any plug-ins, the plug-in provides far more than that, and there are many powerful functions, such as:
Smart completion: Edit code with auto-completion, code navigation, syntax checking, etc. Code inspection: Use Pylint, Flake8 to get additional code analysis, check for programming errors Code format: Use black, autopep or YAPF to adjust code format Debugging: Debugging
Python Scripts, web applications, and remote or multi-threaded processes
Testing: Run and debug tests via unittest, pytest or nose in Test Explorer Jupyter
Notebook: Create and edit Jupyter
Notebooks, add and run code units, render plots, visualize via Variable Explorer Variables, visualizing dataframes using the data viewer, and more Environments: automatically activate and
switch between virtualenv, venv, pipenv, conda, and pyenv environments Refactoring: Refactoring with variable extraction, method extraction, and import sorting
Python Snippets
The Python Snippets plug-in can make our Python programming more efficient and GPT rewritten . It contains a large number of built-in methods, as well as string, list, sets, tuple, dictionary, class code snippets, and also provides at least one example for each code snippet.
All python built-in method snippets
All python string snippets
All python list snippets
All python set snippets
All python tuple snippets
All python dictionary dictionary snippets
and include many other snippets (e.g. if/else, for, while, while/else, try/catch , file processing and class fragments and oop class examples (polymorphism, encapsulation, inheritance.ig)
Python Docstring Generator
Python Docstring Generator can automatically create docstrings, which really reduces a lot of work for developers.
And, the generated docstrings follow all standard formats, including Google, docBlockr, Numpy, Sphinx, and PEP0257. Its main functions include:
Quickly generate a tab-browsable docstring snippet
Choose between several different types of docstring formats Infer parameter
types via pep484 type hints, default values, and var names
Support for args, kwargs, modifiers, errors, and parameters type
Python Test Explorer for Visual Studio Code
This plugin is very convenient for functional testing by running Python Unittest or Pytest tests using the Test Explorer UI. The specific functions are as follows:
Display the Test Explorer in the Tests view in the sidebar of VS Code with all detected tests, suites and their status Convenient error
reporting during test discovery
Unit tests and Pytest Debugging
in the Explorer After selecting a test, the failed test log is displayed.
Supports multiple root workspaces.
Supports Unittest and Pytest testing frameworks and their plug-ins.
Python Preview
Python Preview can show the visual debugging process and add it to our Python code. It converts debugging code into an interactive session with animations and graphical elements to represent application state, making it very intuitive for code debugging.
Python Type Hint
Python Type Hint provides type hint autocompletion for Python, as well as completion for built-in types, classes, and typing modules.
Provides type-hint completions for built-in types, estimated types, and typing modules
Estimates correct types, provides completions
Python files can be searched in the workspace for type estimation
Jupyter
Jupyter can be said to be one of my favorite VS Code plug-ins, which allows us to use Jupyter Notebooks perfectly in VS Code.
How to use it:
- To create a new notebook, open the Command Palette (Windows: Ctrl + Shift + P; iOS: Command + Shift + P) and select the command Jupyter: Create New Blank Jupyter Notebook
- Select a kernel by clicking the kernel selector in the lower right corner of the status bar or by calling the Notebook: Select Notebook Kernel command.
- Change the cell language by clicking the language selector or calling the Notebook: Change Cell Language command.
