You can avoid having to call this method explicitly if you use the If both cancel_futures and wait are True, all futures that theĮxecutor has started running will be completed prior to this method Any futures thatĪre completed or running won’t be cancelled, regardless of the value If cancel_futures is True, this method will cancel all pendingįutures that the executor has not started running. Value of wait, the entire Python program will not exit until all Return immediately and the resources associated with the executor will beįreed when all pending futures are done executing. Pending futures are done executing and the resources associated with theĮxecutor have been freed. If wait is True then this method will not return until all the Calls toĮxecutor.submit() and Executor.map() made after shutdown will When the currently pending futures are done executing.
#Python queue pool example free
Signal the executor that it should free any resources that it is using shutdown ( wait = True, *, cancel_futures = False ) ¶ ThreadPoolExecutor, chunksize has no effect.Ĭhanged in version 3.5: Added the chunksize argument. Performance compared to the default size of 1. Using a large value for chunksize can significantly improve The (approximate) size of these chunks can be specified by Into a number of chunks which it submits to the pool as separate When using ProcessPoolExecutor, this method chops iterables
Raised when its value is retrieved from the iterator. If a func call raises an exception, then that exception will be None, there is no limit to the wait time. If _next_() is called and the result isn’t availableĪfter timeout seconds from the original call to Executor.map().
The returned iterator raises a TimeoutError The iterables are collected immediately rather than lazily įunc is executed asynchronously and several calls to result ()) map ( func, * iterables, timeout = None, chunksize = 1 ) ¶ submit ( pow, 323, 1235 ) print ( future. With ThreadPoolExecutor ( max_workers = 1 ) as executor : future = executor.
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