The Jupyter Notebook is an interactive computing environment that enables users to author notebook documents that include:
These documents provide a complete and self-contained record of a computation that can be converted to various formats and shared with others using email, Dropbox, version control systems (like git/GitHub) or nbviewer.jupyter.org.
The Jupyter Notebook combines three components:
The notebook web application enables users to:
Through Jupyter's kernel and messaging architecture, the Notebook allows code to be run in a range of different programming languages. For each notebook document that a user opens, the web application starts a kernel that runs the code for that notebook. Each kernel is capable of running code in a single programming language and there are kernels available in the following languages:
The default kernel runs Python code. The notebook provides a simple way for users to pick which of these kernels is used for a given notebook.
Each of these kernels communicate with the notebook web application and web browser using a JSON over ZeroMQ/WebSockets message protocol that is described here. Most users don't need to know about these details, but it helps to understand that "kernels run code."
Notebook documents contain the inputs and outputs of an interactive session as well as narrative text that accompanies the code but is not meant for execution. Rich output generated by running code, including HTML, images, video, and plots, is embeddeed in the notebook, which makes it a complete and self-contained record of a computation.
When you run the notebook web application on your computer, notebook documents are just files on your local filesystem with a
.ipynb extension. This allows you to use familiar workflows for organizing your notebooks into folders and sharing them with others.
Notebooks consist of a linear sequence of cells. There are three basic cell types:
Internally, notebook documents are JSON data with binary values base64 encoded. This allows them to be read and manipulated programmatically by any programming language. Because JSON is a text format, notebook documents are version control friendly.
Notebooks can be exported to different static formats including HTML, reStructeredText, LaTeX, PDF, and slide shows (reveal.js) using Jupyter's
Furthermore, any notebook document available from a public URL or on GitHub can be shared via nbviewer. This service loads the notebook document from the URL and renders it as a static web page. The resulting web page may thus be shared with others without their needing to install the Jupyter Notebook.