![]() close () # You can close QJoinableQueue with close()Ĭomplete example (it needs import multiprocessing): def _process ( qjq ): print ( qjq. join () # When end put values call to put_remain() or join() to mark you will not put more values QJoinableQueue. put ( "value" ) # Put all the values you need qjq. Pseudocode without process: qjq = QJoinableQueue () # > qjq. Import: from quick_queue import QJoinableQueue You can use a Joinable Queue if you want use join and task_done in queue. Process ( target = _process, args = ( qq, qq. end () if _name_ = "_main_" : qq = QQueue ( """""" ) p = multiprocessing. Then in second process you can expand those args in init method with **. With get_init_args (return a dict with your args) in process where you instanced QQueue, You can use defined args in the main constructor if you pass values. Process ( target = _process, args = ( qq ,)) p. end () if _name_ = "_main_" : qq = QQueue () p = multiprocessing. def _process ( qq ): # Define initial args to this process, if you do not call to init method, then it use default values qq. Not found the way) and, by other side, maybe you want to define a different initial values per "put process" to Python message pass between process it is not possible share values in the same shared Queue object (at least I have If you need to use put in other process, then you need to initialize values in QQueue with init. get ()) if _name_ = "_main_" : qq = QQueue () p = multiprocessing. Operation when iterable is consumed but this not close queue, you need call to close() or to end() in this case): def _process ( qq ): print ( qq. You can put all values in one iterable or several iterables with put_iterable method ( put_iterable perform remain Queue, you can call put_remain, then you need to call manually to close (or end, this performs close operation Note: you need to call end method to perform remain operation and close queue. ![]() end () # When end put values call to end() to mark you will not put more values and close QQueueĬomplete example (it needs import multiprocessing): def _process ( qq ): print ( qq. put ( "value" ) # Put all the values you need qq. Pseudocode without process: qq = QQueue () # > qq. ![]() Then subprocesses have elements very quickly. While Producer produce and put lists of elements in queue, subprocesses consume those lists and iterate every element, In other words, Multiprocess queue is pretty slow putting and getting individual data, then QuickQueue wrap severalĭata in one list, this list is one single data that is enqueue in the queue than is more quickly than put one To transfer data between python processes.īut if you put or get one list with elements work similar as put or get one single element this list is getting asįast as usually but this has too many elements for process in the subprocess and this action is very quickly. ![]() The motivation to create this class is due to multiprocessing.queue is too slow putting and getting elements Last release version of the project to install in: pip install quick-queue Information about multiprocessing.queue in This is an implementation of Quick Multiprocessing Queue for Python and work similar to multiprocessing.queue (more ![]()
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