Installation
============

Installation
------------

JupyDeep is available on PyPI and can be installed via pip (including within uv or conda environments). 

``uv`` installation
~~~~~~~~~~~~~~~~~~~

Using ``uv`` as an example, we can set up a project in a new directory named ``tutorial``. 

Ensure you have ``uv`` is installed. If not, please refer to the `uv installation guide <https://docs.astral.sh/uv/getting-started/installation/>`_.

.. code-block:: console

   $ cd tutorial
   $ uv init
   $ uv add jupyterlab jupydeep "jupyter-mcp-server @ git+https://github.com/yezhenqing/jupyter-mcp-server.git"


Then simply launch JupyterLab as below:

.. code-block:: console

   $ uv run jupyter lab --ip=0.0.0.0

The JupyterLab main panel should now display the JupyDeep icon in the right sidebar.


``conda`` installation
~~~~~~~~~~~~~~~~~~~~~~

For ``conda``, you can create a new environment and then install JupyDeep using ``pip`` inside it.

.. code-block:: console

   $ conda create -n jupydeep jupyterlab
   $ conda activate jupydeep
   $ (jupydeep) pip install "jupyter-mcp-server @ git+https://github.com/yezhenqing/jupyter-mcp-server.git" jupydeep


.. note::

   The original ``jupyter-mcp-server`` rely on ``jupyter-server-nbmodel``, which suffers from several known issues. 
   In particular, `Issue #65 <https://github.com/datalayer/jupyter-server-nbmodel/issues/65>`_ prevents notebooks from executing smoothly.

In both ``uv`` and ``conda``, you can install any additional packages you need (such as ``seaborn`` for data analysis).