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https://github.com/mshaaban0/pixi-docker-template
A Python project boilerplate template for new projects with Pixi, Flask, Jupyter Notebook and Docker Compose.
https://github.com/mshaaban0/pixi-docker-template
docker jupyter-notebook pixi python qdrant
Last synced: 4 days ago
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A Python project boilerplate template for new projects with Pixi, Flask, Jupyter Notebook and Docker Compose.
- Host: GitHub
- URL: https://github.com/mshaaban0/pixi-docker-template
- Owner: mshaaban0
- License: mit
- Created: 2024-08-09T21:25:01.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-08-12T12:41:56.000Z (6 months ago)
- Last Synced: 2024-11-27T20:44:07.044Z (2 months ago)
- Topics: docker, jupyter-notebook, pixi, python, qdrant
- Language: Jupyter Notebook
- Homepage:
- Size: 38.1 KB
- Stars: 6
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Python Project Boilerplate with Pixi, Flask, Jupyter Notebook, and Docker Compose
This repository provides a boilerplate for new Python projects using Pixi for dependency management and Docker Compose for containerization. It includes a basic Flask application connected to a Qdrant vector database, as well as Jupyter Notebook for interactive development and data exploration.
## Features
- Python project structure with Pixi for dependency management
- Docker Compose setup for easy development and deployment
- Flask web application with hot-reloading for rapid development
- Qdrant vector database integration
- Watchdog for efficient file change detection in Docker
- Jupyter Notebook for interactive development and data analysis
## Prerequisites
Before you begin, ensure you have the following installed on your system:
- [Docker](https://www.docker.com/get-started)
- [Docker Compose](https://docs.docker.com/compose/install/)
- [Pixi](https://github.com/prefix-dev/pixi) (Optional: for local development without Docker)
## Getting Started
### Clone the Repository
```bash
git clone [email protected]:mshaaban0/pixi-docker-template.git
cd pixi-docker-template
```
### Running with Docker Compose
1. Build and start the containers:
```bash
docker compose up --build
```
2. Access the Flask application at `http://localhost:5001`
3. Access Jupyter Notebook at `http://localhost:9999` (token is in the terminal output)
4. Qdrant Dashboard at `http://localhost:6333/dashboard`
5. To stop the containers, press `Ctrl+C` in the terminal or run:
```bash
docker compose down
```
### Local Development with Pixi (Optional)
1. Install dependencies:
```bash
pixi install
```
2. Run the Flask application:
```bash
pixi run start
```
3. Run Jupyter Notebook:
```bash
pixi run jupyter
```
4. Access the Flask application at `http://localhost:5001`
5. Access Jupyter Notebook at `http://localhost:9999`
## Project Structure
```
.
├── .dockerignore
├── .gitignore
├── docker-compose.yml
├── Dockerfile
├── pixi.toml
├── README.md
├── src
│ └── main.py
└── notebooks
└── example.ipynb
```
## Configuration
- `pixi.toml`: Manages Python dependencies and project metadata
- `Dockerfile`: Defines the Docker image for the Python application
- `docker-compose.yml`: Orchestrates the application, Qdrant services, and Jupyter Notebook
- `src/main.py`: Entry point for the Flask application
- `notebooks/`: Directory for Jupyter notebooks
## Development
The project is set up with hot-reloading, allowing you to see changes immediately without restarting the container. Simply edit the files in the `src` directory, and the application will reload automatically.
For data analysis and exploratory work, use Jupyter Notebook. You can create new notebooks in the `notebooks/` directory, which will be persisted even after stopping the Docker containers.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Acknowledgments
- [Pixi](https://github.com/prefix-dev/pixi) for dependency management
- [Flask](https://flask.palletsprojects.com/) for the web framework
- [Qdrant](https://qdrant.tech/) for vector similarity search
- [Docker](https://www.docker.com/) for containerization
- [Jupyter](https://jupyter.org/) for interactive computing