await asyncio.gather

Concurrency & Async

Meaning

Awaits the concurrent execution of multiple awaitable objects (e.g., coroutines, Tasks) and returns their results in the order of the input awaitables.

Primary Function

Async concurrency

Communicative Purpose

Enables running multiple independent async operations concurrently and collecting all results before proceeding

Pattern

await asyncio.gather(awaitable1, awaitable2, ...)

Core Structure

await asyncio.gather( awaitable1, awaitable2, ... )

Função primária

Async concurrency

Propósito comunicativo

Enables running multiple independent async operations concurrently and collecting all results before proceeding

Situações de gatilho

Network I/O: fetching from multiple APIs in parallel; Data pipelines: running independent transformations concurrently; Testing: executing multiple async test setups simultaneously

Contextos

Inside an async function when you have multiple coroutines or Tasks that can run independently and you need their results together.

Padrão

await asyncio.gather(awaitable1, awaitable2, ...)

Estrutura central

await asyncio.gather( awaitable1, awaitable2, ... )

Slots de substituição

awaitable1: coroutine or Task; awaitable2: coroutine or Task; ...: additional awaitables

Colocados típicos

async
await
asyncio
tasks
coroutines
results
return_exceptions

Substituições comuns

asyncio.wait: for fine-grained control over done/pending sets (more verbose)
asyncio.wait_for: adds timeout to a single awaitable

Erros comuns

Forgetting to await gather itself — cause: treating it as fire-and-forget — consequence: coroutines never execute and results are never collected; Passing non-awaitable objects — cause: misunderstanding what gather accepts — consequence: TypeError at runtime; Not using return_exceptions=True when any coroutine may fail — cause: assuming partial results are still useful — consequence: first exception cancels remaining tasks and propagates; Expecting results in completion order — cause: conflating gather with as_completed — consequence: wrong result mapped to wrong coroutine

Similar / contraste

asyncio.wait (returns done/pending sets), asyncio.wait_for (timeout on a single awaitable), asyncio.sleep (delay)

Interferências

Coming from JavaScript: Promise.all rejects on first rejection and all others are ignored — asyncio.gather also propagates first exception unless return_exceptions=True, but remaining tasks continue running; Coming from threading: may expect gather to use OS threads — asyncio.gather schedules coroutines on a single event loop, not parallel threads

Família do chunk

asyncio-gather

Nuance

Do not use when operations depend on each other's results — run them sequentially instead; All awaitables start immediately upon gather call, which can overwhelm rate-limited services; If one coroutine raises and return_exceptions is False, remaining tasks continue running but their results are discarded

Efeito pragmático

Signals that the programmer intends to launch several asynchronous operations in parallel and wait for all outcomes before continuing.

Dica de memória

Like a group photo — everyone lines up, the camera waits for all to be ready, and you get all faces back in the order they stood, not the order they smiled

Nota

Use return_exceptions=True to collect exceptions as results instead of propagating them.

Upgrade path

Consider asyncio.wait for fine-grained control over done/pending sets, or asyncio.as_completed for processing results as they complete.

Frequência: HighFormulaicidade: Semi-fixedTipo de construção: await expression calling asyncio.gatherPrioridade de aquisição: Active recallPrioridade de output: OutputTag de espaçamento: Medium-term

Examples

import asyncio async def fetch_user(user_id): await asyncio.sleep(1) return {"id": user_id, "name": f"User {user_id}"} async def main(): results = await asyncio.gather( fetch_user(1), fetch_user(2), fetch_user(3) ) print(results) asyncio.run(main())

import asyncio async def compute(value): await asyncio.sleep(1) return value ** 2 async def main(): inputs = [1, 2, 3, 4, 5] results = await asyncio.gather(*[compute(n) for n in inputs]) print(results) asyncio.run(main())

import asyncio async def risky_task(name, fail=False): await asyncio.sleep(0.5) if fail: raise ValueError(f"{name} failed") return f"{name} succeeded" async def main(): results = await asyncio.gather( risky_task("alpha"), risky_task("beta", fail=True), risky_task("gamma"), return_exceptions=True ) for result in results: if isinstance(result, Exception): print(f"Error: {result}") else: print(result) asyncio.run(main())