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 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 how to:

Work with Jupyter-like code cells
Run code in the Python Interactive Window
View, inspect, and filter variables using the Variables Explorer and Data Viewer
Connect to a remote Jupyter server
Debug a Jupyter notebook
Export a Jupyter notebook

To work with Jupyter notebooks, you must activate an Anaconda environment in VS Code, or another Python environment in which you've installed the Jupyter package. To select an environment, use the Python: Select Interpreter command from the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)).

Once the appropriate environment is activated, you can create and run Jupyter-like code cells, connect to a remote Jupyter server for running code cells, and export Python files as Jupyter notebooks.

Jupyter code cells

You define Jupyter-like code cells within Python code using a # %% comment:

">⇧⌘P (Windows, Linux Ctrl+Shift+P)) to export content from a Python file in VS Code to a Jupyter notebook (with the .ipynb extension).

Jupyter: Export Current Python File as Jupyter Notebook: creates a Jupyter notebook from the contents of the current file, using the # %% and # %% [markdown] delimiters to specify their respective cell types.
Jupyter: Export Current Python File and Output as Jupyter Notebook: creates a Jupyter notebook from the contents of the current file and includes output from code cells.
Jupyter: Export Interactive Window as Jupyter Notebook: creates a Jupyter notebook from the contents of the Python Interactive window.

After exporting the contents, VS Code displays a prompt through which you can open the notebook in a browser.

02/04/2026