Metadata-Version: 2.4
Name: jps-controlled-vocabularies-rest-api
Version: 0.1.0
Summary: A lightweight REST service that exposes controlled vocabularies and terms over HTTP for programmatic retrieval and validation.
Author-email: Jaideep Sundaram <jai.python3@gmail.com>
License: MIT
Project-URL: Homepage, https://github.com/jai-python3/jps-controlled-vocabularies-rest-api
Project-URL: Repository, https://github.com/jai-python3/jps-controlled-vocabularies-rest-api
Project-URL: Issues, https://github.com/jai-python3/jps-controlled-vocabularies-rest-api/issues
Keywords: cookiecutter,bootstrap,project-generator,automation
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: typer>=0.12.3
Requires-Dist: fastapi>=0.115.0
Requires-Dist: uvicorn[standard]>=0.32.0
Requires-Dist: pydantic>=2.9.0
Requires-Dist: pydantic-settings>=2.6.0
Requires-Dist: pyyaml>=6.0.2
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Provides-Extra: test
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Dynamic: license-file

# jps-controlled-vocabularies-rest-api

![Build](https://github.com/jai-python3/jps-controlled-vocabularies-rest-api/actions/workflows/test.yml/badge.svg)
![Publish to PyPI](https://github.com/jai-python3/jps-controlled-vocabularies-rest-api/actions/workflows/publish-to-pypi.yml/badge.svg)
[![codecov](https://codecov.io/gh/jai-python3/jps-controlled-vocabularies-rest-api/branch/main/graph/badge.svg)](https://codecov.io/gh/jai-python3/jps-controlled-vocabularies-rest-api)

A lightweight REST service that exposes controlled vocabularies and terms over HTTP for programmatic retrieval and validation.

## 🚀 Overview

`jps-controlled-vocabularies-rest-api` is a FastAPI-based REST service designed to provide programmatic access to controlled vocabularies and terminology. It serves as a stable API layer for consuming vocabulary data from various backend sources including YAML files and PostgreSQL databases.

### Key Features

- **RESTful API** - Clean, well-documented endpoints for vocabulary and term operations
- **Pluggable Backends** - Support for YAML files (built-in) and PostgreSQL (via plugin)
- **Search & Validation** - Full-text search across terms and value validation capabilities
- **OpenAPI Documentation** - Automatic Swagger UI and ReDoc documentation
- **Container-Ready** - Docker and docker-compose configurations included
- **Type-Safe** - Full type hints with Pydantic models
- **Production-Ready** - Health checks, structured logging, and graceful error handling

### Use Cases

1. **Frontend Integration** - Provide drop-down values and definitions for UI components
2. **Service Integration** - Enable backend services to validate terminology consistently
3. **Data Validation** - ETL pipelines can validate data against controlled vocabularies
4. **CI/CD Validation** - Ensure vocabulary definitions are valid before deployment

### Architecture

```
┌─────────────────┐
│   FastAPI App   │
│   (Routers)     │
└────────┬────────┘
         │
         ▼
┌────────────────────┐
│  VocabularyStore   │
│   (Abstraction)    │
└────────┬───────────┘
         │
    ┌────┴─────┐
    ▼          ▼
┌─────────┐  ┌──────────────┐
│ YAML    │  │ PostgreSQL   │
│ Store   │  │ Store        │
│ (Built) │  │ (Plugin)     │
└─────────┘  └──────────────┘
```

## 📦 Installation

### Option 1: Install from PyPI (coming soon)

```bash
pip install jps-controlled-vocabularies-rest-api
```

### Option 2: Install from Source

```bash
git clone https://github.com/jai-python3/jps-controlled-vocabularies-rest-api.git
cd jps-controlled-vocabularies-rest-api
pip install -e .
```

### Option 3: Using Docker

```bash
docker-compose up -d
```

## 🚀 Quick Start

### 1. Configure Environment

```bash
cp .env.example .env
# Edit .env with your configuration
```

Minimal configuration for YAML backend:
```bash
VOCAB_BACKEND=yaml
VOCAB_YAML_PATH=./vocabularies
```

### 2. Prepare Vocabulary Files

Place your YAML vocabulary files in the `vocabularies/` directory:

```yaml
# vocabularies/my_vocab.yaml
vocabulary_id: my_vocabulary
schema_version: "1.0"
title: My Vocabulary
description: Example vocabulary

terms:
  - key: term1
    name: Term One
    description: First term
    metadata:
      allowed_values: ["value1", "value2", "value3"]
```

### 3. Run the Service

#### Using Python directly:
```bash
python -m jps_controlled_vocabularies_rest_api.main
```

#### Using Uvicorn:
```bash
uvicorn jps_controlled_vocabularies_rest_api.main:app --host 0.0.0.0 --port 8000
```

#### Using Docker:
```bash
docker-compose up
```

### 4. Access the API

- **API Base**: http://localhost:8000
- **Swagger UI**: http://localhost:8000/docs
- **ReDoc**: http://localhost:8000/redoc
- **OpenAPI Spec**: http://localhost:8000/openapi.json

## 📚 API Endpoints

### Health & Readiness

- `GET /healthz` - Simple health check
- `GET /readyz` - Detailed readiness check with backend status

### Vocabularies

- `GET /v1/vocabularies` - List all vocabularies
- `GET /v1/vocabularies/{vocabulary_id}` - Get vocabulary details
- `GET /v1/vocabularies/{vocabulary_id}/terms` - List terms (with pagination)
- `GET /v1/vocabularies/{vocabulary_id}/terms/{term_key}` - Get specific term

### Search

- `GET /v1/search?q={query}` - Search terms across vocabularies
  - Optional: `vocabulary_id` - Filter by vocabulary
  - Optional: `limit`, `offset` - Pagination

### Validation

- `POST /v1/validate/value` - Validate a value against a term
- `POST /v1/validate/registry` - Validate the entire registry

## 💡 Example Usage

### List Vocabularies

```bash
curl http://localhost:8000/v1/vocabularies
```

Response:
```json
[
  {
    "vocabulary_id": "workflow.system_terminology",
    "schema_version": "1.0",
    "title": "Workflow and System Terminology",
    "description": "Core terms used across JPSHealth EHR workflow services",
    "term_count": 4
  }
]
```

### Get Vocabulary Details

```bash
curl http://localhost:8000/v1/vocabularies/workflow.system_terminology
```

### Search Terms

```bash
curl "http://localhost:8000/v1/search?q=ready"
```

### Validate a Value

```bash
curl -X POST http://localhost:8000/v1/validate/value \
  -H "Content-Type: application/json" \
  -d '{
    "vocabulary_id": "workflow.system_terminology",
    "term_key": "readiness_status",
    "value": "Almost Ready"
  }'
```

Response:
```json
{
  "is_valid": true,
  "normalized_value": "Almost Ready",
  "reasons": ["Value is in the list of allowed values"],
  "allowed_values": ["Ready", "Almost Ready", "Not Ready"],
  "pattern": null
}
```

## ⚙️ Configuration

### Environment Variables

| Variable | Default | Description |
|----------|---------|-------------|
| `VOCAB_BACKEND` | `yaml` | Backend type: `yaml` or `postgres` |
| `VOCAB_YAML_PATH` | - | Path to YAML file or directory (required for yaml backend) |
| `VOCAB_YAML_RELOAD` | `false` | Enable hot-reload of YAML vocabularies |
| `VOCAB_SEARCH_CASE_SENSITIVE` | `false` | Case-sensitive search |
| `UVICORN_HOST` | `0.0.0.0` | Server host |
| `UVICORN_PORT` | `8000` | Server port |
| `POSTGRES_DSN` | - | PostgreSQL connection string (for postgres backend) |
| `CORS_ALLOW_ORIGINS` | - | Comma-separated list of allowed CORS origins |
| `LOG_REQUEST_BODIES` | `false` | Enable request body logging |

### PostgreSQL Backend

To use PostgreSQL backend (requires plugin):

1. Install the plugin:
```bash
pip install jps-controlled-vocabularies-postgresql
```

2. Configure environment:
```bash
VOCAB_BACKEND=postgres
POSTGRES_DSN=postgresql://user:pass@localhost:5432/dbname
```

## 🧪 Development

### Setup Development Environment

```bash
# Install with dev dependencies
make install

# Or manually
pip install -e ".[dev]"
```

### Run Tests

```bash
# Run all tests
make test

# Run with coverage
pytest --cov=src --cov-report=html

# Run specific test file
pytest tests/test_health.py
```

### Code Quality

```bash
# Format code
make format

# Run linters
make lint

# Fix auto-fixable issues
make fix

# Type checking
mypy src/
```

### Pre-commit Hooks

```bash
pre-commit install
pre-commit run --all-files
```

## 🐳 Docker Deployment

### Build Image

```bash
docker build -t jps-vocab-api:latest .
```

### Run Container

```bash
docker run -d \
  -p 8000:8000 \
  -e VOCAB_BACKEND=yaml \
  -e VOCAB_YAML_PATH=/app/vocabularies \
  -v $(pwd)/vocabularies:/app/vocabularies:ro \
  --name jps-vocab-api \
  jps-vocab-api:latest
```

### Using Docker Compose

```bash
docker-compose up -d
docker-compose logs -f
docker-compose down
```

## 📖 Documentation

- [Software Requirements Specification (SRS)](SRS.md)
- [Development SOP](docs/Development_SOP.md)
- [Release SOP](docs/Release_SOP.md)

## 🤝 Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Make your changes
4. Run tests and linters (`make test && make lint`)
5. Commit your changes (`git commit -m 'Add amazing feature'`)
6. Push to the branch (`git push origin feature/amazing-feature`)
7. Open a Pull Request

## 📝 Changelog

See [CHANGELOG.md](CHANGELOG.md) for release history.

## 📜 License

MIT License © Jaideep Sundaram

See [LICENSE](LICENSE) for details.

## 🔗 Related Projects

- `jps-controlled-vocabularies-utils` - Core vocabulary utilities
- `jps-controlled-vocabularies-postgresql` - PostgreSQL backend plugin

## 📧 Contact

Jaideep Sundaram - jai.python3@gmail.com

Project Link: https://github.com/jai-python3/jps-controlled-vocabularies-rest-api

