API Service Development

This skill covers development of the FastAPI backend services located in /api (main API) and /api_diagnostics (system diagnostics API). Both services follow the same patterns and conventions.

Technology Stack

•Python 3.14 - Core language
•FastAPI - Web framework for building APIs
•Pydantic - Data validation and settings management
•Docker - Containerization
•Redis - Caching layer (via redis.asyncio)
•uvicorn - ASGI server

Project Structure

code

api/
├── main.py              # FastAPI app entry point, router registration, middleware
├── config.py            # Settings and configuration
├── requirements.txt     # Python dependencies
├── Dockerfile           # Docker build configuration
├── cache/               # Redis cache utilities
│   └── router.py
├── github/              # GitHub integration
│   ├── models.py
│   ├── router.py
│   └── retrieval.py
├── pihole/              # Pi-hole integration
│   ├── models.py
│   ├── router.py
│   ├── authentication.py
│   └── retrieval.py
├── nas/                 # Synology NAS integration
│   ├── models.py
│   ├── router.py
│   ├── authentication.py
│   ├── constants.py
│   └── retrieval.py
└── [other services]/    # Similar structure for each service

Creating New Endpoints

1. Create Pydantic Models

Define request/response models in models.py:

python

from pydantic import BaseModel, Field
from typing import Literal

class MyResponseData(BaseModel):
    name: str
    value: int
    status: Literal["active", "inactive"]

class MyResponse(BaseModel):
    data: MyResponseData
    success: Literal[True]

2. Create Router

Create a router in router.py:

python

import logging
from fastapi import APIRouter, HTTPException, Request, status

logger = logging.getLogger(__name__)

router = APIRouter(
    prefix="/myservice",
    tags=["MyService"],
)

@router.get("/", tags=["Ping"])
async def get_health(request: Request):
    return {"status": "ok"}

@router.get("/data/")
async def get_data(request: Request):
    try:
        # Implement data retrieval
        return {"data": "..."}
    except Exception as e:
        logger.error(f"Error: {e}")
        raise HTTPException(status_code=500, detail=str(e))

3. Register Router

Add the router in main.py:

python

from api.myservice.router import router as myservice_router

api.include_router(myservice_router)

4. Add Tags Metadata (Optional)

Add to tags_metadata in main.py for OpenAPI documentation:

python

tags_metadata = [
    # ... existing tags
    {
        "name": "MyService",
        "description": "Description of my service",
    },
]

Available Tools

Linting and Formatting

Run these commands from the repository root:

bash

# Format Python code with Black
black api/

# Sort imports with isort
isort api/

# Lint with flake8
flake8 api/

Docker Operations

bash

# Build the API container
docker compose -f compose.dev.yml build api

# Run the API in development mode
docker compose -f compose.dev.yml up api

# View API logs
docker compose -f compose.dev.yml logs -f api

Dependency Management

bash

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

# Add new dependency (update requirements.txt manually)
# Format: package>=min_version,<max_version

Best Practices

•Use Type Hints: Always use Python type hints for function parameters and return values
•Pydantic Validation: Use Pydantic models for all request/response data
•Async Functions: Use async def for endpoint handlers to support async operations
•Error Handling: Use HTTPException with appropriate status codes
•Logging: Use the module logger (logger = logging.getLogger(__name__))
•Redis Caching: Access Redis via request.app.state.redis
•Router Organization: Each service module should have its own router with a unique prefix

Patterns Used in This Codebase

Authentication Pattern

For services requiring authentication (see nas/authentication.py, pihole/authentication.py):

python

async def authenticate(credentials: dict) -> str:
    # Return session/token
    pass

async def logout(session: str) -> None:
    pass

Data Retrieval Pattern

Separate retrieval logic from routers (see retrieval.py files):

python

async def retrieve_data(request: Request) -> dict:
    # Fetch and process data
    redis = request.app.state.redis
    # Check cache, fetch if needed, cache result
    return data