This returns an iterator that yields the input future objects in the order in which they complete. Calling next
on the iterator will block until the next future completes, irrespective of order.
Additionally, you can also add more futures to this object during computation with the .add
method
A list of Future objects to be iterated over in the order in which they complete
Whether to wait and include results of futures as well; in this case as_completed
yields a tuple of (future, result)
Whether we should raise when the result of a future raises an exception; only affects behavior when :None:None:`with_results=True`
.
Return futures in the order in which they complete
>>> x, y, z = client.map(inc, [1, 2, 3]) # doctest: +SKIP
... for future in as_completed([x, y, z]): # doctest: +SKIP
... print(future.result()) # doctest: +SKIP 3 2 4
Add more futures during computation
This example is valid syntax, but we were not able to check execution>>> x, y, z = client.map(inc, [1, 2, 3]) # doctest: +SKIP
... ac = as_completed([x, y, z]) # doctest: +SKIP
... for future in ac: # doctest: +SKIP
... print(future.result()) # doctest: +SKIP
... if random.random() < 0.5: # doctest: +SKIP
... ac.add(c.submit(double, future)) # doctest: +SKIP 4 2 8 3 6 12 24
Optionally wait until the result has been gathered as well
This example is valid syntax, but we were not able to check execution>>> ac = as_completed([x, y, z], with_results=True) # doctest: +SKIPSee :
... for future, result in ac: # doctest: +SKIP
... print(result) # doctest: +SKIP 2 4 3
The following pages refer to to this document either explicitly or contain code examples using this.
distributed.client.as_completed.batches
distributed.client.as_completed
distributed.client.as_completed.next_batch
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