I have a bunch of I/O-bound tasks, and I’m executing them asynchronously to exploit concurrency. What makes my case special is that, I have a heuristic for each task’s cost. In the example below, the required time for a task is clearly proportional to its task_id. My initial solution is quite starghtforward. Of course, there ..
I’m seeing some behaviour with Python 3.8 and the concurrent.futures.ThreadPoolExecutor method which I’m not sure is working as designed. What my script does is requests multiple RTSP streams from an RTSP server and then uses OpenCV to save the first frame as a jpg. Here is my code: from cv2 import VideoCapture, imwrite import concurrent.futures ..
Set Up This is part two of a question that I posted regarding accessing results from multiple processes. For part one click Here: Link to Part One I have a complex set of data that I need to compare to various sets of constraints concurrently, but I’m running into multiple issues. The first issue is ..
Summary: When running multiple threads concurrently with ThreadPoolExecutor and an exception is raised in one of them, the remaining threads continue execution. Is there a way to stop all other still-running threads if an exception is raised by one of them? Code: This demonstrative script shows that tasks t1 and t3 continue running even though ..
I have a dataframe that consists of all the links that I will use requests to scrape the data. I am using concurrent.futures.ThreadPoolExecutor to loop through all the links from the dataframe and scrape it. When the scrapings are done, I want to store all the data back into the dataframe. How can I assure ..
Lets say there is four core cpu processor and I am running all four process. To each process, I assigned a queue. But how do i run all queue concurrently. class ParentProcess(multiprocessing.Process): def __init__(self, queue): multiprocessing.Process.__init__(self) self.queue = queue def run(self): while not self.queue.empty(): data = self.queue.get() print(data) def main(): numProcs = 4 queueList = ..
I have two threads in a producer consumer pattern. When the consumer receives data it calls an time consuming function expensive() and then enters in a for loop. But if while the consumer is working new data arrives, it should abort the current work, (exit the loop) and start with the new data. I tried ..
I have a python script. (a single .py file) I need to run it concurrently (say 10/12 times). What is the best way to do it? Source: Python..
I am generating the coefficients for x, y and z. I want to run the generating functions simultaneously (as they take a while), then once all generated, merge the coefficients together. My ideal code will be a bit like this: #generated in parallel x = generate_x() y = generate_y() z = generate_z() merged = x ..
I’ve noticed that concurrent.futures.ThreadPoolExecutor works somewhat well on Darwin OS in cleanly exiting the application when interrupted by KeyboardInterrupt. However, this is not the case for Windows 10, where the process hangs for minutes without any indication of a thrown exception. Here’s an example code: import concurrent.futures import urllib.request URLS = [‘http://www.foxnews.com/’, ‘http://www.cnn.com/’, ‘http://europe.wsj.com/’, ‘http://www.bbc.co.uk/’, ..