Visual Studio Code Python | Python Profile Template

Python in Visual Studio Code

Working with Python in Visual Studio Code, using the Microsoft Python extension, is simple, fun, and productive. The extension makes VS Code an excellent Python editor, and works on any operating system with a variety of Python interpreters. It leverages all of VS Code’s power to provide auto complete and IntelliSense, linting, debugging, and unit testing, along with the ability to easily switch between Python environments, including virtual and conda environments.

This article provides only an overview of the different capabilities of the Python extension for VS Code. For a walkthrough of editing, running, and debugging code, use the button below.

Command line extension management

To make it easier to automate and configure VS Code, it is possible to list, install, and uninstall extensions from the command line. When identifying an extension, provide the full name of the form

publisher.extension

, for example

ms-python.python

.

Example:


code --extensions-dir



Set the root path for extensions. code --list-extensions List the installed extensions. code --show-versions Show versions of installed extensions, when using --list-extension. code --install-extension (

|

) Installs an extension. code --uninstall-extension (

|

) Uninstalls an extension. code --enable-proposed-api (

) Enables proposed API features for extensions. Can receive one or more extension IDs to enable individually.








You can see the extension ID on the extension details page under the Marketplace Info.

Python and Visual Studio Code Setup

In this part, we will learn to install Python and VSCode and run a simple Python code.

Installing Python

Downloading and installing the latest version of Python is straightforward. Go to Python.org and download the latest version for Windows. The installer is also available for Linux/Unix, macOS, and other platforms. After downloading the installer, install Python with default settings.

Image from Python.org

The most popular way of installing Python is through Anaconda Distribution. It comes with a pre-installed package and software for us to start coding without hiccups. It is available for Windows, macOS, and Linux operating systems.

Image from Anaconda

After installing Python on our operating system, check whether it is properly working by typing the following command in CLI / Terminal.


python --version


Output:


Python 3.9.13


Other Python installation methods

We can also install Python using various CLI tools or through the Windows store.

You can check out our full guide on how to install Python for more details. Similarly, our interactive Introduction to Python course helps you master the basics of Python syntax, lists, functions, packages, and Numpy.

Installing VSCode

Installing VSCode is super simple. Download and install the stable build from the official website. The installer is available for all kinds of operating systems, including web browsers.

Image from Visual Studio Code

Other VSCode installation methods

We can install using Microsoft store, Snap Store, and multiple CLI tools for Windows, Linux, and macOS.

Running Python in VSCode

After installing Python and VSCode, it is time to write a simple code and run the Python file within the IDE.

Create a new file

At start, you will see the welcome note. Ignore that and go to File > New Text File or use the keyboard shortcut Ctrl + N to create a new file. After that, write a simple print expression to display “Hello World.”

Save Python file

Save the file using Ctrl + S. Select the file directory and type the file name. Make sure to add `.py` at the end of the file name.

Select the interpreter

To run the Python file, we need to select the Python interpreter. By default, the Anaconda environment comes with Python version 3.9.13.

Run a Python file

To run the Python file, simply click on the Run button on the top left, as shown in the image. It will initialize the terminal and run the Python file to display the output.

You can also type python test.py in the terminal to run the file present in the current directory.

Vì sao nên lập trình Python với Visual Studio Code

1. Hỗ Trợ Python Mạnh Mẽ:
   • Extension Python cho VSCode được phát triển chủ yếu bởi Microsoft, đồng nghĩa với việc nó nhận được sự hỗ trợ chủ đạo và cập nhật liên tục. Extension này mang lại các tính năng mạnh mẽ như Intellisense (dự đoán mã), kiểm tra lỗi, đồng bộ hóa môi trường ảo, và tích hợp với các công cụ debugging. Điều này giúp tăng cường trải nghiệm lập trình Python và làm cho quá trình phát triển trở nên dễ dàng.
2. Giao Diện Người Dùng Thân Thiện và Linh Hoạt:
   • VSCode có một giao diện người dùng thân thiện và đơn giản. Bạn có thể dễ dàng tìm hiểu và sử dụng mà không cần nhiều thời gian học cách sử dụng. Nó cũng hỗ trợ các tính năng linh hoạt như split view, giúp bạn làm việc trên nhiều tệp và thư mục cùng một lúc.
3. Tích Hợp Git và Công Cụ Quản Lý Phiên Bản:
   • VSCode tích hợp sẵn với Git, một hệ thống quản lý phiên bản phổ biến. Điều này giúp bạn theo dõi sự thay đổi trong mã nguồn, thực hiện commit, push và pull mà không cần rời khỏi môi trường phát triển. Tích hợp với Git làm cho quản lý phiên bản trở nên thuận tiện và linh hoạt.
4. Mở Rộng Bằng Extension và Cộng Đồng Lớn:
   • VSCode có một cộng đồng lớn và đa dạng, với nhiều extension sẵn có để mở rộng tính năng của nó. Cộng đồng này liên tục phát triển và cung cấp nhiều tài nguyên hữu ích, từ theme đến các extension giúp tối ưu hóa quá trình phát triển Python. Điều này giúp đảm bảo rằng bạn có thể tận dụng những công cụ tốt nhất để phát triển ứng dụng của mình.

Tổng cộng, VSCode không chỉ là một IDE phổ biến mà còn là một môi trường phát triển hiệu quả cho Python với sự linh hoạt, tích hợp tốt và cộng đồng lớn. Nếu bắt đầu học Python, hãy tham khảo hướng dẫn lập trình Python với Visual Studio Code trên.

Xem thêm Cơ sở lập trình Python

Để được hướng dẫn lập trình Python với Visual Studio Code chi tiết và bài bản từ chuyên gia, để lại thông tin phía dưới:

Aptech Việt Nam

Fanpage: https://www.facebook.com/aptechvietnam.com.vn

Install and use packages

Let’s build upon the previous example by using packages.

In Python, packages are how you obtain any number of useful code libraries, typically from PyPI, that provide additional functionality to your program. For this example, you use the

numpy

package to generate a random number.

Return to the Explorer view (the top-most icon on the left side, which shows files), open

hello.py

, and paste in the following source code:


import numpy as np msg = "Roll a dice" print(msg) print(np.random.randint(1,9))


Tip: If you enter the above code by hand, you may find that auto-completions change the names after the


as

keywords when you press Enter at the end of a line. To avoid this, type a space, then Enter.

Next, run the file in the debugger using the “Python: Current file” configuration as described in the last section.

You should see the message, “ModuleNotFoundError: No module named ‘numpy'”. This message indicates that the required package isn’t available in your interpreter. If you’re using an Anaconda distribution or have previously installed the

numpy

package you may not see this message.

To install the

numpy

package, stop the debugger and use the Command Palette to run Terminal: Create New Terminal (⌃⇧` (Windows, Linux Ctrl+Shift+`)). This command opens a command prompt for your selected interpreter.

To install the required packages in your virtual environment, enter the following commands as appropriate for your operating system:

1. Install the packages

   
# Don't use with Anaconda distributions because they include matplotlib already. # macOS python3 -m pip install numpy # Windows (may require elevation) py -m pip install numpy # Linux (Debian) apt-get install python3-tk python3 -m pip install numpy


2. Now, rerun the program, with or without the debugger, to view the output!

Congrats on completing the Python tutorial! During the course of this tutorial, you learned how to create a Python project, create a virtual environment, run and debug your Python code, and install Python packages. Explore additional resources to learn how to get the most out of Python in Visual Studio Code!

Testing Support

VS Code can automatically recognize existing Python tests written in the

unittest

framework, or the

pytest

or

Nose

frameworks if those frameworks are installed in the current environment. I have a unit test written in

unittest

for the equation eval library, which you can use for this example.

To run your existing unit tests, from any Python file in the project, right-click and select Run Current Unit Test File. You’ll be prompted to specify the test framework, where in the project to search for tests, and the filename pattern your tests utilize.

All of these are saved as workspace settings in your local

.vscode/settings.json

file and can be modified there. For this equation project, you select

unittest

, the current folder, and the pattern

*_test.py

.

Once the test framework is set up and the tests have been discovered, you can run all your tests by clicking Run Tests on the Status Bar and selecting an option from the Command Palette:

You can even run individual tests by opening the test file in VS Code, clicking Run Tests on the Status Bar, and selecting the Run Unit Test Method… and the specific test to run. This makes it trivial to address individual test failures and re-run only failed tests, which is a huge time-saver! Test results are shown in the Output pane under Python Test Log.

Conclusion

Visual Studio Code is one of the coolest general purpose editors and a great candidate for Python development. In this article, you learned:

• How to install VS Code on any platform
• How to find and install extensions to enable Python-specific features
• How VS Code makes writing a simple Python application easier
• How to run and debug existing Python programs within VS Code
• How to work with Git and GitHub repositories from VS Code

Visual Studio Code has become my default editor for Python and other tasks, and I hope you give it a chance to become yours as well.

If you have questions or comments, please reach out in the comments below. There is also a lot more information at the Visual Studio Code website than we could cover here.

The author sends thanks to Dan Taylor from the Visual Studio Code team at Microsoft for his time and invaluable input in this article.

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Python Development in Visual Studio Code (Setup Guide)

Enable Visual Studio Code to seamlessly identify the correct runtime for your project, letting you leverage the security and compliance features inherent in the ActiveState project within your integrated development environment (IDE).

Before using your ActiveState project’s Python interpreter in your VS Code environment, make sure the following conditions are met:


state update. If you have installed the State Tool after opening VS Code you will need to restart VS Code for the changes to take effect.


The following will help you integrate Visual Studio Code with your ActiveState project.

Begin by creating a Python file in your project, or opening an existing Python file. If this is a new file you may be prompted to select an interpreter, or if it is an existing file you can select a new interpreter using the VS Code Command Palette.

To access the “Select Interpreter” drop-down from the Command Palette

This will automatically generate a list of all of the interpreters currently available on your machine (including those provided by ActiveState). Click to select your preferred interpreter and begin working on your file.

After making your selection your new interpreter will be displayed at the bottom of the VS Code window (“andrewd-activestate/PythonWindows3’:ActiveState” shown above).

If your ActiveState Python interpreter is not immediately available in the “Select Interpreter” dropdown:


python.activeStateToolPathunder the “Settings” list.


$PATHor


%PATH%variable. To enter the absolute path to the State Tool’s executable go to File > Preferences> Settings and search for ”State Tool”. Enter the absolute path to the State Tool executable in the field shown.



state projects


Extension Marketplace

Increase the power of Visual Studio Code through Extensions

The features that Visual Studio Code includes out-of-the-box are just the start. VS Code extensions let you add languages, debuggers, and tools to your installation to support your development workflow. VS Code’s rich extensibility model lets extension authors plug directly into the VS Code UI and contribute functionality through the same APIs used by VS Code. This article explains how to find, install, and manage VS Code extensions from the Visual Studio Code Marketplace.

How to create and open a Python project or file

If you have an existing Python project you wish to work on in VS Code, you can begin by opening your folder or file from the VS Code Welcome page or File Explorer view, or by selecting File > Open Folder (Ctrl+K Ctrl+O) or File > Open File (⌘O (Windows, Linux Ctrl+O)).

You can create a new Python file by selecting New File on the VS Code Welcome page and then selecting Python file, or by navigating to File > New File ().

Tip: If you already have a workspace folder open in VS Code, you can add new files or folders directly into your existing project. You can create new folders and files by using the corresponding New Folder or New File icons on the top level folder in the File Explorer view.

Next steps

• Python Hello World tutorial – Get started with Python in VS Code.
• Editing Python – Learn about auto-completion, formatting, and refactoring for Python.
• Basic Editing – Learn about the powerful VS Code editor.
• Code Navigation – Move quickly through your source code.
• Django tutorial
• Flask tutorial

Getting Started with Python in VS Code

In this tutorial, you will learn how to use Python 3 in Visual Studio Code to create, run, and debug a Python “Roll a dice” application, work with virtual environments, use packages, and more! By using the Python extension, you turn VS Code into a great, lightweight Python editor.

If you are new to programming, check out the Visual Studio Code for Education – Introduction to Python course. This course offers a comprehensive introduction to Python, featuring structured modules in a ready-to-code browser-based development environment.

To gain a deeper understanding of the Python language, you can explore any of the programming tutorials listed on python.org within the context of VS Code.

For a Data Science focused tutorial with Python, check out our Data Science section.

Supported locales

The extension is available in multiple languages:

de

,

en

,

es

,

fa

,

fr

,

it

,

ja

,

ko-kr

,

nl

,

pl

,

pt-br

,

ru

,

tr

,

zh-cn

,

zh-tw


Questions, issues, feature requests, and contributions

• If you have a question about how to accomplish something with the extension, please ask on Stack Overflow
• If you come across a problem with the extension, please file an issue
• Contributions are always welcome! Please see our contributing guide for more details
• Any and all feedback is appreciated and welcome!
  • If someone has already filed an issue that encompasses your feedback, please leave a 👍/👎 reaction on the issue
  • Otherwise please start a new discussion
• If you’re interested in the development of the extension, you can read about our development process

Installed extensions

The Python extension will automatically install the following extensions by default to provide the best Python development experience in VS Code:

• Pylance – to provide performant Python language support
• Python Debugger – to provide a seamless debug experience with debugpy

These extensions are optional dependencies, meaning the Python extension will remain fully functional if they fail to be installed. Any or all of these extensions can be disabled or uninstalled at the expense of some features. Extensions installed through the marketplace are subject to the Marketplace Terms of Use.

Python Extension Pack

Unsure which extensions to recommend to your students? You can point your students to the Python Education Extension Pack that contains essential and helpful extensions for the classroom. You can download the extension pack from the VS Code Marketplace:

The extension pack contains:

• Python for basic Python functionality like compiling, debugging support, linting, Jupyter Notebooks, unit tests, and more.
• Live Share to enable real-time collaboration.
• Remote – SSH to work on remote projects (for example, to access lab machines) through SSH with full VS Code functionality.
• Markdown+Math for full LaTeX support in Markdown.
• Python Test Explorer for Visual Studio Code to visualize and run Python tests in the side bar.
• Code Runner to run snippets (selected code) and single files of any code with a single click.

Run, debug, and test

Now that you are more familiar with Python in VS Code, let’s learn how to run, debug, and test your code.

Run

There are a few ways to run Python code in VS Code.

To run the Python script you have open on the editor, select the Run Python File in Terminal play button in the top-right of the editor.

There are also additional ways you can iteratively run snippets of your Python code within VS Code:

• Select one or more lines, then press Shift+Enter or right-click and select Run Selection/Line in Python Terminal. This command is convenient for testing just a part of a file.
• From the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), select the Python: Start REPL command to open a REPL terminal for the currently selected Python interpreter. In the REPL, you can then enter and run lines of code one at a time.

Debug

The debugger is a helpful tool that allows you to inspect the flow of your code execution and more easily identify errors, as well as explore how your variables and data change as your program is run. You can start debugging by setting a breakpoint in your Python project by clicking in the gutter next to the line you wish to inspect.

To start debugging, initialize the debugger by pressing F5. Since this is your first time debugging this file, a configuration menu will open allowing you to select the type of application you want to debug. If it’s a Python script, you can select Python File.

Once your program reaches the breakpoint, it will stop and allow you to track data in the Python Debug console, and progress through your program using the debug toolbar.

For a deeper dive into Python debugging functionality, see Python debugging in VS Code.

Test

The Python extension provides robust testing support for Unittest and pytest.

You can configure Python tests through the Testing view on the Activity Bar by selecting Configure Python Tests and selecting your test framework of choice.

You can also create tests for your Python project, which the Python extension will attempt to discover once your framework of choice is configured. The Python extension also allows you to run and debug your tests in the Testing view and inspect the test run output in the Test Results panel.

For a comprehensive look at testing functionality, see Python testing in VS Code.

Install Python and the Python extension

The tutorial guides you through installing Python and using the extension. You must install a Python interpreter yourself separately from the extension. For a quick install, use Python from python.org and install the extension from the VS Code Marketplace.

Note: To help get you started with Python development, you can use the Python profile template that includes useful extensions, settings, and Python code snippets.

Once you have a version of Python installed, select it using the Python: Select Interpreter command. If VS Code doesn’t automatically locate the interpreter you’re looking for, refer to Environments – Manually specify an interpreter.

You can configure the Python extension through settings. Learn more in the Python Settings reference.

Windows Subsystem for Linux: If you are on Windows, WSL is a great way to do Python development. You can run Linux distributions on Windows and Python is often already installed. When coupled with the WSL extension, you get full VS Code editing and debugging support while running in the context of WSL. To learn more, go to Developing in WSL or try the Working in WSL tutorial.

Tips and Tricks for Efficient Python Development in VSCode

VSCode comes with awesome Python development features and extensions. We can customize them to our needs and improve the productivity. In this section, we will learn about tips and tricks for efficient Python development.

1. Getting started: Help > Get Started. Learn about VSCode’s customization and features by following guided tutorials.
2. Command Palette: access entire all available commands by using the Keyboard shortcut: Ctrl+Shift+P. By writing keywords, we can access specific commands.
3. Keyboard shortcuts: better than command palettes. We can modify keyboard shortcuts or memorize them by using keyboard reference sheets. It will help us access the commands directly, instead of searching with the keyword.
4. Command line: launch the VSCode editor through the command line interface by typing `code .`. We can also customize how the editor is launched by adding additional arguments.
5. Errors and warnings: quick jump to errors and warnings in a project by using the keyboard shortcut: Ctrl+Shift+M. We can also cycle through the error with F8 or Shift+F8.
6. Customization: VSCode allows us to customize themes, keyboard shortcuts, JSON validation, debugging settings, fonts, and many more. It is a fully customizable IDE.
7. Extensions: other Python extensions improve our development experience. Look for popular extensions on the Visual Studio Marketplace.
8. Multi cursor selection: is a lifesaver. Add cursors at arbitrary positions by using Alt+Click. It will allow us to modify multiple lines of code at once. We can also use Ctrl+Shift+L to modify all occurrences of the current selection.
9. Search and modify: this is the best tool for searching and modifying multiple expressions at once. We can also rename the symbol by selecting the symbol and typing F2.
10. Git integration: allows us to perform all Git-related tasks within IDE. It provides an easy-to-use GUI for diff, views, staging, branching, committing, merging, and more.
11. Code Snippets: is our best friend. Just like Autohotkey, we are creating templates for repeating code patterns. To create a custom code snippet, select File > Preferences > Configure User Snippets and then select the language.
12. GitHub Copilot: is a winner extension for all kinds of development. It enhances the coding experience with artificial intelligence (AI) by suggesting lines of code or entire functions.

Bonus: sync your settings by logging into your GitHub account. It will sync your settings across all of the machines.

Configuring Linting and Formatting in VSCode

Linting

Linting highlights the problems in the Python source code and provides us with suggestions. It generally highlights syntactical and stylistic issues. Linting helps you identify and correct coding issues that can lead to errors.

You can select the linting method by selecting Python: Select Linter command in the command palette (Ctrl+Shift+P). You can also manually enable the linting method in settings.

Select linting method

In our case, we have selected the flake8 method. You can also review the list of available linting methods.

• Enable/ Disable Linting: select Python: Enable/Disable Linting in command palette.
• Run Linting: command palette (Ctrl+Shift+P) > Python: Run Linting.

Fixing the error

After running the Python linter, you will see the issues with the suggestions.

Note: Enabling a different linter will prompt you to install the required Python package.

Formatting

Formatting makes code readable. It follows specific rules for line spacing, indents, spacing around operators, and closing brackets. The Python extension supports three Python formatting methods: autopep8, black, or yapf.

By reading about PEP-8: Python Naming Conventions & Code Standards, you can learn Python’s style guide and formatting rules.

Select the Python formatter

To access the formatting option, we have to open the settings panel by going to Preferences -> Settings or using the keyboard shortcut: Ctrl +,. After that, type “python formatting provider” in the search bar and select “black” from the dropdown menu.

Configure Python formatter

For formatting the Python file on save, we have to search for format on save in the Settings and enable the Editor: Format on Save option.

Intro to CS at Harvey Mudd College

Professor Zachary Dodds is a Computer Science professor at Harvey Mudd College who teaches several introductory classes both for students new to Computer Science and students from a non-Computer Science background. He co-created the popular introduction to Computer Science class CS5, which attracts students from all backgrounds to develop programming and problem-solving skills and to build “a coherent, intellectually compelling picture of Computer Science”. The class is taught with Python and uses VS Code as the recommended editor.

Why Visual Studio Code?

Professor Dodds has been recommending and using Visual Studio Code in his classes since it debuted in 2015.

“Visual Studio Code is the best balance of authenticity and accessibility… Visual Studio Code doesn’t feel ‘fake’, it’s what real software developers use. Plus, Visual Studio Code works on every OS!”

VS Code runs on Windows, macOS, Linux, and even Chromebooks.

Classroom settings

Since VS Code is easy to customize, Professor Dodds is able to tailor the editor for his students, preferring to hide IntelliSense, or code completion suggestions, so they can learn from what they type and reinforce the conceptual models being built.

Here are the settings his students use:


"editor.quickSuggestions": false, "editor.acceptSuggestionOnCommitCharacter": false, "editor.suggest.filterGraceful": true, "editor.suggestOnTriggerCharacters": false, "editor.acceptSuggestionOnEnter": "on", "editor.suggest.showIcons": false, "editor.suggest.maxVisibleSuggestions": 7, "editor.hover.enabled": false, "editor.hover.sticky": false, "editor.suggest.snippetsPreventQuickSuggestions": false, "editor.parameterHints.enabled": false, "editor.wordBasedSuggestions": "matchingDocuments", "editor.tabCompletion": "on", "extensions.ignoreRecommendations": true, "files.autoSave": "afterDelay",


You can find the most up-to-date settings on his course website: CS5 – Python Tips.

Integrated Terminal

Professor Dodds also utilizes the built-in terminal heavily in his class as an introduction to running programs from the command line and navigating around their machine all within Visual Studio Code. He appreciates how “the built-in terminal panel does not try to automate too much (which, if it did, would deprive newcomers of the experience of the information-flow that’s going on).”

In the video below, the student does all of their command line and coding work in one place, such as installing Python libraries, while working on Lab 3 from the CS5 class:

Thank you, Professor Dodds, for sharing your story! If you’re interested in using VS Code to teach Python in your classes, you can get started with the Python Education Extension Pack below!

Install from a VSIX

You can manually install a VS Code extension packaged in a

.vsix

file. Using the Install from VSIX command in the Extensions view command dropdown, or the Extensions: Install from VSIX command in the Command Palette, point to the

.vsix

file.

You can also install using the VS Code

--install-extension

command-line switch providing the path to the

.vsix

file.


code --install-extension myextension.vsix


You may provide the

--install-extension

multiple times on the command line to install multiple extensions at once.

If you’d like to learn more about packaging and publishing extensions, see our Publishing Extensions article in the Extension API.

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