python-multithreading

I try to utilize the pool multiprocessing functionality of python. Independent how I set the chunk size (under Windows 7 and Ubuntu - the latter see below with 4 cores), the amount of parallel threads seems to stay the same. from multiprocessing import Pool from multiprocessing import cpu_count import multiprocessing import time def f(x): print("ready to sleep", x, multiprocessing.current_process()) time.sleep(20) print("slept with:", x, multiprocessing.current_process()) if __name__ == '__main__': processes = cpu_count() print('-' * 20) print('Utilizing %d cores' % processes) print('-' * 20)

Any help on how I can get this to accept more than one client, and why it isn't at the moment? Thanks! Also, is there anything I'm doing wrong with this code? I've been following mostly Python 2 tutorials because I can't find any for Python 3.4 Here is my Server code: import socket import time import os from threading import Thread folderPath = "Chat Logs" filePath = folderPath + "/" + str(time.strftime("%H-%M-%S_%d-%m-%Y")) + ".txt" def clientHandler(c): while True: data = c.recv(1024) if not data: break data = data.decode("UTF-8") message = str(data[:data.index("§")]) nick = str(data[data

I'm using Python's Watchdog to monitor a given directory for new files being created. When a file is created, some code runs that spawns a subprocess shell command to run different code to process this file. This should run for every new file that is created. I've tested this out when one file is created, and things work great, but am having trouble getting it working when multiple files are created, either at the same time, or one after another. My current problem is this... the processing code run in the shell takes a while to run and will not finish before a new file is created in the

Closed . This question is opinion-based. It is not currently accepting answers. Learn more . Want to improve this question? Update the question so it can be answered with facts and citations by editing this post . I am running a python method that parses a lot of data. Since it is time intensive, I would like to run it asynchronously on a separate thread so the user can still access the website/UI. Do threads using the "from threading import thread" module terminate if a user exits the site or do they continue to run on the server? What would be the advantages of using Celery versus simply

I have a simple producer consumer application. The producer is a thread that writes stuff to a queue and a consumer is a thread that reads the messages from the queue does stuff and at some points exits. my producer looks a little bit like this def producer(queue): while not queue.full(): queue.put(randint(1, 199)) and the consumer def consumer(queue): for i in range(100): print(queue.get()) queue.task_done() in my main I invoke those threads like that p = Thread(target=producer) c = Thread(target=consumer) p.daemon = True p.start() c.start() c.join() when c finishes the only remaining non