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Python Interactive window
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: