pool

I have two questions: public static void main(String[] args) { String s1 = "bla"; String s2 = "b" +"l" + "a"; String s3 = "b".concat("l").concat("a"); if(s1 == s2) System.out.println("Equal"); else System.out.println("Not equal"); if(s1 == s3) System.out.println("Equal"); else System.out.println("Not equal"); } Why does s1 and s2 point to the same object, whereas s1 and s3 doesn't? ( There is no usage of new keyword ). If I get a string from the user and add to the above code these lines: BufferedReader in=new BufferedReader(new InputStreamReader(System.in)); String name=in.readLine(); if(name

mp.set_start_method('spawn') total_count = Counter(0) pool = mp.Pool(initializer=init, initargs=(total_count,), processes=num_proc) pool.map(part_crack_helper, product(seed_str, repeat=4)) pool.close() pool.join() So I have a pool of worker process that does some work. It just needs to find one solution. Therefore, when one of the worker processes finds the solution, I want to stop everything. One way I thought of was just calling sys.exit(). However, that doesn't seem like it's working properly since other processes are running. One other way was to check for the return value of each process

So, I am playing around with multiprocessing.Pool and Numpy , but it seems I missed some important point. Why is the pool version much slower? I looked at htop and I can see several processes be created, but they all share one of the CPUs adding up to ~100%. $ cat test_multi.py import numpy as np from timeit import timeit from multiprocessing import Pool def mmul(matrix): for i in range(100): matrix = matrix * matrix return matrix if __name__ == '__main__': matrices = [] for i in range(4): matrices.append(np.random.random_integers(100, size=(1000, 1000))) pool = Pool(8) print timeit(lambda:

I want a long-running process to return its progress over a Queue (or something similar) which I will feed to a progress bar dialog. I also need the result when the process is completed. A test example here fails with a RuntimeError: Queue objects should only be shared between processes through inheritance . import multiprocessing, time def task(args): count = args[0] queue = args[1] for i in xrange(count): queue.put("%d mississippi" % i) return "Done" def main(): q = multiprocessing.Queue() pool = multiprocessing.Pool() result = pool.map_async(task, [(x, q) for x in range(10)]) time.sleep(1)

I'm using python 2.7, and trying to run some CPU heavy tasks in their own processes. I would like to be able to send messages back to the parent process to keep it informed of the current status of the process. The multiprocessing Queue seems perfect for this but I can't figure out how to get it work. So, this is my basic working example minus the use of a Queue. import multiprocessing as mp import time def f(x): return x*x def main(): pool = mp.Pool() results = pool.imap_unordered(f, range(1, 6)) time.sleep(1) print str(results.next()) pool.close() pool.join() if __name__ == '__main__': main(