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 …

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. …

The Python and Jupyter extensions work together to give you a great Notebook experience in VS Code, providing you the ability to directly view and modify code cells with IntelliSense support, …

To create local environments in VS Code using virtual environments or Anaconda, you can follow these steps: open the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), search for the …

Run Python code. The Python extension offers various ways to run Python code without extra configuration. Select the Run Python File in Terminal play button in the top-right of the editor.

Jupyter (formerly IPython Notebook) is an open-source project that lets you easily combine Markdown text and executable Python source code on one canvas called a notebook. Visual …

Two common options are to use the Python File configuration to run the currently open Python file or to use the Attach using Process ID configuration to attach the debugger to a process that is …

Visual Studio Code supports working with Jupyter Notebooks natively, as well as through Python code files. This topic covers the support offered through Python code files and demonstrates …

Data Wrangler is a code-centric data viewing and cleaning tool that is integrated into VS Code and VS Code Jupyter Notebooks. It provides a rich user interface to view and analyze your …

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 …