FastAPIと非同期処理
FastAPIが非同期関数を自然に処理する仕組みと、効率的なノンブロッキングコードの書き方を理解します。
「FastAPIと非同期処理」はCoddyKit上の無料FastAPI Backend Development Bootcampレッスンです。 これはレッスン2/4です。 下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。 これはFastAPI Backend Development Bootcamp学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 FastAPI Backend Development Bootcampコースには全4レッスンが含まれています。
このレッスンの一部はまだ翻訳されておらず、英語で表示されています。
FastAPI's Async Foundation
FastAPI is built for speed! It leverages Python's asynchronous features to handle many requests concurrently, especially I/O-bound tasks.
This means your API can stay responsive even when waiting for external resources like databases or other APIs.
Sync vs. Async Endpoints
In FastAPI, you can define two main types of endpoint functions:
- Synchronous (
def): These functions block the event loop while they run. If one request takes long, others might wait. - Asynchronous (
async def): These functions can 'pause' and let other tasks run while they await an operation (like reading from a database), making your API non-blocking.
Simple Synchronous Endpoint
Here's a standard synchronous endpoint. While simple, if time.sleep() were a real, slow database call, it would block other requests until it completes.
Try running it and observe the delay if you try to make multiple requests quickly.
from fastapi import FastAPI
import uvicorn
import time
app = FastAPI()
@app.get("/sync_hello")
def sync_hello():
time.sleep(2) # Simulate a blocking I/O operation
return {"message": "Hello from sync endpoint!"}
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=8000)Defining Asynchronous Endpoints
To make your endpoint non-blocking, use async def. This tells FastAPI (and Python) that this function can be suspended and resumed.
Inside an async def function, you use the await keyword to wait for other asynchronous operations to complete without blocking the entire application.
Your First Async Endpoint
This example uses asyncio.sleep(), which is an asynchronous sleep function. Notice the await keyword before it.
This allows FastAPI to handle other requests while this one 'sleeps', making the server more responsive.
from fastapi import FastAPI
import uvicorn
import asyncio
app = FastAPI()
@app.get("/async_hello")
async def async_hello():
await asyncio.sleep(2) # Simulate non-blocking I/O
return {"message": "Hello from async endpoint!"}
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=8000)When to Go Async
async def shines for I/O-bound operations. These are tasks that spend most of their time waiting for something else to happen, such as:
- Making requests to external APIs (e.g.,
httpx). - Querying a database (e.g.,
asyncpg,SQLModel). - Reading/writing files from disk.
- Network communication.
For CPU-bound tasks (heavy calculations), async def doesn't speed up the task itself, but it can help keep the server responsive.
Interacting with Async Libraries
When your FastAPI async def endpoint needs to interact with another asynchronous library (like an async HTTP client or an async database driver), you must use await.
Failing to use await will result in the awaitable object being returned directly, not its resolved result, which is usually not what you want!
Conceptual Async API Call
Imagine fetching data from another service. An async HTTP client allows this without blocking. Here's how it conceptually looks within an async def endpoint:
We simulate network latency with asyncio.sleep to show the non-blocking nature.
from fastapi import FastAPI
import uvicorn
import asyncio
app = FastAPI()
@app.get("/fetch_data")
async def fetch_external_data():
# In a real app, you'd use an async HTTP client like 'httpx'
# async with httpx.AsyncClient() as client:
# response = await client.get("https://api.example.com/data")
# data = response.json()
await asyncio.sleep(1) # Simulate network latency
return {"data": "Fetched async data!"}
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=8000)Uvicorn: The Async Engine
FastAPI relies on an ASGI server like Uvicorn. Uvicorn is what actually runs your async def functions efficiently.
- It manages the Python event loop, which orchestrates when different asynchronous tasks get to run.
- When an
awaitis encountered, Uvicorn can switch to another ready task, making your API highly concurrent.
This 'context switching' is what allows FastAPI to handle many requests without waiting for each one to finish entirely.
Quick Check: Async Use
You are building a FastAPI endpoint that needs to fetch data from a slow external API (an I/O-bound task). Which of the following is the best way to define this endpoint to ensure your FastAPI application remains responsive?
Recap: Async FastAPI
We've explored how FastAPI harnesses Python's asynchronous features:
- Use
async deffor endpoint functions that perform I/O-bound operations. - Use
awaitwhen calling other asynchronous functions or libraries within anasync def. - This non-blocking approach, powered by Uvicorn and the event loop, allows your FastAPI application to handle many concurrent requests efficiently, leading to highly responsive APIs.
Next, we'll look at how to offload truly long-running or CPU-bound tasks to background processes!
よくある質問
「FastAPIと非同期処理」レッスンは無料ですか？
はい。「FastAPIと非同期処理」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、FastAPI Backend Development Bootcampコースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 FastAPI Backend Development Bootcampコースには全4レッスンが含まれています。
「FastAPIと非同期処理」で何を学びますか？
FastAPIが非同期関数を自然に処理する仕組みと、効率的なノンブロッキングコードの書き方を理解します。 ブラウザで直接実行するハンズオンコードでFastAPI Backend Development Bootcampを演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。
FastAPI Backend Development Bootcampを始めるのに経験は必要ですか？
事前経験は必要ありません。CoddyKitのFastAPI Backend Development Bootcampは初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。 これはレッスン2/4です。
「FastAPIと非同期処理」レッスンにはどのくらい時間がかかりますか？
ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。
このFastAPI Backend Development Bootcampレッスンでコードを書いて実行できますか？
はい。すべてのFastAPI Backend Development Bootcampレッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。