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# 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