create-fastapi-service 0.1.1

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Why create-fastapi-service?

Setting up a new FastAPI microservice from scratch takes hours — configuring the database session, wiring routers, writing middleware, setting up auth, connecting Redis, adding Docker support… every time. create-fastapi-service eliminates all of that.

create-fastapi-service payment-service --postgres --redis --jwt --docker

↓ In under 2 minutes you get ↓

✓  uv init complete
✓  Directories and __init__.py files created
✓  PostgreSQL session (async SQLAlchemy)
✓  Redis client + @cache() decorator
✓  JWT RS256 handler
✓  Dockerfile + docker-compose.yml
✓  RSA key-pair generated in keys/
✓  Dependencies installed

  Swagger UI  →  http://localhost:8000/payment-service/docs
  Health      →  http://localhost:8000/payment-service/api/v1/health

✨ Features

🚀 Quick Start

Prerequisites

# Python 3.12+
python --version

# uv package manager
pip install uv
# or: curl -LsSf https://astral.sh/uv/install.sh | sh

Option 1 — Install once, use anywhere (recommended)

pip install create-fastapi-service

Then from any directory:

create-fastapi-service my-service --all
create-fastapi-service payment-api --postgres --redis --jwt
create-fastapi-service event-bus --kafka --workers

Option 2 — Clone & run

git clone https://github.com/me-lier/FastAPI-Fast.git
cd FastAPI-Fast
python create_fastapi_app.py my-service --all

Option 3 — Pin in requirements.txt

Add this line to any project's requirements.txt:

create-fastapi-service

Then:

pip install -r requirements.txt
create-fastapi-service my-service --all

After generating a service

cd my-service
uv run uvicorn app.main:app --reload

Open http://localhost:8000/my-service/docs 🎉

🎛️ CLI Options

create-fastapi-service <service-name> [options]
# or if running from clone:
python create_fastapi_app.py <service-name> [options]

Examples

# Full stack
create-fastapi-service payment-service --all

# Auth + DB only
create-fastapi-service auth-service --postgres --jwt

# Event-driven service
create-fastapi-service event-service --kafka --workers --redis

# Choose features interactively
create-fastapi-service my-api --interactive

💡 Use Cases

1. Payment / Billing API

Needs a database, caching for speed, JWT auth to protect endpoints, and Docker for deployment.

create-fastapi-service payment-service --postgres --redis --jwt --docker

What you get:

• Async PostgreSQL for storing transactions
• Redis @cache() to avoid duplicate DB hits
• JWT RS256 to protect /charge, /refund endpoints
• docker-compose.yml with Postgres + Redis ready to go

cd payment-service
docker compose up --build
# Swagger UI → http://localhost:8000/payment-service/docs

2. Auth / Identity Service

Pure auth service — issues and validates JWT tokens, stores users in Postgres, runs DB migrations.

create-fastapi-service auth-service --postgres --jwt --alembic

What you get:

• RSA key-pair auto-generated in keys/
• create_access_token() + require_auth() ready to use
• Alembic migrations pre-configured for user table
• verify_token() endpoint for other services to validate tokens

cd auth-service
uv run alembic upgrade head
uv run uvicorn app.main:app --reload

3. Event-Driven Notification Service

Consumes Kafka events (e.g. order.placed) and processes them via background workers.

create-fastapi-service notification-service --kafka --workers --redis

What you get:

• Kafka consumer template wired to asyncio event loop
• Background worker loop with graceful shutdown
• Redis to deduplicate or throttle notifications

cd notification-service
uv run uvicorn app.main:app --reload
# Worker starts automatically on app startup

4. Simple CRUD REST API

Just need a database and a clean project structure — no auth, no cache.

create-fastapi-service inventory-service --postgres

What you get:

• Async SQLAlchemy session + models + repositories
• Pre-wired GET/POST/PUT/DELETE /users endpoints to extend
• Pydantic schemas, services layer, structured logging

cd inventory-service
uv run uvicorn app.main:app --reload
# http://localhost:8000/inventory-service/docs

5. Full Production Microservice

Everything — when you want the complete stack from day one.

create-fastapi-service orders-service --all

What you get: PostgreSQL + Redis + JWT + Kafka + Docker + Background Workers + Alembic migrations + test scaffold + OpenTelemetry tracing + structured logging + request ID middleware.

cd orders-service
docker compose up --build
# http://localhost:8000/orders-service/docs

6. Not sure what you need? Use interactive mode

create-fastapi-service my-service --interactive

Prompts you one feature at a time:

? Add PostgreSQL support? (y/n) y
? Add Redis caching? (y/n) n
? Add JWT authentication? (y/n) y
? Add Kafka messaging? (y/n) n
? Add Docker support? (y/n) y
? Add background workers? (y/n) n
? Add Alembic migrations? (y/n) y

📁 Generated Project Structure

my-service/
│
├── app/
│   ├── main.py                    # FastAPI app factory + lifespan
│   │
│   ├── api/
│   │   ├── router.py              # Root API router
│   │   └── v1/
│   │       ├── router.py          # v1 router
│   │       └── endpoints/
│   │           ├── health.py      # GET /health
│   │           └── users.py       # CRUD /users
│   │
│   ├── auth/
│   │   └── jwt_handler.py         # RS256 create/verify token
│   │
│   ├── cache/
│   │   ├── redis_client.py        # Async Redis connection
│   │   └── decorators.py          # @cache(ttl=60)
│   │
│   ├── kafka/
│   │   ├── producer.py            # publish(topic, payload)
│   │   └── consumer.py            # consume(handler)
│   │
│   ├── workers/
│   │   └── task_worker.py         # Async background loop
│   │
│   ├── logging/
│   │   └── logger.py              # get_logger(name)
│   │
│   ├── middleware/
│   │   ├── request_id.py          # X-Request-ID header
│   │   └── request_context.py     # Request/response logging
│   │
│   ├── models/
│   │   └── user_model.py          # SQLAlchemy ORM model
│   │
│   ├── repositories/
│   │   └── user_repository.py     # DB queries (CRUD)
│   │
│   ├── schemas/
│   │   └── user_schema.py         # Pydantic request/response
│   │
│   ├── services/
│   │   └── user_service.py        # Business logic
│   │
│   ├── db/
│   │   └── session.py             # Async SQLAlchemy engine + session
│   │
│   ├── dependencies/
│   │   └── auth.py                # Depends() factories
│   │
│   ├── utils/
│   │   └── tracing.py             # OpenTelemetry helpers
│   │
│   └── core/
│       └── config.py              # Pydantic Settings
│
├── keys/
│   ├── private.pem                # RSA private key (auto-generated)
│   └── public.pem                 # RSA public key  (auto-generated)
│
├── migrations/                    # Alembic scaffold
│   ├── env.py
│   └── versions/
│
├── tests/
│   └── test_health.py             # Async health check test
│
├── scripts/
│
├── Dockerfile                     # Multi-stage production image
├── docker-compose.yml             # API + Postgres + Redis + Kafka
├── gunicorn.conf.py               # UvicornWorker, cpu*2+1 workers
├── .env                           # Environment variables
├── pyproject.toml                 # Project metadata + pinned deps
└── README.md

🏛️ Architecture

Every generated service follows a strict layered architecture:

HTTP Request
     │
     ▼
┌─────────────────────────────────────────┐
│           Middleware Layer              │
│   RequestIDMiddleware (X-Request-ID)    │
│   RequestContextMiddleware (logging)    │
└─────────────────────────────────────────┘
     │
     ▼
┌─────────────────────────────────────────┐
│              Router Layer               │
│   /{service}/api/v1/users               │
│   /{service}/api/v1/health              │
└─────────────────────────────────────────┘
     │
     ▼
┌─────────────────────────────────────────┐
│             Endpoint Layer              │
│   HTTP validation, Depends injection    │
└─────────────────────────────────────────┘
     │
     ▼
┌─────────────────────────────────────────┐
│             Service Layer               │
│   Business logic, cache decorators      │
└─────────────────────────────────────────┘
     │
     ▼
┌─────────────────────────────────────────┐
│           Repository Layer              │
│   All DB queries, no business logic     │
└─────────────────────────────────────────┘
     │
     ▼
┌─────────────────────────────────────────┐
│           Database / Cache              │
│   PostgreSQL (asyncpg) │ Redis          │
└─────────────────────────────────────────┘

Each layer has one job:

🔒 JWT Authentication (RS256)

RSA keys are auto-generated at project creation time:

keys/private.pem   # signing key   (keep secret)
keys/public.pem    # verification key (share freely)

Create a token:

from app.auth.jwt_handler import create_access_token

token = create_access_token(subject="user@example.com")

Protect an endpoint:

from app.dependencies.auth import require_auth

@router.get("/secure")
async def secure_route(user: dict = Depends(require_auth)):
    return {"user": user}

Call the secured endpoint:

curl -H "Authorization: Bearer <token>" \
     http://localhost:8000/my-service/api/v1/users/secure

🔴 Redis Caching

from app.cache.decorators import cache

@cache(ttl=60)
async def get_user(user_id: int) -> dict:
    # result cached in Redis for 60 seconds
    return await repo.get_by_id(user_id)

Cache key is auto-derived from the function module, name, args and kwargs. No configuration needed.

📨 Kafka

Publish an event:

from app.kafka.producer import publish

await publish("user.created", {"id": 1, "email": "a@b.com"})

Consume events:

from app.kafka.consumer import consume

async def handle(msg: dict):
    print("received:", msg)

await consume(handler=handle)

🐳 Docker

# Start everything (API + Postgres + Redis + Kafka)
docker compose up --build

# API only
docker compose up api

Services:

🔄 Database Migrations (Alembic)

# After starting Postgres:
uv run alembic revision --autogenerate -m "init"
uv run alembic upgrade head

🌐 Service-Scoped URLs

Every URL is automatically prefixed with the service name so multiple services can run on the same host without path collisions:

http://localhost:8000/payment-service/docs
http://localhost:8000/payment-service/redoc
http://localhost:8000/payment-service/openapi.json
http://localhost:8000/payment-service/api/v1/health
http://localhost:8000/payment-service/api/v1/users

The prefix is derived from APP_NAME in .env at runtime — rename the service by changing one variable.

🧪 Running Tests

cd my-service
uv run pytest --cov=app tests/ -v

The test scaffold includes an async health check test using httpx.AsyncClient + ASGITransport (no server needed).

📦 Pinned Dependencies

All dependencies are installed with exact minimum versions:

🛡️ Resilient Startup

The generated service never crashes on startup due to missing infrastructure. Each connection attempt is wrapped:

INFO  | main | Starting payment-service (env=development)
WARN  | main | Database unavailable at startup: Connection refused
WARN  | main | Endpoints requiring DB will fail until PostgreSQL is reachable.
WARN  | main | Redis unavailable at startup: Connection refused
WARN  | main | Endpoints using @cache() will skip caching until Redis is reachable.
WARN  | main | Kafka unavailable at startup: ...
INFO  | main | Background worker started
INFO  | Uvicorn running on http://127.0.0.1:8000   ← always starts

⚙️ Production Server

# Gunicorn with UvicornWorker — auto-scales to cpu_count * 2 + 1 workers
uv run gunicorn -c gunicorn.conf.py app.main:app

🗺️ Roadmap

• --graphql — Strawberry GraphQL integration
• --grpc — gRPC service scaffold
• --sentry — Sentry error tracking
• --prometheus — Prometheus metrics endpoint
• --celery — Celery task queue
• pip install git+... — installable CLI via GitHub
• pip install create-fastapi-service — published to PyPI

🤝 Contributing

Contributions are welcome! Here's how to get started:

1. Fork the repo — github.com/me-lier/FastAPI-Fast
2. Create a feature branch: git checkout -b feat/my-feature
3. Make your changes to create_fastapi_app.py
4. Test by generating a new project: python create_fastapi_app.py test-svc --all
5. Push and open a Pull Request

Found a bug? Open an issue with steps to reproduce.

📄 License

MIT © 2025 Srinivas Deekonda — Free to use in personal and commercial projects.

👨‍💻 Author

Srinivas Deekonda

Building tools that help developers ship production-grade services faster.