FastAPI Day 14 – Core Design Philosophy, Interview Q&A, and 14‑Day Learning Summary

FastAPI Core Design Philosophy

Type hints drive everything. Python type hints are real type information; FastAPI relies on Pydantic to read these annotations and automatically generate JSON Schema, validation rules, and OpenAPI documentation.

Python type hints → Pydantic field → JSON Schema → OpenAPI docs

Declaring a parameter automatically provides runtime validation, interactive documentation, and IDE type hints.

Frequently Asked Interview Questions

FastAPI vs Flask vs Django

Framework positioning : FastAPI – API framework; Flask – microframework; Django – full‑stack.

Type safety : FastAPI – native support; Flask – none; Django – none.

Async support : FastAPI – native async; Flask – requires extensions; Django – limited.

Automatic docs : FastAPI – generated by default; Flask – manual; Django – none.

Learning curve : FastAPI – low; Flask – low; Django – high.

Typical scenarios : FastAPI – APIs, data services; Flask – small projects; Django – large web applications.

Dependency injection

Depends() builds a dependency graph, FastAPI resolves it, caches repeated dependencies within a request, and runs cleanup code after yield.

def get_db():
    db = connect()
    yield db
    db.close()

def get_current_user(token: str = Depends(verify_token), db = Depends(get_db)):
    ...

For each request FastAPI executes dependencies in DAG order and runs cleanup in reverse order.

Pydantic validation mechanism

BaseModel reads Python type annotations.

Converts them to JSON Schema.

At runtime JSON Schema validates request data.

Validation failures return HTTP 422.

Validated data is passed directly to the route function.

Field() configures defaults, validation rules, and description.

async def vs def

async def

: coroutine, suited for I/O‑bound work such as database queries or external APIs. def: runs in a thread pool, suited for calling synchronous libraries or CPU‑bound work.

# I/O‑bound, use async
@app.get("/items/{id}")
async def get_item(id: int):
    item = await db_query()  # async DB
    return item

# Call sync library, use def
@app.get("/compute")
def compute():
    result = sync_calculation()  # thread‑pool
    return result

Middleware vs Dependency Injection

Scope : Middleware – global, every request passes through; Dependency Injection – declared per route.

Typical use : Middleware – logging, CORS, timing; Dependency Injection – authentication, pagination, DB session.

Execution timing : Middleware – on request entry and response exit; Dependency Injection – before route function execution.

The two complement each other rather than replace each other.

14‑Day Learning Roadmap

Day 1‑2: Routes, path parameters, query parameters.

Day 3‑4: Request bodies, response models, input‑output separation.

Day 5: Dependency injection.

Day 6: Error handling, middleware, CORS.

Day 7: JWT authentication.

Day 8: Database integration, project structure.

Day 9‑12: Complete Todo API project.

Day 13: Background tasks, deployment.

Day 14: Knowledge map, interview preparation.

References

Official documentation (Chinese): https://fastapi.tiangolo.com/zh/

GitHub repository: https://github.com/fastapi/fastapi