Python async standard library providing async versions of builtins, itertools, functools, contextlib, and heapq for asyncio, trio, and custom event loops. Use when building async Python applications that need iterator operations (zip, map, chain, groupby), async caching (lru_cache), async context managers, or safe iterator lifecycle management.
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name
asyncstdlib-3-14-0
description
Python async standard library providing async versions of builtins, itertools, functools, contextlib, and heapq for asyncio, trio, and custom event loops. Use when building async Python applications that need iterator operations (zip, map, chain, groupby), async caching (lru_cache), async context managers, or safe iterator lifecycle management.
asyncstdlib 3.14.0
Overview
asyncstdlib re-implements functions and classes from the Python standard library to make them compatible with async callables, iterables, and context managers. It is fully agnostic to async event loops — it works seamlessly with asyncio, trio, and any custom async event loop.
The library mirrors the structure of the standard library, with submodules named after their stdlib counterparts:
asyncstdlib.builtins — Async versions of built-in functions: zip(), map(), sum(), list(), sorted(), etc.
asyncstdlib.functools — Async versions of reduce(), lru_cache(), and cached_property().
asyncstdlib.contextlib — Async versions of contextmanager(), closing(), ExitStack, and related tools.
asyncstdlib.itertools — Async versions of chain(), cycle(), accumulate(), groupby(), tee(), etc.
All functions are also available directly from the top-level asyncstdlib namespace. For example, asyncstdlib.enumerate is a shortcut for asyncstdlib.builtins.enumerate.
Reducing async iterables (sum, all, any, max, min, reduce)
Collecting async iterables into standard types (list, dict, set, tuple)
Caching async function results with lru_cache or cached_property
Building async context managers with contextmanager or managing multiple contexts with ExitStack
Merging pre-sorted async streams with heapq.merge
Safely managing async iterator lifecycle with scoped_iter and borrow
Writing async-neutral code that accepts both sync and async arguments
Core Concepts
Async Neutral Arguments
Many asyncstdlib functions are async neutral — they accept both regular (sync) and async arguments. Type annotations use parentheses to denote this: (async) iter T means the parameter can be either a sync or async iterable. Whether a callable is sync or async is determined by inspecting its return type at runtime.
However, all asyncstdlib functions consistently produce awaitables, async iterators, and async context managers as output. Only arguments may be async neutral.
Async Iterator Cleanup
Cleanup of async iterables requires an active event loop (via aclose()). All asyncstdlib utilities that work on async iterators assume sole ownership of passed-in iterators and eagerly aclose() them when done. This provides a resource-safe default for the most common case of exhausting iterators.
Use borrow() to prevent automatic cleanup when passing an iterator to another function. Use scoped_iter() as a context manager to guarantee cleanup in custom code while providing a borrowed iterator for safe passing around.
Event Loop Agnosticism
asyncstdlib does not depend on any specific event loop. It works with asyncio, trio, or any custom async framework that supports the standard async iteration and context manager protocols.
Usage Examples
Basic async iteration with builtins:
import asyncstdlib as a
asyncdefmain():
# Async zip of sync and async iterables
names = ["alice", "bob", "carol"]
asyncdefget_scores():
for s in [95, 87, 92]:
yield s
asyncfor name, score in a.zip(names, get_scores()):
print(f"{name}: {score}")
# Reduce an async iterable
total = await a.sum(a.iter(range(100)))
print(total) # 4950
