Machine Learning Mission

# Automatic API documentation
from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def root():
    return {"message": "Hello World"}

# Run with: uvicorn main:app --reload
# Visit: http://127.0.0.1:8000/docs

from pydantic import BaseModel
from fastapi import FastAPI

app = FastAPI()

class Item(BaseModel):
    name: str
    price: float
    is_offer: bool = False

@app.post("/items/")
async def create_item(item: Item):
    return item

from fastapi import Depends, FastAPI

app = FastAPI()

async def common_parameters(q: str = None, skip: int = 0, limit: int = 100):
    return {"q": q, "skip": skip, "limit": limit}

@app.get("/items/")
async def read_items(commons: dict = Depends(common_parameters)):
    return commons

from fastapi import BackgroundTasks, FastAPI

app = FastAPI()

def write_notification(email: str, message=""):
    # Simulate sending an email
    with open("log.txt", mode="w") as email_file:
        content = f"notification for {email}: {message}"
        email_file.write(content)

@app.post("/send-notification/{email}")
async def send_notification(email: str, background_tasks: BackgroundTasks):
    background_tasks.add_task(write_notification, email, message="some notification")
    return {"message": "Notification sent in the background"}