# Introduction

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This documentation contains archived materials maintained for reference or record-keeping purposes. Some materials may not meet current accessibility standards. To learn more or to request an accessible version of archived content, please visit: [Digital Accessibility at Brown University](https://digital-accessibility.brown.edu/)
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Welcome to the Brown University JupyterHub Documentation & Quickstart Guide. The Brown JupyterHub is designed to provide an environment to run Jupyter Notebooks for Python, Julia, R, and other languages without the need to install any software or packages. JupyterHub is interacted with completely through a web browser. This service is a collaboration supported by various teams in CIS.

If you are an instructor looking to request a JupyterHub for your course or workshop, please visit this [link](https://ccv.brown.edu/services/classroom#computational-notebooks).

## How To Use This Guide

This document is designed to help instructors and students use their JupyterHub. This guide also provides extensive documentation on different [workflows](/archive-jupyterhub/workflows.md) used to **distribute** materials to the hub. Depending on a specific workflow, there are different sections of this documentation that are more relevant to you. To help you identified those sections, we make use of the following labels depending on your role and workflow

1. [**Determine your workflow**](/archive-jupyterhub/workflows.md)
2. Use labels as a guide to revelant sections\
   ① Basic usage guide ② Advanced usage guide\
   Ⓣ Teacher guide ***-***** Ⓢ** Student guide

## What Do You Get?

On the Brown JupyterHub, each user is provided their own persistent working directory and compute resource allocation unique from each other user. This means the environment you are provided is only accessible by yourself and CIS support staff.

Once connected to your server, you are provided an isolated workspace where you can write and run code. There are no time limit restrictions or specified lockout times, so please feel free to use your personal JupyterHub notebook server anytime you want and adhere to [CCV's Computing Policies](/archive-jupyterhub/computing-policy.md)


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# 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.ccv.brown.edu/archive-jupyterhub/readme.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.