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Run a coroutine with each item in an iterable, concurrently
pip install aioconcurrency
import aioconcurrency
items = [1, 2, 3, 4]
async def f(item):
return item * 2
async def main():
await aioconcurrency.map(items, f, concurrency=2) # Returns [2, 4, 6, 8]
async for result in aioconcurrency.each(items, f, concurrency=2):
print(result) # Prints 2 4 6 8 in random order
Runs the given coroutine concurrently with each item in an iterable. The list of the return values will be ordered as if ran serially.
items
An iterable object.
coro
Coroutine to feed each item to.
optional: concurrency
Number of concurrent runs of coro
. Defaults to aioconcurrency.Infinite
.
optional: executor
Can be an instance of ThreadPoolExecutor.
optional: loop
The asyncio event loop that will be used.
Runs the given coroutine concurrently with each item in an iterable. Returns a generator that may be used to iterate over the return values. The generator yields values as soon as they are available.
items
An iterable object. If an asyncio.Queue
is passed then .each
will read from it indefinitely.
coro
Coroutine to feed each item to.
optional: concurrency
Number of concurrent runs of coro
. Defaults to aioconcurrency.Infinite
.
optional: executor
Can be an instance of ThreadPoolExecutor.
optional: loop
The asyncio event loop that will be used.
optional: discard_results
If truthy, discard the return value of coro
. Defaults to false.
property: wait()
Coroutine. May be used to wait until all items have been processed.
property: processed_count
The number of items that have been processed so far.
property: cancel()
Cancels all runs of coro
.
pytest .
FAQs
Run a coroutine with each item in an iterable, concurrently
We found that aioconcurrency demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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