Installation

JupyterLab can be installed using conda, pip, pipenv or docker.

conda

If you use conda, you can install it with:

conda install -c conda-forge jupyterlab

pip

If you use pip, you can install it with:

pip install jupyterlab

If installing using pip install --user, you must add the user-level bin directory to your PATH environment variable in order to launch jupyter lab. If you are using a Unix derivative (FreeBSD, GNU / Linux, OS X), you can achieve this by using export PATH="$HOME/.local/bin:$PATH" command.

pipenv

If you use pipenv, you can install it as:

pipenv install jupyterlab
pipenv shell

or from a git checkout:

pipenv install git+git://github.com/jupyterlab/jupyterlab.git#egg=jupyterlab
pipenv shell

When using pipenv, in order to launch jupyter lab, you must activate the project’s virtualenv. For example, in the directory where pipenv’s Pipfile and Pipfile.lock live (i.e., where you ran the above commands):

pipenv shell
jupyter lab

Alternatively, you can run jupyter lab inside the virtualenv with

pipenv run jupyter lab

Docker

If you have Docker installed, you can install and use JupyterLab by selecting one of the many ready-to-run Docker images maintained by the Jupyter Team. Follow the instructions in the Quick Start Guide to deploy the chosen Docker image.

Ensure your docker command includes the -e JUPYTER_ENABLE_LAB=yes flag to ensure JupyterLab is enabled in your container.

Usage with JupyterHub

Read the details on our JupyterLab on JupyterHub documentation page.

Supported browsers

The latest versions of the following browsers are currently known to work:

  • Firefox

  • Chrome

  • Safari

Earlier browser versions may also work, but come with no guarantees.

JupyterLab uses CSS Variables for styling, which is one reason for the minimum versions listed above. IE 11+ or Edge 14 do not support CSS Variables, and are not directly supported at this time. A tool like postcss can be used to convert the CSS files in the jupyterlab/build directory manually if desired.

Usage with private NPM registry

To install some extensions, you will need access to an NPM packages registry. Some companies do not allow reaching directly public registry and have a private registry. To use it, you need to configure npm and yarn to point to that registry (ask your corporate IT department for the correct URL):

npm config set registry https://registry.company.com/
yarn config set registry https://registry.company.com/

JupyterLab will pick up that registry automatically. You can check which registry URL is used by JupyterLab by running:

python -c "from jupyterlab.commands import AppOptions; print(AppOptions().registry)"

Installation problems

If your computer is behind corporate proxy or firewall, you may encounter HTTP and SSL errors due to the proxy or firewall blocking connections to widely-used servers. For example, you might see this error if conda cannot connect to its own repositories:

CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://repo.anaconda.com/pkgs/main/win-64/current_repodata.json>

Here are some widely-used sites that host packages in the Python and JavaScript open-source ecosystems. Your network adminstrator may be able to allow http and https connections to these domains:

  • pypi.org

  • pythonhosted.org

  • continuum.io

  • anaconda.com

  • conda.io

  • github.com

  • githubusercontent.com

  • npmjs.com

  • yarnpkg.com

Alternatively, you can specify a proxy user (usually a domain user with password), that is allowed to communicate via network. This can be easily achieved by setting two common environment variables: HTTP_PROXY and HTTPS_PROXY. These variables are automatically used by many open-source tools (like conda) if set correctly.

# For Windows
set HTTP_PROXY=http://USER:PWD@proxy.company.com:PORT
set HTTPS_PROXY=https://USER:PWD@proxy.company.com:PORT

# For Linux / MacOS
export HTTP_PROXY=http://USER:PWD@proxy.company.com:PORT
export HTTPS_PROXY=https://USER:PWD@proxy.company.com:PORT

In case you can communicate via HTTP, but installation with conda fails on connectivity problems to HTTPS servers, you can disable using SSL for conda.

Warning

Disabling SSL in communication is generally not recommended and involves potential security risks.

# Configure npm to not use SSL
conda config --set ssl_verify False

You can do a similar thing for pip. The approach here is to mark repository servers as trusted hosts, which means SSL communication will not be required for downloading Python libraries.

# Install pandas (without SSL)
pip install --trusted-host pypi.org --trusted-host files.pythonhosted.org pandas

Using the tips from above, you can handle many network problems related to installing Python libraries.

Many Jupyter extensions require having working npm and jlpm (alias for yarn) commands, which is required for downloading useful Jupyter extensions or other JavaScript dependencies. If npm cannot connect to its own repositories, you might see an error like:

ValueError: "@jupyterlab/toc" is not a valid npm package

You can set the proxy or registry used for npm with the following commands.

# Set proxy for NPM
npm config set proxy http://USER:PWD@proxy.company.com:PORT
npm config set proxy https://USER:PWD@proxy.company.com:PORT

# Set default registry for NPM (optional, useful in case if common JavaScript libs cannot be found)
npm config set registry http://registry.npmjs.org/
jlpm config set registry https://registry.yarnpkg.com/

In case you can communicate via HTTP, but installation with npm fails on connectivity problems to HTTPS servers, you can disable using SSL for npm.

Warning

Disabling SSL in communication is generally not recommended and involves potential security risk.

# Configure npm to not use SSL
npm set strict-ssl False