async / await

Introduction

async/await enables single-thread concurrency for I/O-bound code — perfect for web servers, scrapers, and pipelines doing many network calls.

Understanding the topic

Core concepts to understand:

• async def defines a coroutine.
• await yields control to the loop.
• asyncio.gather() runs in parallel.
• Blocking calls freeze the loop — use async libs.

Syntax reference

Visual flow / code:

import asyncio, httpx

async def fetch(client, url):
    r = await client.get(url)
    return r.status_code

async def main():
    async with httpx.AsyncClient() as client:
        results = await asyncio.gather(
            fetch(client, "https://example.com"),
            fetch(client, "https://python.org"),
            fetch(client, "https://github.com"),
        )
        print(results)

asyncio.run(main())

Execution workflow

Real-world use

FastAPI, aiohttp, Litestar, and modern Python web stacks are async-first. A single async worker can handle thousands of concurrent connections.

Best practices

• Use async libraries (httpx, asyncpg) — never sync ones inside async fns.
• asyncio.gather for parallel I/O.
• asyncio.run() at the entry point.

Common mistakes

• Calling requests.get inside async fn blocks the event loop.

Hands-on exercise

Interview preparation — practice these questions:

• async vs threads vs processes?
• What is the event loop?
• When does await yield?

Summary

In summary: Single-thread concurrency for I/O. Never block the event loop.