Python AsyncIO Cheat Sheet

Covers async/await syntax, creating and gathering concurrent tasks, synchronization primitives, and timeout/error handling patterns.

2 PagesAdvancedMar 25, 2026

Coroutines & await

Define and run coroutine functions.

python

import asyncioasync def fetch_data(delay):    await asyncio.sleep(delay)   # Non-blocking sleep    return f"data after {delay}s"async def main():    result = await fetch_data(1)    print(result)asyncio.run(main())   # Entry point: creates and runs the event loop

Tasks & Concurrent Execution

Run multiple coroutines concurrently.

python

import asyncioasync def main():    # Schedule coroutines to run concurrently    task1 = asyncio.create_task(fetch_data(1))    task2 = asyncio.create_task(fetch_data(2))    result1 = await task1    result2 = await task2    # Or gather many at once, preserving input order in the results    results = await asyncio.gather(        fetch_data(1), fetch_data(2), fetch_data(3)    )    # Wait for just the first to finish    done, pending = await asyncio.wait(        [task1, task2], return_when=asyncio.FIRST_COMPLETED    )asyncio.run(main())

Synchronization Primitives

Coordinate access between coroutines.

python

import asynciolock = asyncio.Lock()sem = asyncio.Semaphore(3)   # Limit to 3 concurrent tasksasync def worker(n):    async with sem:               # Acquire/release semaphore        async with lock:          # Acquire/release mutex            print(f"worker {n} running")            await asyncio.sleep(1)queue = asyncio.Queue()async def producer():    for i in range(5):        await queue.put(i)async def consumer():    while True:        item = await queue.get()        print(f"consumed {item}")        queue.task_done()

Timeouts & Error Handling

Guard against slow or failing coroutines.

python

import asyncioasync def main():    try:        result = await asyncio.wait_for(fetch_data(5), timeout=2)    except asyncio.TimeoutError:        print("Timed out!")    # gather() with exceptions captured instead of raised    results = await asyncio.gather(        fetch_data(1), bad_coro(), return_exceptions=True    )    for r in results:        if isinstance(r, Exception):            print("failed:", r)

Key Concepts

Core vocabulary for asyncio code.

async def- Defines a coroutine function; calling it returns a coroutine object, not the result
await- Suspends the coroutine until the awaited object completes, yielding control to the event loop
asyncio.create_task()- Schedules a coroutine to run concurrently on the event loop, returns immediately
asyncio.run()- Creates a new event loop, runs the coroutine to completion, and closes the loop
Event loop- The single-threaded scheduler that runs coroutines/tasks and dispatches I/O callbacks
async with / async for- Async context managers and iterators for use inside coroutines

Pro Tip

asyncio gives concurrency, not parallelism — it's built for I/O-bound work like network and disk calls. CPU-bound code still blocks the single-threaded event loop; offload it with loop.run_in_executor() or a ProcessPoolExecutor.

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