Extended IPA Symbols Backend

This project provides a backend service for the Extended IPA Symbols application. The backend handles data storage, audio file serving, and manages extended phoneme data.

Features

• RESTful API for phoneme data
• Extended IPA symbols support
• Audio file serving
• Proposal system for new symbols
• Discussion forum
• Database support (SQLite or PostgreSQL)

Prerequisites

• Python 3.9+
• pip (Python package manager)
• Optional: Docker and Docker Compose for containerized deployment

Quick Start

Using the start script

The easiest way to get started is using the provided start script:

# Make the script executable
chmod +x start.sh

# Run the script
./start.sh

The script will:

1. Check for and create required directories
2. Set up a Python virtual environment
3. Install dependencies
4. Initialize the database
5. Start the FastAPI server

Manual Setup

If you prefer to set up manually:

# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# On Windows:
venv\Scripts\activate
# On Unix or MacOS:
source venv/bin/activate

# Install dependencies
pip install -r backend/requirements.txt

# Initialize the database
python -m backend.scripts.init_db

# Start the server
cd backend
uvicorn app.main:app --reload

Using Docker Compose

# Start all services
docker-compose up -d

# View logs
docker-compose logs -f

Project Structure

my_extended_ipa_symbols/
├── backend/                      # Python FastAPI server
│   ├── app/
│   │   ├── __init__.py
│   │   ├── main.py               # FastAPI application entry point
│   │   ├── models/               # Database models
│   │   ├── routers/              # API route handlers
│   │   ├── schemas/              # Pydantic models for validation
│   │   ├── services/             # Business logic
│   │   └── database.py           # Database connection
│   ├── audio_files/              # Storage for audio files
│   ├── scripts/                  # Utility scripts
│   ├── requirements.txt          # Dependencies
│   └── Dockerfile                # For containerization
└── docker-compose.yml            # For local development

API Endpoints

Language Endpoints

• GET /api/languages - List all languages
• GET /api/languages/{lang_code} - Get specific language details

Phoneme Endpoints

• GET /api/languages/{lang_code}/phonemes - Get all phonemes for a language
• GET /api/languages/{lang_code}/phonemes/{phoneme_id} - Get specific phoneme
• GET /api/languages/{lang_code}/phonemic - Get phonetic view data
• GET /api/languages/{lang_code}/extended-phonemes - Get only extended IPA phonemes
• GET /api/languages/{lang_code}/impossible-phonemes - Get impossible phonemes
• GET /api/phonemes/categories - Get phoneme categories

Audio Endpoints

• GET /api/audio/{lang_code}/{filename} - Serve audio file

Additional Endpoints

If you've implemented the extended features:

• GET/POST /api/proposals - Symbol proposals system
• GET/POST /api/discussions - Discussion forum
• GET /api/notifications - Notification system

Data Import

To import extended IPA data:

# Extract data from HTML
python -m backend.scripts.extract_extended_phonemes

# Import to database
python -m backend.scripts.import_extended_ipa

Development

Adding New Models

1. Create a new model file in app/models/
2. Create a corresponding schema file in app/schemas/
3. Create a router in app/routers/
4. Include the router in app.main:app

Running Tests

# Run tests
pytest

Deployment Options

VPS/Cloud Service

• Deploy on AWS EC2, DigitalOcean Droplet, or similar
• Use Docker for containerization
• Set up a PostgreSQL database for production
• Configure Nginx as a reverse proxy

Platform as a Service

• Deploy the backend on Heroku, Render, or Railway
• Use their PostgreSQL add-ons
• Store audio files on AWS S3 or similar storage service

Serverless

• Convert backend to AWS Lambda functions with API Gateway
• Use a service like DynamoDB for data storage
• Store audio files in S3

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.