The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more.

JupyterHub is the best way to serve Jupyter notebook for multiple users. It can be used in a classes of students, a corporate data science group or scientific research group. It is a multi-user Hub that spawns, manages, and proxies multiple instances of the single-user Jupyter notebook server.

Guix-Jupyter is a Jupyter kernel. It allows you to annotate notebooks with information about their software dependencies, such that code is executed in the right software environment. Guix-Jupyter spawns the actual kernels such as python-ipykernel on behalf of the notebook user and runs them in an isolated environment, in separate namespaces.

This package provides an Emacs interface to communicate with Jupyter kernels. It provides REPL and Org mode source code block frontends to Jupyter kernels and kernel interactions integrated with Emacs' built-in features.

JupyterHub: A multi-user server for Jupyter notebooks

An extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture.

This package provides an Emacs interface to communicate with Jupyter kernels. It provides REPL and Org mode source code block frontends to Jupyter kernels and kernel interactions integrated with Emacs' built-in features.

The package provides a PARI/GP kernel for Jupyter.

Jupyter core is the base package on which Jupyter projects rely.

This package provides a Guile 2.x kernel for the Jupyter Notebook. It allows users to interact with the Guile REPL through Jupyter.

This package provides a pytest plugin for testing Jupyter libraries and extensions.

The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications.

This package provides the backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications.

Jupyter Events enables Jupyter Python Applications (e.g. Jupyter Server, JupyterLab Server, JupyterHub, etc.) to emit events—structured data describing things happening inside the application. Other software (e.g. client applications like JupyterLab) can listen and respond to these events.

The jupyter_client package contains the reference implementation of the Jupyter protocol. It also provides client and kernel management APIs for working with kernels, and the jupyter kernelspec entrypoint for installing kernelspecs for use with Jupyter frontends.

Jupyter-sphinx is a Sphinx extension that executes embedded code in a Jupyter kernel, and embeds outputs of that code in the document. It has support for rich output such as images, LaTeX math and even JavaScript widgets, and supports thebelab for live code execution with minimal effort.

This is a Common Lisp kernel for Jupyter along with a library for building Jupyter kernels, based on Maxima-Jupyter which was based on cl-jupyter.

This package provides a terminal-based console frontend for Jupyter kernels. It also allows for console-based interaction with non-Python Jupyter kernels such as IJulia and IRKernel.

The jupyterlite-core package provides the core functionality for building JupyterLite websites, the jupyter-lite CLI, and extension points for authoring custom addons.

This is a Common Lisp kernel for Jupyter along with a library for building Jupyter kernels, based on Maxima-Jupyter which was based on cl-jupyter.

This Python library is an experimental implementation of the Jupyter protocol to be used by both clients and kernels.

The Littlest JupyterHub (TLJH) distribution helps you provide Jupyter Notebooks to 1-50 users on a single server. Administrators who do not consider themselves 'system administrators' but would like to provide hosted Jupyter Notebooks for their students / users are the primary audience. All users are provided with the same environment, and administrators can easily install libraries into this environment without any specialized knowledge.

Jupyter telemetry library

This package provides tools to help build and install Jupyter Python packages that require a pre-build step that may include JavaScript build steps.