# Using HEAVY.AI with JupyterLab

{% tabs %}
{% tab title="HEAVY.AI Enterprise Edition" %}
HEAVY.AI Enterprise Edition comes with a fully integrated version of [JupyterHub](https://jupyter.org/hub). This provides a secure, multi-user notebook environment for data exploration with OmniSci, and is the primary user interface for the HEAVY.AI Data Science Foundation.

You can quickly switch from visual data exploration, to a Data Science environment preloaded with useful open source libraries and tools that work with OmniSci transparently.

You can access [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/), the next generation Jupyter notebook UI from within Immerse via a button located on the dashboard title

![](/files/uic9GXrX76FWTOZGDeps)

In addition, you can also launch JupyterLab from SQL Editor. In this case, a notebook is opened up with the query wrapped in an Ibis expression.

![](/files/hzYSk7bBTamFj8bvb70X)

{% hint style="info" %}
HEAVY.AI Enterprise allows you to control which users have access to JupyterLab and Data Science tools. This is managed as a separate privilege under the HEAVY.AI role-based permissions model. Refer to the [installation](/v8.3.0/python-data-science/get-started-jupyter.md) instructions for how to set this up for specific users
{% endhint %}
{% endtab %}

{% tab title="HEAVY.AI Open Source Edition" %}
If you are an HEAVY.AI open source edition user, you do not have access to HeavyImmerse, but you can still explore HEAVY.AI with the Data Science Foundation tools.

{% hint style="info" %}
Using JupyterLab with HEAVY.AI Open Source Edition requires you to connect to HEAVY.AI explicitly from within a Jupyter notebook cell, using [Ibis](/v8.3.0/python-data-science/introduction-to-ibis.md) or [py](https://github.com/omnisci/docs-internal/tree/7ca9a3f8fbca75498ccfec3bba1ada3eb88f2fe4/apis-and-interfaces/pyomnisci.md)[mapd](https://github.com/omnisci/docs-internal/tree/7ca9a3f8fbca75498ccfec3bba1ada3eb88f2fe4/apis-and-interfaces/pyomnisci.md) connection syntax. Refer to the [Ibis](/v8.3.0/python-data-science/introduction-to-ibis.md) or pyomnisci examples for more details.
{% endhint %}

#### Using the Anaconda Package Manager

If you are using the Anaconda package manager, you can install the set of Python tools for HEAVY.AI:

```
conda install -c conda-forge omnisci-pytools
```

#### Using the HEAVY.AI Docker Container for Jupyter tools

You can download a prebuilt Docker container and simply start up these tools as a standalone container.
{% endtab %}
{% endtabs %}

## Tools and Utilities

HEAVY.AI provides a collection utilities to work with JupyterLab.

This is a collection of useful functions and Jupyter cell magics that allows running commands that are typically possible from [heavysql](/v8.3.0/apis-and-interfaces/heavysql.md) from inside a notebook environment.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.heavy.ai/v8.3.0/python-data-science/using-omnisci-with-jupyterlab.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.