What it does
Jupyter Notebook is Project Jupyter's classic, document-centered interface for interactive computing. In a browser, users edit code cells, run them with a language kernel, and keep outputs alongside Markdown explanations, equations, and visualizations in shareable .ipynb documents. The open-source project can serve a local workspace or run on remote infrastructure. It is distinct from JupyterLab, the separately named, more flexible web IDE in the same project.
Work in a computational document
The documented local workflow starts a Notebook server, which opens a browser interface and a dashboard for the chosen working directory. From the dashboard, create a notebook, select an available kernel, and alternate code cells with Markdown notes. Run a cell with Shift-Enter; its output stays beside the code that produced it. The default IPython kernel runs Python, while other languages require their own installed kernels.
An .ipynb file stores inputs, outputs, and explanatory text as a JSON document, so a notebook can be shared or version-controlled as a unit. The documentation also describes exporting to static formats with nbconvert and viewing public notebooks as rendered pages. This makes the format useful for a report that needs to show both a calculation and the reasoning around it.
Notebook is the original, streamlined notebook interface, not JupyterLab. Jupyter.org labels JupyterLab as the next-generation interface with a flexible, configurable workspace. Teams choosing between them should consider whether a focused notebook document or a more configurable IDE fits their work. A local installation runs on the user's machine; a remotely hosted server has a separate operator and security model.
Strengths
- Code, narrative Markdown, mathematics, and rich computation output can be kept together in one notebook.
- The .ipynb document format is JSON and can be shared, version-controlled, or exported to static formats.
- The browser interface can connect to different language kernels rather than being limited to Python.
Watch out for
- Interactive execution requires a running Notebook server and an installed kernel for the language being used.
- A remote server's access controls and data handling depend on its operator; a local install and a hosted deployment are different operating models.
Best for
- Exploring data or prototyping code while keeping explanations and results beside each step
- Teaching or sharing computational work as a portable .ipynb document
Sources
- Project Jupyter | Home (Oct 26, 2026)
- The Jupyter Notebook — Jupyter Notebook 7.7.0a2 documentation (Oct 26, 2026)
- notebook/LICENSE at main · jupyter/notebook · GitHub (Oct 26, 2026)