Multiprocessing share array

Question

How i can share an array as in the code below with an array and not a single value (in this example there is a counter as you can see)?

How i can append and remove elements from the array?

class mp_counter(object):
    def __init__(self, initval=0):
        self.val = multiprocessing.Value('i', initval)
        self.lock = multiprocessing.Lock()

    def increment(self):
        with self.lock:
            self.val.value += 1

    def decrement(self):
        with self.lock:
            self.val.value -= 1

    def value(self):
        with self.lock:
            return self.val.value

counter = mp_counter(0)
proc = threading.Thread(target=start_processes,kwargs={"counter":counter})
proc.daemon = True
proc.start()

Thank you in advance

What about the Queue? Check out this example: docs.python.org/2/library/… — matino
– matino, Commented Apr 27, 2017 at 15:42
What about shared arrays: shared_array_base = multiprocessing.Array(ctypes.c_double, 10) shared_array = np.ctypeslib.as_array(shared_array_base.get_obj()) — RicLeal
– RicLeal, Commented Apr 27, 2017 at 15:44

J'e · Accepted Answer · 2017-04-27 16:26:09Z

1

check out from multiprocessing import Array. Array has a "lock" argument that has a default of True for thread safe reason. another option would be from multiprocessing import RawArray which does not have "lock" built in.

from multiprocessing import Array, Process
import numpy as np

def worker(shared_arr, proc_number):
    shared_arr[proc_number] = 1

shared_arr = Array('f', 4)
print("initialArray:", np.array(shared_arr))
# will print [ 0. 0. 0. 0.]

num_procs = 2
processes = []
for proc_number in range(2):
    p = threading.Thread(target=worker, args=(shared_arr, proc_number,))
    p.daemon = True
    processes.append(p)
[p.start() for p in processes]
[p.join() for p in processes]

print("results:", np.array(shared_arr))
# will print [ 1. 1. 0. 0. ]

answered Apr 27, 2017 at 16:26

J'e

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Comments

RicLeal · Accepted Answer · 2017-04-27 16:00:04Z

Using your code I'm +1 the whole array. Is that what you want?

import multiprocessing
import ctypes
import threading

import numpy as np


class mp_counter(object):
    def __init__(self, initval=0):
        shared_array_base = multiprocessing.Array(ctypes.c_double, initval)
        self.val = np.ctypeslib.as_array(shared_array_base.get_obj())
        self.lock = multiprocessing.Lock()

    def increment(self):
        with self.lock:
            self.val += 1

    def decrement(self):
        with self.lock:
            self.val -= 1

    def value(self):
        with self.lock:
            return self.val

def start_processes(counter):
    print("Before:", counter)
    m = mp_counter(counter)
    m.increment()
    print("After: ", m.value())

if __name__ == '__main__':
    counter = [1., 2., 3., 4.]
    proc = threading.Thread(target=start_processes,kwargs={"counter":counter})
    proc.daemon = True
    proc.start()
    proc.join()

The output is:

Before: [1.0, 2.0, 3.0, 4.0]
After:  [ 2.  3.  4.  5.]

I hope it helped!

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