pool | 易学教程

Using python multiprocessing Pool in the terminal and in code modules for Django or Flask

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问题 When using multiprocessing.Pool in python with the following code, there is some bizarre behavior. from multiprocessing import Pool p = Pool(3) def f(x): return x threads = [p.apply_async(f, [i]) for i in range(20)] for t in threads: try: print(t.get(timeout=1)) except Exception: pass I get the following error three times (one for each thread in the pool), and it prints "3" through "19": AttributeError: 'module' object has no attribute 'f' The first three apply_async calls never return.

Python multiprocessing - tracking the process of pool.map operation

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问题 I have a function which performs some simulation and returns an array in string format. I want to run the simulation (the function) for varying input parameter values, over 10000 possible input values, and write the results to a single file. I am using multiprocessing, specifically, pool.map function to run the simulations in parallel. Since the whole process of running the simulation function over 10000 times takes a very long time, I really would like to track the process of the entire

How to combine Pool.map with Array (shared memory) in Python multiprocessing?

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I have a very large (read only) array of data that I want to be processed by multiple processes in parallel. I like the Pool.map function and would like to use it to calculate functions on that data in parallel. I saw that one can use the Value or Array class to use shared memory data between processes. But when I try to use this I get a RuntimeError: 'SynchronizedString objects should only be shared between processes through inheritance when using the Pool.map function: Here is a simplified example of what I am trying to do: from sys import stdin from multiprocessing import Pool, Array def

When does the pool change?

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问题 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

Python Process Pool non-daemonic?

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Would it be possible to create a python Pool that is non-daemonic? I want a pool to be able to call a function that has another pool inside. I want this because deamon processes cannot create process. Specifically, it will cause the error: AssertionError: daemonic processes are not allowed to have children For example, consider the scenario where function_a has a pool which runs function_b which has a pool which runs function_c . This function chain will fail, because function_b is being run in a daemon process, and daemon processes cannot create processes. The multiprocessing.pool.Pool class

Python Multiprocess Pool. How to exit the script when one of the worker process determines no more work needs to be done?

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问题 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

Can I use a multiprocessing Queue in a function called by Pool.imap?

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问题 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

Python Process Pool non-daemonic?

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问题 Would it be possible to create a python Pool that is non-daemonic? I want a pool to be able to call a function that has another pool inside. I want this because deamon processes cannot create process. Specifically, it will cause the error: AssertionError: daemonic processes are not allowed to have children For example, consider the scenario where function_a has a pool which runs function_b which has a pool which runs function_c . This function chain will fail, because function_b is being run

Combine Pool.map with shared memory Array in Python multiprocessing

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问题 I have a very large (read only) array of data that I want to be processed by multiple processes in parallel. I like the Pool.map function and would like to use it to calculate functions on that data in parallel. I saw that one can use the Value or Array class to use shared memory data between processes. But when I try to use this I get a RuntimeError: \'SynchronizedString objects should only be shared between processes through inheritance when using the Pool.map function: Here is a simplified

How is the java memory pool divided?

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问题 I’m currently monitoring a Java application with jconsole. The memory tab lets you choose between: Heap Memory Usage Non-Heap Memory Usage Memory Pool “Eden Space” Memory Pool “Survivor Space” Memory Pool “Tenured Gen” Memory Pool “Code Cache” Memory Pool “Perm Gen” What is the difference between them ? 回答1: Heap memory The heap memory is the runtime data area from which the Java VM allocates memory for all class instances and arrays. The heap may be of a fixed or variable size. The garbage