Jupyter Notebooks
Jupyter Notebooks offer a flexible, interactive UI for combining code, prose, and visualizations.
Positron enhances Jupyter Notebooks in several key ways:
- Notebooks work out of the box. You don’t need to install any additional dependencies into your Python or R environments.
- Notebooks are integrated into the IDE, allowing you to manage data sources in the Connections Pane, view data at a glance in the Variables Pane, explore data in depth with the Data Explorer, and browse documentation in the Help Pane.
- Language features such as autocompletion and go-to-definition work seamlessly across notebooks and plaintext files.
Using Jupyter Notebooks
You can create and edit .ipynb files in Positron just as you would in other editors. For a general introduction to working with Jupyter Notebooks, see the VS Code Jupyter Notebooks documentation.
Setting up your environment
Positron comes prepackaged with Jupyter kernels for R and Python. Once you’ve configured an R or Python environment for Positron, you do not need to install any additional dependencies into your environment before using notebooks.
If an environment installed on your computer isn’t available in Positron, you may want to read more about how Positron discovers Python installations and R installations.
Selecting an interpreter
When you first open a Jupyter Notebook, Positron automatically selects an interpreter based on the notebook’s language, the current workspace, and your configuration.
We recommend matching the selected interpreter for the workspace and the notebook, however, they can be controlled separately.
You can manually select a different interpreter for the notebook by clicking the Kernel Selector button in the notebook toolbar or by running the Notebook: Select Notebook Kernel from the Command Palette.
