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.

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 …

A quick start guide to get you up and coding with the Python extension in Visual Studio Code.

We recommend you install a Python interpreter into your conda environment, otherwise one will be installed for you after you select the environment. For example, the following command …

In this section, we will create a folder to open as a workspace in VS Code, set up a Python virtual environment, and install the project's dependencies. In your file system, create a project folder …

If you do not have any Jupyter kernel or Python environment on your machine, VS Code can help you set up: go to the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), select Python: …

The VS Code Native REPL for Python builds upon the classic Python REPL and provides additional features, such as Intellisense and syntax highlighting to make your Python …

Visual Studio Code is free and available on your favorite platform - Linux, macOS, and Windows. Download Visual Studio Code to experience a redefined code editor, optimized for building …

This tutorial demonstrates using Visual Studio Code and the Microsoft Python extension with common data science libraries to explore a basic data science scenario.

To work with Python in Jupyter Notebooks, you must activate an Anaconda environment in VS Code, or another Python environment in which you've installed the Jupyter package.