CODEWITHSUNDEEP
pythonmultithreadingprocess
Martijn Nosyncerror
Martijn Nosyncerror

Reputation: 192

Access data between two threading processes

We are trying to access data between two threads, but are unable to accomplish this. We are looking for an easy (and elegant) way.

This is our current code. Goal: after the second thread/process is done, the listHolder in instance B must contain 2 items.

Class A:
   self.name = "MyNameIsBlah"

Class B:
   # Contains a list of A Objects. Is now empty.
   self.listHolder = []

   def add(self, obj):
      self.listHolder.append(obj)

   def remove(self, obj):
      self.listHolder.remove(obj)

def process(list):
    # Create our second instance of A in process/thread
    secondItem = A()
    # Add our new instance to the list, so that we can access it out of our process/thread.
    list.append(secondItem)

# Create new instance of B which is the manager. Our listHolder is empty here. 
manager = B()

# Create new instance of A which is our first item
firstItem = A()

# Add our first item to the manager. Our listHolder now contains one item now.
b.add(firstItem)

# Start a new seperate process.
p = Process(target=process, args=manager.listHolder)

# Now start the thread
p.start()

# We now want to access our second item here from the listHolder, which was initiated in the seperate process/thread.

print len(manager.listHolder) << 1
print manager.listHolder[1] << ERROR

How can we access our objects in the manager with the use of a seperated process/threads, so they can run two functions simultaneously in a non-thread-blocking way.

Currently we are trying to accomplish this with processes, but if threads can accomplish this goal in a easier way, then its not a problem. Python 2.7 is used.

Update 1:

@James Mills replied with using ".join()". However, this will block the main thread until the second Process is done. I tried using this, but the Process which is used in this example will never stop execution (while True). It will act as a timer, which must be able to iterate to a list and remove objects from the list.

Anyone has any suggestion how to accomplish this and fix the current cPickle error?

Upvotes: 1

Views: 708

Answers (2)

johntellsall
johntellsall

Reputation: 15170

if James Mills answer doesn't work for you, here's a writeup of how to use queues to explicitly send data back and forth to a worker process:

#!/usr/bin/env python

import logging, multiprocessing, sys


def myproc(arg):
    return arg*2

def worker(inqueue, outqueue):
    logger = multiprocessing.get_logger()
    logger.info('start')
    while True:
        job = inqueue.get()
        logger.info('got %s', job)
        outqueue.put( myproc(job) )

def beancounter(inqueue):
    while True:
        print 'done:', inqueue.get()

def main():
    logger = multiprocessing.log_to_stderr(
            level=logging.INFO,
    )
    logger.info('setup')

    data_queue = multiprocessing.Queue()
    out_queue = multiprocessing.Queue()

    for num in range(5):
        data_queue.put(num)

    worker_p = multiprocessing.Process(
        target=worker, args=(data_queue, out_queue), 
        name='worker',
    )
    worker_p.start()

    bean_p = multiprocessing.Process(
        target=beancounter, args=(out_queue,),
        name='beancounter',
        )
    bean_p.start()

    worker_p.join()
    bean_p.join()
    logger.info('done')


if __name__=='__main__':
    main()

from: Django multiprocessing and empty queue after put

Another example of using multiprocessing Manager to handle the data is here:

http://johntellsall.blogspot.com/2014/05/code-multiprocessing-producerconsumer.html

Upvotes: 2

James Mills
James Mills

Reputation: 19050

One of the simplest ways of Sharing state between processes is to use the multiprocessing.Manager class to synchronize data between processes (which interally uses a Queue):

Example:

from multiprocessing import Process, Manager

def f(d, l):
    d[1] = '1'
    d['2'] = 2
    d[0.25] = None
    l.reverse()

if __name__ == '__main__':
    manager = Manager()

    d = manager.dict()
    l = manager.list(range(10))

    p = Process(target=f, args=(d, l))
    p.start()
    p.join()

    print d
    print l

Output:

bash-4.3$ python -i foo.py 
{0.25: None, 1: '1', '2': 2}
[9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
>>>

Note: Please be careful with the types of obejcts ou are sharing and attaching to your Process classes as you may end up with issues with pickling. See: Python multiprocessing pickling error

Upvotes: 0

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