python-multithreading

multiprocessing.pool.MaybeEncodingError: 'TypeError(“cannot serialize '_io.BufferedReader' object”,)'

时光总嘲笑我的痴心妄想 提交于 2019-11-27 05:39:01
Why does the code below work only with multiprocessing.dummy , but not with simple multiprocessing . import urllib.request #from multiprocessing.dummy import Pool #this works from multiprocessing import Pool urls = ['http://www.python.org', 'http://www.yahoo.com','http://www.scala.org', 'http://www.google.com'] if __name__ == '__main__': with Pool(5) as p: results = p.map(urllib.request.urlopen, urls) Error : Traceback (most recent call last): File "urlthreads.py", line 31, in <module> results = p.map(urllib.request.urlopen, urls) File "C:\Users\patri\Anaconda3\lib\multiprocessing\pool.py",

How to best perform Multiprocessing within requests with the python Tornado server?

耗尽温柔 提交于 2019-11-27 04:59:49
问题 I am using the I/O non-blocking python server Tornado. I have a class of GET requests which may take a significant amount of time to complete (think in the range of 5-10 seconds). The problem is that Tornado blocks on these requests so that subsequent fast requests are held up until the slow request completes. I looked at: https://github.com/facebook/tornado/wiki/Threading-and-concurrency and came to the conclusion that I wanted some combination of #3 (other processes) and #4 (other threads).

How to find a thread id in Python

萝らか妹 提交于 2019-11-27 04:12:45
问题 I have a multi-threading Python program, and a utility function, writeLog(message) , that writes out a timestamp followed by the message. Unfortunately, the resultant log file gives no indication of which thread is generating which message. I would like writeLog() to be able to add something to the message to identify which thread is calling it. Obviously I could just make the threads pass this information in, but that would be a lot more work. Is there some thread equivalent of os.getpid()

Meaning of daemon property on Python Threads

て烟熏妆下的殇ゞ 提交于 2019-11-27 03:59:36
问题 I'm a little confused about what setting a thread to be a daemon means. The documentation says this: A thread can be flagged as a “daemon thread”. The significance of this flag is that the entire Python program exits when only daemon threads are left. The initial value is inherited from the creating thread. The flag can be set through the daemon property. I'm not sure what makes this different from a normal thread. Is this saying that this program won't ever finish? def threadfunc(): while

Pyqt5 qthread + signal not working + gui freeze

筅森魡賤 提交于 2019-11-27 03:59:29
问题 I am trying to make a mailbox checker with imap lib, it work pretty fine with python, queue and multithread without gui. But when I try to put a gui, every fonction i made, make the gui freeze until finish . I tried many thing from various doc(add qthread, signal, cursorr etcc) and tutorials none worked for me . Can someone help me to understand how to set or append a text to a QtextEdit while running a function coz it work only after finish . Here is my code : class Checker(QtCore.QThread):

Return value from thread

北城以北 提交于 2019-11-27 03:19:24
How do I get a thread to return a tuple or any value of my choice back to the parent in Python? I suggest you instantiate a Queue.Queue before starting the thread, and pass it as one of the thread's args: before the thread finishes, it .put s the result on the queue it received as an argument. The parent can .get or .get_nowait it at will. Queues are generally the best way to arrange thread synchronization and communication in Python: they're intrinsically thread-safe, message-passing vehicles -- the best way to organize multitasking in general!-) If you were calling join() to wait for the

Multiple scipy.integrate.ode instances

一个人想着一个人 提交于 2019-11-27 03:19:16
问题 I would like to use scipy.integrate.ode (or scipy.integrate.odeint) instances in multiple threads (one for each CPU core) in order to solve multiple IVPs at a time. However the documentation says: " This integrator is not re-entrant. You cannot have two ode instances using the “vode” integrator at the same time. " (Also odeint causes internal errors if instantiated multiple times although the documentation does not say so.) Any idea what can be done? 回答1: One option is to use multiprocessing

Use of threading.Thread.join()

不羁的心 提交于 2019-11-27 00:55:18
问题 I am new to multithreading in python and trying to learn multithreading using threading module. I have made a very simple program of multi threading and i am having trouble understanding the threading.Thread.join method. Here is the source code of the program I have made import threading val = 0 def increment(): global val print "Inside increment" for x in range(100): val += 1 print "val is now {} ".format(val) thread1 = threading.Thread(target=increment, args=()) thread2 = threading.Thread

python: how to terminate a thread when main program ends

纵然是瞬间 提交于 2019-11-27 00:44:06
If I have a thread in an infinite loop, is there a way to terminate it when the main program ends (for example, when I press Ctrl + C )? rogeriopvl Check this question. The correct answer has great explanation on how to terminate threads the right way: Is there any way to kill a Thread in Python? To make the thread stop on Keyboard Interrupt signal (ctrl+c) you can catch the exception "KeyboardInterrupt" and cleanup before exiting. Like this: try: start_thread() except (KeyboardInterrupt, SystemExit): cleanup_stop_thread() sys.exit() This way you can control what to do whenever the program is

Matplotlib: simultaneous plotting in multiple threads

社会主义新天地 提交于 2019-11-27 00:04:28
问题 I am trying to do some plotting in parallel to finish large batch jobs quicker. To this end, I start a thread for each plot I plan on making. I had hoped that each thread would finish its plotting and close itself (as I understand it, Python closes threads when they get through all the statements in run()). Below is some code that shows this behavior. If the line that creates a figure is commented out, it runs as expected. Another plausibly helpful tidbit is that it also runs as expected when