General Codebase Orientation#

The jupyterlab repository is a monorepo: it contains code for many packages that are versioned and published independently.

In particular, there are many TypeScript packages and a single Python package. The Python package contains server-side code, and also distributes the bundled-and-compiled TypeScript code.

See the Contributing Guidelines for detailed developer installation instructions.


The repository contains a number of top-level directories, the contents of which are described here.

Python package: jupyterlab/#

This, along with the pyproject.toml, comprises the Python code for the project. This includes the notebook server extension, JupyterLab’s command line interface, entrypoints, and Python tests.

It also contains the final built JavaScript assets which are distributed with the Python package.

NPM packages: packages/#

This contains the many TypeScript sub-packages which are independently versioned and published to These are compiled to JavaScript and bundled with the Python package.

The bulk of JupyterLab’s codebase resides in these packages. A common pattern for the various components in JupyterLab is to have one package that implements the component, and a second package postfixed with -extension that integrates that component with the rest of the application. Inspection of the contents of this directory shows many such packages.

You can build these packages by running jlpm build:packages.

Binder setup: binder/#

This contains an environment specification for repo2docker which allows the repository to be tested on This specification is developer focused. For a more user-focused binder see the JupyterLab demo The binder instance adds two endpoints in addition to /lab: /lab-dev and /lab-spliced. The lab-dev endpoint is the equivalent of checking out the repo locally and running jupyter lab --dev-mode. The lab-spliced endpoint is the equivalent of building JupyterLab in spliced mode and running jupyter lab. See the Development workflow for source extensions for more information on spliced mode.

Build utilities: buildutils/#

An npm package that contains several utility scripts for managing the JupyterLab build process.

You can build this package by running jlpm build:utils.

Design: design/#

A directory containing a series of design documents motivating various choices made in the course of building JupyterLab.

Development-Mode: dev_mode/#

An application directory containing built JavaScript assets which are used when developing the TypeScript sources. If you are running JupyterLab in dev-mode, you are serving the application out of this directory.

Documentation: docs/#

This directory contains the Sphinx project for this documentation. You can install the dependencies for building the documentation using pip install .[docs], and you can build the documentation by running make html. The entry point to the built docs will then be in docs/build/index.html.

Examples: examples/#

The examples/ directory contains stand-alone examples of components, such as a simple notebook on a page, a console, terminal, and a file browser. The app example illustrates a simplified combination of several of the components used in JupyterLab.

Jupyter Server Configuration: jupyter-config/#

This directory contains metadata distributed with the Python package that allows it to automatically enable the Jupyter server extension upon installation.

Utility Scripts: scripts/#

This directory contains a series of utility scripts which are primarily used in continuous integration testing for JupyterLab.

Testing: tests/#

Tests for the TypeScript packages in the packages/ directory. These test directories are themselves small npm packages which pull in the TypeScript sources and exercise their APIs.

Test Utilities: testutils/#

A small npm package which is aids in running the tests in tests/.