multiprocessing

问题 This example from PYMOTW gives an example of using multiprocessing.Pool() where the processes argument (number of worker processes) passed is twice the number of cores on the machine. pool_size = multiprocessing.cpu_count() * 2 (The class will otherwise default to just cpu_count() .) Is there any validity to this? What is the effect of creating more workers than there are cores? Is there ever a case to be made for doing this, or will it perhaps impose additional overhead in the wrong

问题 This example from PYMOTW gives an example of using multiprocessing.Pool() where the processes argument (number of worker processes) passed is twice the number of cores on the machine. pool_size = multiprocessing.cpu_count() * 2 (The class will otherwise default to just cpu_count() .) Is there any validity to this? What is the effect of creating more workers than there are cores? Is there ever a case to be made for doing this, or will it perhaps impose additional overhead in the wrong

问题 I use standard RotatingFileHandler within my Flask application with next parameters: maxBytes=10 * 1024 * 1024, backupCount=50 . App is managed by uWSGI behind nginx. uWSGI config file part looks like this: processes = 16 enable-threads = true threads = 10 Right after start of an app everything (I mean logging) works well. But after first log file rotation some processes (and maybe threads too) continue writing to rotated file and some - to new one. It is obvious. But for me it is not so

问题 I would like to implement a button to stop a thread with a process, it works but not as expected: i can't delete the thread object. ( EDIT: The reference to the thread object seems to be deleted, but the signals are not disconnected automatically by deleting the thread object, i can access it anyway via the signal.) I have a modul with a class thread_worker and a function for complex processing which is running as process: from PySide.QtCore import * from PySide.QtGui import * import

问题 I would like to implement a button to stop a thread with a process, it works but not as expected: i can't delete the thread object. ( EDIT: The reference to the thread object seems to be deleted, but the signals are not disconnected automatically by deleting the thread object, i can access it anyway via the signal.) I have a modul with a class thread_worker and a function for complex processing which is running as process: from PySide.QtCore import * from PySide.QtGui import * import

问题 I am trying to figure a way to get the number of processes directly from an instance of multiprocessing.Pool class in Python.. Is there a way to do it? The documentation doesn't show anything related. Thanks 回答1: You can use _processes attribute: >>> import multiprocessing >>> pool = multiprocessing.Pool() >>> pool._processes 8 The return value is same for multiprocessing.cpu_count() unless you specified process count when creating Pool object. >>> multiprocessing.cpu_count() 8 来源： https:/

问题 I am trying to figure a way to get the number of processes directly from an instance of multiprocessing.Pool class in Python.. Is there a way to do it? The documentation doesn't show anything related. Thanks 回答1: You can use _processes attribute: >>> import multiprocessing >>> pool = multiprocessing.Pool() >>> pool._processes 8 The return value is same for multiprocessing.cpu_count() unless you specified process count when creating Pool object. >>> multiprocessing.cpu_count() 8 来源： https:/

问题 While serving a FastAPI request, I have a CPU-bound task to do on every element of a list. I'd like to do this processing on multiple CPU cores. What's the proper way to do this within FastAPI? Can I use the standard multiprocessing module? All the tutorials/questions I found so far only cover I/O-bound tasks like web requests. 回答1: TL;DR You could use loop.run_in_executor with ProcessPoolExecutor to start function at a separate process. loop = asyncio.get_event_loop() with concurrent.futures

来源： https://stackoverflow.com/questions/64516687/how-to-write-a-huge-2d-numpy-array-into-a-buffer

来源： https://stackoverflow.com/questions/64516687/how-to-write-a-huge-2d-numpy-array-into-a-buffer