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Harmful code can be embedded in notebooks and the Workspace Trust feature allows you to indicate which folders and their contents should allow or restrict automatic code execution. When getting started with Notebooks, you'll want to make sure that you are working in a trusted workspace. Once the appropriate environment is activated, you can create and open a Jupyter Notebook, connect to a remote Jupyter server for running code cells, and export a Jupyter Notebook as a Python file. To select an environment, use the Python: Select Interpreter command from the Command Palette ( ⇧⌘P (Windows, Linux Ctrl+Shift+P)). 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.

View, inspect, and filter variables using the Variable Explorer and Data Viewer.

Create, open, and save Jupyter Notebooks.

This topic covers the native support available for Jupyter Notebooks and demonstrates how to:

Visual Studio Code supports working with Jupyter Notebooks natively, and through Python code files.

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.

Configure IntelliSense for cross-compiling.

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