On this page there are 10 sectionsOn this page

• Prerequisites
• Understand the Python setup
• Install a Python interpreter
• Start VS Code in a workspace folder
• Create a virtual environment
• Create a Python source code file
• Run Python code
• Configure and run the debugger
• Install and use packages
• Next steps

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.

Prerequisites

To successfully complete this tutorial, you need to first set up your Python development environment. Specifically, this tutorial requires:

• Python 3
• VS Code
• VS Code Python extension (For additional details on installing extensions, see Extension Marketplace)

Understand the Python setup

If you're new to programming tools, it helps to know that three separate pieces work together to run Python in VS Code:

• VS Code: the editor where you write and organize your code.

• Python extension: adds Python language support to VS Code, such as IntelliSense, running, and debugging. The extension doesn't include Python itself.

• Python interpreter: the program that actually runs your Python code. You install it separately from VS Code.

You install all three in this tutorial. VS Code is the workspace, the Python extension connects VS Code to Python, and the interpreter does the work of running your script.

Install a Python interpreter

Along with the Python extension, you need to install a Python interpreter. Which interpreter you use is dependent on your specific needs, but some guidance is provided below.

Windows

Install Python from python.org. Use the Download Python button that appears first on the page to download the latest version.

Note: If you don't have admin access, an additional option for installing Python on Windows is to use the Microsoft Store. The Microsoft Store provides installs of supported Python versions.

For additional information about using Python on Windows, see Using Python on Windows at Python.org

macOS

The system install of Python on macOS is not supported. Instead, a package management system like Homebrew is recommended. To install Python using Homebrew on macOS use brew install python3 at the Terminal prompt.

Note: On macOS, make sure the location of your VS Code installation is included in your PATH environment variable. See these setup instructions for more information.

Linux

The built-in Python 3 installation on Linux works well, but to install other Python packages you must install pip with get-pip.py.

Other options

• Data Science: If your primary purpose for using Python is Data Science, then you might consider a download from Anaconda. Anaconda provides not just a Python interpreter, but many useful libraries and tools for data science.

• Windows Subsystem for Linux: If you are working on Windows and want a Linux environment for working with Python, the Windows Subsystem for Linux (WSL) is an option for you. If you choose this option, you'll also want to install the WSL extension. For more information about using WSL with VS Code, see VS Code Remote Development or try the Working in WSL tutorial, which will walk you through setting up WSL, installing Python, and creating a Hello World application running in WSL.

Note: To verify that you've installed Python successfully on your machine, run one of the following commands (depending on your operating system):

Linux/macOS: open a Terminal Window and type the following command:

If the installation was successful, the output window should show the version of Python that you installed. Alternatively, you can use the py -0 command in the VS Code integrated terminal to view the versions of python installed on your machine. The default interpreter is identified by an asterisk (*).

Start VS Code in a workspace folder

By starting VS Code in a folder, that folder becomes your "workspace".

Using a command prompt or terminal, create an empty folder called "hello", navigate into it, and open VS Code (code) in that folder (.) by entering the following commands:

When you start typing print, notice how IntelliSense presents auto-completion options.

IntelliSense and auto-completions work for standard Python modules as well as other packages you've installed into the environment of the selected Python interpreter. It also provides completions for methods available on object types. For example, because the msg variable contains a string, IntelliSense provides string methods when you type msg.:

Finally, save the file (⌘S (Windows, Linux Ctrl+S)). At this point, you're ready to run your first Python file in VS Code.

For full details on editing, formatting, and refactoring, see Editing code. The Python extension also has full support for Linting.

Run Python code

Click the Run Python File play button in the top-right side of the editor.

The button opens a terminal panel in which your Python interpreter is automatically activated, then runs python3 hello.py (macOS/Linux) or python hello.py (Windows):

There are three other ways you can run Python code within VS Code:

1. Right-click anywhere in the editor window and select Run Python > Run Python File in Terminal (which saves the file automatically):

2. Select one or more lines, then press Shift+Enter or right-click and select Run Python > Run Selection/Line in Python Terminal. Alternatively, you can activate Smart Send using Shift+Enter without a selection and the Python extension will send the smallest runnable block of code near where your cursor is placed to the terminal. This command is convenient for testing just a part of a file.

   Note: If you prefer to send code at the particular line your cursor is placed, you can turn off Smart Send by setting python.REPL.enableREPLSmartSend : "false" in your User settings.

3. From the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), select the Python: Start Terminal REPL command to open a REPL terminal (notated by >>>) for the currently selected Python interpreter. In the REPL, you can then enter and run lines of code one at a time.

Congrats, you just ran your first Python code in Visual Studio Code!

Configure and run the debugger

Let's now try debugging our Python program. Debugging support is provided by the Python Debugger extension, which is automatically installed with the Python extension. To ensure it has been installed correctly, open the Extensions view (⇧⌘X (Windows, Linux Ctrl+Shift+X)) and search for @installed python debugger. You should see the Python Debugger extension listed in the results.

Next, set a breakpoint on line 2 of hello.py by placing the cursor on the print call and pressing F9. Alternately, click in the editor's left gutter, next to the line numbers. When you set a breakpoint, a red circle appears in the gutter.

Next, to initialize the debugger, press F5. Since this is your first time debugging this file, a configuration menu will open from the Command Palette allowing you to select the type of debug configuration you would like for the opened file.

Note: VS Code uses JSON files for all of its various configurations; launch.json is the standard name for a file containing debugging configurations.

Select Python File, which is the configuration that runs the current file shown in the editor using the currently selected Python interpreter.

The debugger will start, and then stop at the first line of the file breakpoint. The current line is indicated with a yellow arrow in the left margin. If you examine the Local variables window at this point, you can see that the msg variable appears in the Local pane.

A debug toolbar appears along the top with the following commands from left to right: continue (F5), step over (F10), step into (F11), step out (⇧F11 (Windows, Linux Shift+F11)), restart (⇧⌘F5 (Windows, Linux Ctrl+Shift+F5)), and stop (⇧F5 (Windows, Linux Shift+F5)).

The Status Bar also changes color (orange in many themes) to indicate that you're in debug mode. The Python Debug Console also appears automatically in the lower right panel to show the commands being run, along with the program output.

To continue running the program, select the continue command on the debug toolbar (F5). The debugger runs the program to the end.

Tip Debugging information can also be seen by hovering over code, such as variables. In the case of msg, hovering over the variable will display the string Roll a dice! in a box above the variable.

You can also work with variables in the Debug Console (If you don't see it, select Debug Console in the lower right area of VS Code, or select it from the ... menu.) Then try entering the following lines, one by one, at the > prompt at the bottom of the console:

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 one of the following methods:

Option 1: Use the Package Management UI

1. Open the Python sidebar and expand Environment Managers
2. Right-click on your environment and select Manage Packages
3. Search for numpy and select Install

Option 2: Use the terminal

Run Terminal: Create New Terminal (⌃⇧` (Windows, Linux Ctrl+Shift+`)) from the Command Palette. 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:

You can now use the newly generated requirements.txt file to install dependencies in another environment. Furthermore, you can continue to add dependencies to it as your project may grow in complexity.