# Jupyter Notebook Docker Setup

This repository contains Docker configuration for running Jupyter Notebook with various data science libraries pre-installed.

## Features

- Based on Ubuntu Focal (20.04)
- Includes Jupyter Notebook with:
  - Pandas
  - OpenCV
  - Scikit-learn
  - Scikit-image
  - PyTorch
  - Imutils
  - Notebook export capabilities (nbconvert)
- Volume mounted for persistent notebook storage
- Two deployment profiles (build locally or pull from registry)

## Directory Structure

```
.
├── Dockerfile          # Docker image definition
├── docker-compose.yml  # Services configuration
├── requirements.txt    # Python package dependencies
└── notebooks/          # Directory for your Jupyter notebooks (will be created)
```

## Usage

### Create notebooks directory

```bash
mkdir -p notebooks
```

### Profile 1: Build locally

To build the Docker image locally and run the container:

```bash
docker-compose --profile build up
```

### Profile 2: Pull from your registry

To pull the image from your private registry and run it:

```bash
REGISTRY_URL=your-registry-url docker-compose --profile registry up
```

Replace `your-registry-url` with your actual Docker registry URL.

## Accessing Jupyter Notebook

Once the container is running, access Jupyter Notebook by opening a browser and navigating to:

```
http://localhost:8888
```

No password is required (for simplicity - you may want to add authentication for production use).

## Customization

- To add more Python packages, modify the `pip3 install` command in the Dockerfile
- To change the Jupyter configuration, modify the command in docker-compose.yml

## Notes

- The notebooks directory is mounted as a volume to persist your work
- For security in production environments, consider adding authentication to your Jupyter instance