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Python / FastAPI Basics Interview Questions

What are BackgroundTasks in FastAPI and when should you use them?

BackgroundTasks let you run work after returning a response to the client — for lightweight fire-and-forget tasks like sending emails or writing audit logs. The response is sent immediately and the task runs afterward in the same process.

from fastapi import FastAPI, BackgroundTasks
from pydantic import BaseModel

app = FastAPI()

def send_welcome_email(email: str, username: str):
    # Simulate sending an email (could call an email service)
    print(f"Sending welcome email to {email} for {username}")

def write_audit_log(action: str, user_id: int):
    print(f"Audit: user {user_id} performed {action}")

class UserIn(BaseModel):
    username: str
    email: str

@app.post("/register", status_code=201)
def register_user(user: UserIn, background_tasks: BackgroundTasks):
    # Response is returned immediately
    # Email is sent after the response
    background_tasks.add_task(
        send_welcome_email,
        email=user.email,
        username=user.username,
    )
    background_tasks.add_task(write_audit_log, "register", user_id=42)
    return {"message": f"User {user.username} created"}

# BackgroundTasks can also be injected via dependencies
def get_background(background_tasks: BackgroundTasks) -> BackgroundTasks:
    return background_tasks

Limitations: BackgroundTasks run in the same process and event loop — if the server restarts, queued tasks are lost. For heavy, reliable background work use Celery, ARQ, or FastAPI + Redis Queue instead.

When is FastAPI's BackgroundTasks appropriate to use?
When does a BackgroundTask actually run relative to the HTTP response?

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