.. Copyright (c) Jupyter Development Team. .. Distributed under the terms of the Modified BSD License. .. _installation: Installation ============ JupyterLab can be installed using ``conda``, ``mamba``, ``pip``, ``pipenv`` or ``docker``. .. warning:: New versions of JupyterLab may break backwards compatibility with extensions and other Jupyter customizations. As noted in :ref:`versioning_notes`, JupyterLab development and release cycles follow semantic versioning, so we recommend planning your installation and upgrade procedures to account for possible breaking changes that may disrupt your usage of JupyterLab and any related tools that are critical to your workflows. conda ----- If you use ``conda``, you can install it with: .. code:: bash conda install -c conda-forge jupyterlab mamba ----- If you use ``mamba``, you can install it with: .. code:: bash mamba install -c conda-forge jupyterlab pip --- If you use ``pip``, you can install it with: .. code:: bash pip install jupyterlab If you are using a macOS version that comes with Python 2, run ``pip3`` instead of ``pip``. 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, macOS), you can do this by running ``export PATH="$HOME/.local/bin:$PATH"``. pipenv ------ If you use ``pipenv``, you can install it as: .. code:: bash pipenv install jupyterlab pipenv shell or from a git checkout: .. code:: bash 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): .. code:: bash pipenv shell jupyter lab Alternatively, you can run ``jupyter lab`` inside the virtualenv with .. code:: bash 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 :ref:`JupyterLab on JupyterHub documentation page `. Supported browsers ------------------ The latest versions of the following browsers are currently known to work: - Firefox - Chrome - Safari - Edge Earlier browser versions may also work, but come with no guarantees. 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 Here are some widely-used sites that host packages in the Python and JavaScript open-source ecosystems. Your network administrator 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. .. code:: bash # 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. .. code:: bash # 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. .. code:: bash # 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. .. code:: bash # 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 npmRegistryServer 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. .. code:: bash # Configure npm to not use SSL npm set strict-ssl False