JupyterLab Server sits between JupyterLab and Jupyter Server, and provides a set of REST API handlers and utilities that are used by JupyterLab. It is a separate project in order to accommodate creating JupyterLab-like applications from a more limited scope.

xeus is a library meant to facilitate the implementation of kernels for Jupyter. It takes the burden of implementing the Jupyter Kernel protocol so developers can focus on implementing the interpreter part of the kernel.

Several Jupyter kernels are built upon xeus, such as xeus-cling, a kernel for the C++ programming language, and xeus-python, an alternative Python kernel for Jupyter.

This package provides the IPython kernel for Jupyter.

repo2docker fetches a repository (from GitHub, GitLab, Zenodo, Figshare, Dataverse installations, a Git repository or a local directory) and builds a container image in which the code can be executed. The image build process is based on the configuration files found in the repository. repo2docker can be used to explore a repository locally by building and executing the constructed image of the repository, or as a means of building images that are pushed to a Docker registry.

This package provides Jupyter kernels for use with the consoles of Spyder, the Scientific Python Development Environment.

These kernels can be launched either through Spyder itself or in an independent Python session, and allow for interactive or file-based execution of Python code inside Spyder.

This package opens a notebook, strips its output, and writes the outputless version to the original file.

This package provides python-pycrdt-based data structures for various documents used in the Jupyter ecosystem. Built-in documents include:

• YBlob: a generic immutable binary document.

• YUnicode: a generic UTF8-encoded text document (YFile is an alias).

• YNotebook: a Jupyter notebook document.

This package provides a Model Context Protocol server for jupyter, bridging LLMs and Jupyter Notebooks.

This package provides the IPython kernel for Jupyter.

Voilà turns Jupyter notebooks into standalone web applications. Unlike the usual HTML-converted notebooks, each user connecting to the Voilà tornado application gets a dedicated Jupyter kernel which can execute the callbacks to changes in Jupyter interactive widgets.

This package provides a Jupyter Server extension for serving Mathjax, the JavaScript display engine for mathematics.

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

This package provides a Python library to interact with Jupyter Server REST API for server management operations. It provides server-level functionality including kernel listing (read-only) while avoiding duplication with existing kernel management libraries.

This package Python provides enhanced Jupyter representation capabilities through proxy objects, enabling efficient Apache Arrow-based serialization for pandas DataFrames/Series and pickle-based serialization for generic Python objects in Jupyter environments.

ipywidgets, also known as jupyter-widgets or simply widgets, are interactive HTML widgets for Jupyter notebooks and the IPython kernel.

This package provides a set of widgets to help facilitate reuse of large datasets across widgets.

Papermill is a tool for parameterizing, executing, and analyzing Jupyter Notebooks.

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

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.

This package provides the IPython kernel for Jupyter.

This package contains a syntax coloring theme for pygments making use of the JupyterLab CSS variables.

This package provides a Jupyter Server extension providing terminals.

This package provides a Qt-based console for Jupyter with support for rich media output.

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.