Meaning
Creates a list of asyncio.Task objects by invoking a coroutine function multiple times in a list comprehension. Use it when you need to fire off several independent asynchronous operations concurrently and keep references to their tasks for later awaiting or cancellation.
Primary Function
Task creation and concurrency
Communicative Purpose
Launch multiple concurrent asynchronous operations and obtain handles to manage them.
Pattern
tasks = [asyncio.create_task(coro(item)) for item in collection]
Core Structure
... = [asyncio.create_task(...) for ... in ...]
Função primária
Task creation and concurrency
Propósito comunicativo
Launch multiple concurrent asynchronous operations and obtain handles to manage them.
Situações de gatilho
Web scraping: downloading many URLs in parallel, API clients: processing a batch of async database queries, Server startup: starting several background services concurrently
Contextos
Asyncio-based Python applications, web scrapers, API clients, any code using async/await for I/O‑bound work.
Padrão
tasks = [asyncio.create_task(coro(item)) for item in collection]
Estrutura central
... = [asyncio.create_task(...) for ... in ...]
Slots de substituição
tasks: list identifier, coro: coroutine function, item: element from collection, collection: iterable of items
Colocados típicos
- asyncio.gather
- asyncio.wait
- await
- event loop
Substituições comuns
- asyncio.ensure_future (deprecated
- prefer create_task)
- loop.create_task (older API
- requires explicit event loop reference)
- asyncio.TaskGroup (Python 3.11+
- provides structured concurrency and automatic exception propagation)
- asyncio.gather(*[coro(item) for item in collection]) (awaits all at once
- no intermediate task handles)
Erros comuns
Forgetting to await tasks — tasks are created but never awaited, causing silent dropped work and 'Task was destroyed but it is pending' warnings; Using blocking calls inside the coroutine — blocks the entire event loop since asyncio is cooperative multitasking; Creating unlimited concurrent tasks — can exhaust file descriptors or memory when launching thousands of I/O operations without a semaphore; Not handling task exceptions — unhandled exceptions in tasks are only reported when the task is garbage collected, not at the point of creation
Similar / contraste
asyncio.gather(*[coro() for _ in range(workers)]) – collects results directly; asyncio.TaskGroup provides structured concurrency and automatic cleanup
Interferências
Coming from thread‑based languages: may treat asyncio tasks as heavyweight OS threads → they are lightweight and cooperative, so excessive numbers still need limits
Família do chunk
- asyncio task creation
- asyncio.gather
- asyncio.wait
- asyncio.TaskGroup
Nuance
Do not use when you need results in a specific order or when tasks have interdependencies — use asyncio.gather or sequential awaits instead; Each create_task call schedules the coroutine immediately on the event loop, so resource usage scales with the number of tasks; The list comprehension evaluates eagerly, creating all tasks at once — for lazy or bounded scheduling, construct tasks incrementally or use a semaphore
Efeito pragmático
Enables fire‑and‑forget concurrency; simplifies launching multiple async operations
Dica de memória
Spawn a swarm of workers with a list comprehension
Nota
Ensure the coroutine function is defined as async def and returns an awaitable; avoid blocking calls inside the coroutine to keep the event loop responsive.
Upgrade path
async with asyncio.TaskGroup() as tg: [tg.create_task(coro()) for _ in range(workers)]
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