A production-ready Flask API framework with built-in storage, authentication, and AI capabilities. Designed for developers who need a robust foundation for building scalable APIs while following best practices.
- SQLModel + Pydantic for type-safe database operations
- Comprehensive validation with detailed error messages
- Clear separation between core and custom components
- Standardized response formats
- JWT token-based authentication
- API key management with scoping
- Role-based access control (RBAC)
- Request validation and sanitization
- Hash-based secure storage
- On-demand request/response storage
- Session-based data organization
- Compression for large payloads
- TTL-based expiration
- Flexible querying with metadata filters
- Provider-agnostic interface
- Response validation
- Automatic retry mechanisms
- Error handling with fallbacks
- OpenAPI/Swagger documentation
- Remote debugging support
- Environment-based configuration
- Comprehensive error handling
- Warning collection system
# Install the core package
pip install flask-structured-api
# Create new project
mkdir my-api && cd my-api
# Initialize basic structure
flask-api init
# Install dependencies
pip install -r requirements.txt
Note: When using the PyPI package, you'll need to set up your own PostgreSQL and Redis services.
For a fresh start with full Docker support:
# Create and enter project directory
mkdir my-api && cd my-api
# Initialize empty git repo
git init
# Add boilerplate as remote
git remote add boilerplate https://github.com/julianfleck/flask-structured-api.git
# Pull files without history
git pull boilerplate main --allow-unrelated-histories
# Make initial commit
git add .
git commit -m "Initial commit from boilerplate"
# Start services
docker-compose up -d
If you want to preserve boilerplate history (not recommended for production):
# Clone the repo
git clone https://github.com/julianfleck/flask-structured-api.git my-api
cd my-api
# Start services
docker-compose up -d
Essential environment variables:
# Required
FLASK_APP=flask_structured_api.main:app
DATABASE_URL=postgresql://user:password@localhost:5432/dbname
REDIS_URL=redis://localhost:6379/0
SECRET_KEY=your-secret-key
# Optional
AI_PROVIDER=openai
AI_API_KEY=your-api-key
from flask import Blueprint
from flask_structured_api.core.auth import require_auth
from flask_structured_api.models.responses import SuccessResponse
bp = Blueprint('example', __name__)
@bp.route('/hello', methods=['GET'])
@require_auth
def hello_world():
return SuccessResponse(
message="Hello, World!",
data={"authenticated": True}
).dict()
from flask_structured_api.core.storage import store_api_data
@bp.route('/ai/generate', methods=['POST'])
@require_auth
@store_api_data() # Automatically stores request/response
def generate():
result = ai_service.generate(request.json)
return SuccessResponse(data=result).dict()
- Fork the repository
- Create a feature branch
- Submit a pull request
See CONTRIBUTING.md for guidelines.
This project is licensed under the Apache License 2.0 - see LICENSE and NOTICE for details.
When using this project, please include the following attribution in your documentation:
Based on Flask Structured API (https://github.com/julianfleck/flask-structured-api)
Created by Julian Fleck and contributors