![]() Does not guarantee to return the original awaitables that you passed in.Yields Futures that you have to await as soon as something is done.There’s no way to find out which awaitable you’re awaiting though 5. as_completed (, timeout = 5.0 ): try : await fut print ( "one task down!" ) except Exception : print ( "ouch" ) So the following construct is quite common:įor fut in asyncio. If the awaitable is a coroutine, it will automatically be wrapped by a task. asyncio.wait_for()Īsyncio.wait_for() takes two arguments: one awaitable and a timeout in seconds. Since gather() hasn’t an option for that, we need the next helper. Now we can wait for many awaitables at once! However well-behaved distributed systems need timeouts. If gather() itself is canceled, it cancels all unfinished tasks it’s gathering.Otherwise if one of the awaitables raises an exception, gather() propagates it immediately to the caller.Allows errors to be returned as results (by passing return_exceptions=True).Returns the list of results in the same order.Wraps each awaitable in a task if necessary.You can also pass return_exceptions=True and then exceptions are returned like normal results and you have to check yourself whether or not they were successful (e.g. However if gather() itself is canceled, all of the awaitables that it’s gathering – and that have not completed yet – are also canceled. If f() or g() raise an exception, gather() will raise it immediately, but the other tasks are not affected. Then it returns the results of all awaitables in the same order as you passed in the awaitables: asyncio.gather()Īsyncio.gather() takes 1 or more awaitables as *args, wraps them in tasks if necessary, and waits for all of them to finish. What we need is to gather the results of multiple awaitables. In real-life code you often enough don’t even know how many awaitables you will need to wrangle. However, the awaits are only needed to collect the results and to clean up resources 3.īut waiting for each of them like this is not very practical. Please note that you must create both tasks before you await the first one – otherwise you gain nothing. Your tasks now run concurrently and if you decide that you don’t want to wait for task_f or task_g to finish, you can cancel them using task_f.cancel() or task_g.cancel() respectively. sleep ( 0.1 ) # <- f() and g() are already running! result_f = await task_f result_g = await task_g
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