multiprocessing

问题 I want to use subprocesses to let 20 instances of a written script run parallel. Lets say i have a big list of urls with like 100.000 entries and my program should control that all the time 20 instances of my script are working on that list. I wanted to code it as follows: urllist = [url1, url2, url3, .. , url100000] i=0 while number_of_subproccesses < 20 and i<100000: subprocess.Popen(['python', 'script.py', urllist[i]] i = i+1 My script just writes something into a database or textfile. It

问题 I want to use subprocesses to let 20 instances of a written script run parallel. Lets say i have a big list of urls with like 100.000 entries and my program should control that all the time 20 instances of my script are working on that list. I wanted to code it as follows: urllist = [url1, url2, url3, .. , url100000] i=0 while number_of_subproccesses < 20 and i<100000: subprocess.Popen(['python', 'script.py', urllist[i]] i = i+1 My script just writes something into a database or textfile. It

问题 I'm planning to use concurrent.futures.ProcessPoolExecutor to parallelize execution of functions. According to the documentation, its executor object can only accept a simple function in map . My actual situation involves initialization (loading of data) prior to execution of the 'to-be-parallelized' function. How do I arrange that? The 'to-be-parallelized' function is called in an iteration for many times. I don't want it to be re-initialized each time. In other words, there's an init

问题 From this post: Two threads being timesliced on a single CPU core won't run into a reordering problem. A single core always knows about its own reordering and will properly resolve all its own memory accesses. Multiple cores however operate independently in this regard and thus won't really know about each other's reordering. Why can't the instruction reorder issue occur on a single CPU core? This article doesn't explain it. EXAMPLE : The following pictures are picked from Memory Reordering

问题 I am designing a dedicated syslog-processing daemon for Linux that needs to be robust and scalable and I'm debating multithread vs. multiprocess. The obvious objection with multithreading is complexity and nasty bugs. Multi-processes may impact performance because of IPC communications and context switching. "The Art of Unix Programming" discusses this here. Would you recommend a process-based system (like Apache) or a multi-threaded approach? 回答1: Both of them can be complicated and complex

问题 I am using multiprocessing module for parallel processing. Bellow code snippet search the string filename in X location and return the file name where the string found. But in some cases it take long time to search process so i was trying to kill the search process with take more than 300 seconds.For that i used timeout == 300 as given bellow , this kills the search process but it dosent kill the child process spawn by bellow code. I tried to find multiple way but no success :/ How can i kill

问题 I am using multiprocessing module for parallel processing. Bellow code snippet search the string filename in X location and return the file name where the string found. But in some cases it take long time to search process so i was trying to kill the search process with take more than 300 seconds.For that i used timeout == 300 as given bellow , this kills the search process but it dosent kill the child process spawn by bellow code. I tried to find multiple way but no success :/ How can i kill

问题 I would like to use a queue for passing data from a parent to a child process which is launched via multiprocessing.Process . However, since the parent process uses Python's new asyncio library, the queue methods need to be non-blocking. As far as I understand, asyncio.Queue is made for inter-task communication and cannot be used for inter-process communication. Also, I know that multiprocessing.Queue has the put_nowait() and get_nowait() methods but I actually need coroutines that would

问题 I am a bit confused about multiproessing feature of mod_wsgi and about a general design of WSGI applications that would be executed on WSGI servers with multiprocessing ability. Consider the following directive: WSGIDaemonProcess example processes=5 threads=1 If I understand correctly, mod_wsgi will spawn 5 Python (e.g. CPython) processes and any of these processes can receive a request from a user. The documentation says that: Where shared data needs to be visible to all application

问题 I have been working with the multiprocessing package to speed up some geoprocessing (GIS/ arcpy ) tasks that are redundant and need to be done the same for more than 2,000 similar geometries. The splitting up works well, but my "worker" function is rather long and complicated because the task itself from start to finish is complicated. I would love to break the steps apart down more but I am having trouble passing information to/from the worker function because for some reason ANYTHING that a