Using globally declared tuple for Python multiprocessing

I am having some trouble using a tuple globally with the multiprocessing class.

I have a code as produced below:

from multiprocessing import Pool



if __name__ == '__main__':

    jj = ()

    def f(x):

        global jj

        jj += (x*x,)



    # Section A

    #for ii in range(20):

    #    f(ii)

    #print (jj)



    # Section B

    pool = Pool(processes=4)

    pool.map(f, range(20))  

    pool.join()

    print (jj)

If I run section only B, I get the tuple jj as an empty tuple. However, if I run only section A, I get a tuple of length 20.

Why is that so?

edited Nov 22 '18 at 9:00

asked Nov 22 '18 at 8:45

Shihab Khan

227

Please run either section A or section B at a time. Comment out the other section not in use. I use tuple because in my original code, I have to store a lot of variables and I read that the instantiation of tuples is much faster than a list. I am not calling these values anywhere in the code.

– Shihab Khan
Nov 22 '18 at 8:59

add a comment |

I am having some trouble using a tuple globally with the multiprocessing class.

I have a code as produced below:

from multiprocessing import Pool



if __name__ == '__main__':

    jj = ()

    def f(x):

        global jj

        jj += (x*x,)



    # Section A

    #for ii in range(20):

    #    f(ii)

    #print (jj)



    # Section B

    pool = Pool(processes=4)

    pool.map(f, range(20))  

    pool.join()

    print (jj)

If I run section only B, I get the tuple jj as an empty tuple. However, if I run only section A, I get a tuple of length 20.

Why is that so?

edited Nov 22 '18 at 9:00

asked Nov 22 '18 at 8:45

Shihab Khan

227

Please run either section A or section B at a time. Comment out the other section not in use. I use tuple because in my original code, I have to store a lot of variables and I read that the instantiation of tuples is much faster than a list. I am not calling these values anywhere in the code.

– Shihab Khan
Nov 22 '18 at 8:59

add a comment |

I am having some trouble using a tuple globally with the multiprocessing class.

I have a code as produced below:

from multiprocessing import Pool



if __name__ == '__main__':

    jj = ()

    def f(x):

        global jj

        jj += (x*x,)



    # Section A

    #for ii in range(20):

    #    f(ii)

    #print (jj)



    # Section B

    pool = Pool(processes=4)

    pool.map(f, range(20))  

    pool.join()

    print (jj)

If I run section only B, I get the tuple jj as an empty tuple. However, if I run only section A, I get a tuple of length 20.

Why is that so?

edited Nov 22 '18 at 9:00

asked Nov 22 '18 at 8:45

Shihab Khan

227

I am having some trouble using a tuple globally with the multiprocessing class.

I have a code as produced below:

from multiprocessing import Pool



if __name__ == '__main__':

    jj = ()

    def f(x):

        global jj

        jj += (x*x,)



    # Section A

    #for ii in range(20):

    #    f(ii)

    #print (jj)



    # Section B

    pool = Pool(processes=4)

    pool.map(f, range(20))  

    pool.join()

    print (jj)

If I run section only B, I get the tuple jj as an empty tuple. However, if I run only section A, I get a tuple of length 20.

Why is that so?

python python-3.x python-multiprocessing

edited Nov 22 '18 at 9:00

asked Nov 22 '18 at 8:45

Shihab Khan

227

edited Nov 22 '18 at 9:00

asked Nov 22 '18 at 8:45

Shihab Khan

227

edited Nov 22 '18 at 9:00

asked Nov 22 '18 at 8:45

Shihab Khan

227

asked Nov 22 '18 at 8:45

Shihab Khan

227

asked Nov 22 '18 at 8:45

Shihab Khan

227

Please run either section A or section B at a time. Comment out the other section not in use. I use tuple because in my original code, I have to store a lot of variables and I read that the instantiation of tuples is much faster than a list. I am not calling these values anywhere in the code.

– Shihab Khan
Nov 22 '18 at 8:59

add a comment |

Please run either section A or section B at a time. Comment out the other section not in use. I use tuple because in my original code, I have to store a lot of variables and I read that the instantiation of tuples is much faster than a list. I am not calling these values anywhere in the code.

– Shihab Khan
Nov 22 '18 at 8:59

Please run either section A or section B at a time. Comment out the other section not in use. I use tuple because in my original code, I have to store a lot of variables and I read that the instantiation of tuples is much faster than a list. I am not calling these values anywhere in the code.

– Shihab Khan
Nov 22 '18 at 8:59

add a comment |

1 Answer
1

active

oldest

votes

Ok, as Python multiprocessing global variable updates not returned to parent explains, global state is not shared among processes.

You can share state using, for example, multiprocessing.Queue.

from multiprocessing import Pool, Queue



if __name__ == "__main__":

    jj = ()

    q = Queue()



    def f(x):

        global jj

        jj += (x * x,)



    def f_multi(x):

        q.put(x * x)



    # Section A

    for ii in range(20):

        f(ii)

    print(jj)



    # Section B

    pool = Pool(processes=4)

    pool.map(f_multi, range(20))

    pool.close()



    stop = "STOP"

    q.put(stop)

    items = 

    for i in iter(q.get, stop):

        items.append(i)



    print(tuple(items))

Alternatively you can use print(tuple(sorted(items))) to get the values in the same order as Section A will produce. 4 processes are working on the task in Section B and hence the "unordered" result.

edited Nov 22 '18 at 9:32

answered Nov 22 '18 at 9:26

Dušan Maďar

4,37742035

Thanks a lot. Actually @Dušan, the problem which I am facing is that I don't have a single variable I'd have to put in a Queue. I have a function that generates a lot of data. I'm trying to store that data from each iteration so that I can use them later on for validating/checking my results. Is there any efficient way to do that? It seems to be that I'll have to do this for each of the variables.

– Shihab Khan
Nov 22 '18 at 9:34

1

You can put all variables you want to return from your function to a dict and then put that dict to the Queue, e.g. q.put({'data1': [1,2,3], 'data2': (0.5, 0.6)}).

– Dušan Maďar
Nov 22 '18 at 9:43

This sounds like a good idea. If I can make the function return this dictionary then I don't even have to use a queue.

– Shihab Khan
Nov 22 '18 at 9:53

add a comment |

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1 Answer
1

active

oldest

votes

1 Answer
1

active

oldest

votes

Ok, as Python multiprocessing global variable updates not returned to parent explains, global state is not shared among processes.

You can share state using, for example, multiprocessing.Queue.

from multiprocessing import Pool, Queue



if __name__ == "__main__":

    jj = ()

    q = Queue()



    def f(x):

        global jj

        jj += (x * x,)



    def f_multi(x):

        q.put(x * x)



    # Section A

    for ii in range(20):

        f(ii)

    print(jj)



    # Section B

    pool = Pool(processes=4)

    pool.map(f_multi, range(20))

    pool.close()



    stop = "STOP"

    q.put(stop)

    items = 

    for i in iter(q.get, stop):

        items.append(i)



    print(tuple(items))

edited Nov 22 '18 at 9:32

answered Nov 22 '18 at 9:26

Dušan Maďar

4,37742035

Thanks a lot. Actually @Dušan, the problem which I am facing is that I don't have a single variable I'd have to put in a Queue. I have a function that generates a lot of data. I'm trying to store that data from each iteration so that I can use them later on for validating/checking my results. Is there any efficient way to do that? It seems to be that I'll have to do this for each of the variables.

– Shihab Khan
Nov 22 '18 at 9:34

1

You can put all variables you want to return from your function to a dict and then put that dict to the Queue, e.g. q.put({'data1': [1,2,3], 'data2': (0.5, 0.6)}).

– Dušan Maďar
Nov 22 '18 at 9:43

This sounds like a good idea. If I can make the function return this dictionary then I don't even have to use a queue.

– Shihab Khan
Nov 22 '18 at 9:53

add a comment |

Ok, as Python multiprocessing global variable updates not returned to parent explains, global state is not shared among processes.

You can share state using, for example, multiprocessing.Queue.

from multiprocessing import Pool, Queue



if __name__ == "__main__":

    jj = ()

    q = Queue()



    def f(x):

        global jj

        jj += (x * x,)



    def f_multi(x):

        q.put(x * x)



    # Section A

    for ii in range(20):

        f(ii)

    print(jj)



    # Section B

    pool = Pool(processes=4)

    pool.map(f_multi, range(20))

    pool.close()



    stop = "STOP"

    q.put(stop)

    items = 

    for i in iter(q.get, stop):

        items.append(i)



    print(tuple(items))

edited Nov 22 '18 at 9:32

answered Nov 22 '18 at 9:26

Dušan Maďar

4,37742035

Thanks a lot. Actually @Dušan, the problem which I am facing is that I don't have a single variable I'd have to put in a Queue. I have a function that generates a lot of data. I'm trying to store that data from each iteration so that I can use them later on for validating/checking my results. Is there any efficient way to do that? It seems to be that I'll have to do this for each of the variables.

– Shihab Khan
Nov 22 '18 at 9:34

1

You can put all variables you want to return from your function to a dict and then put that dict to the Queue, e.g. q.put({'data1': [1,2,3], 'data2': (0.5, 0.6)}).

– Dušan Maďar
Nov 22 '18 at 9:43

This sounds like a good idea. If I can make the function return this dictionary then I don't even have to use a queue.

– Shihab Khan
Nov 22 '18 at 9:53

add a comment |

Ok, as Python multiprocessing global variable updates not returned to parent explains, global state is not shared among processes.

You can share state using, for example, multiprocessing.Queue.

from multiprocessing import Pool, Queue



if __name__ == "__main__":

    jj = ()

    q = Queue()



    def f(x):

        global jj

        jj += (x * x,)



    def f_multi(x):

        q.put(x * x)



    # Section A

    for ii in range(20):

        f(ii)

    print(jj)



    # Section B

    pool = Pool(processes=4)

    pool.map(f_multi, range(20))

    pool.close()



    stop = "STOP"

    q.put(stop)

    items = 

    for i in iter(q.get, stop):

        items.append(i)



    print(tuple(items))

edited Nov 22 '18 at 9:32

answered Nov 22 '18 at 9:26

Dušan Maďar

4,37742035

Ok, as Python multiprocessing global variable updates not returned to parent explains, global state is not shared among processes.

You can share state using, for example, multiprocessing.Queue.

from multiprocessing import Pool, Queue



if __name__ == "__main__":

    jj = ()

    q = Queue()



    def f(x):

        global jj

        jj += (x * x,)



    def f_multi(x):

        q.put(x * x)



    # Section A

    for ii in range(20):

        f(ii)

    print(jj)



    # Section B

    pool = Pool(processes=4)

    pool.map(f_multi, range(20))

    pool.close()



    stop = "STOP"

    q.put(stop)

    items = 

    for i in iter(q.get, stop):

        items.append(i)



    print(tuple(items))

edited Nov 22 '18 at 9:32

answered Nov 22 '18 at 9:26

Dušan Maďar

4,37742035

edited Nov 22 '18 at 9:32

answered Nov 22 '18 at 9:26

Dušan Maďar

4,37742035

answered Nov 22 '18 at 9:26

Dušan Maďar

4,37742035

answered Nov 22 '18 at 9:26

Dušan Maďar

4,37742035

Thanks a lot. Actually @Dušan, the problem which I am facing is that I don't have a single variable I'd have to put in a Queue. I have a function that generates a lot of data. I'm trying to store that data from each iteration so that I can use them later on for validating/checking my results. Is there any efficient way to do that? It seems to be that I'll have to do this for each of the variables.

– Shihab Khan
Nov 22 '18 at 9:34

1

You can put all variables you want to return from your function to a dict and then put that dict to the Queue, e.g. q.put({'data1': [1,2,3], 'data2': (0.5, 0.6)}).

– Dušan Maďar
Nov 22 '18 at 9:43

This sounds like a good idea. If I can make the function return this dictionary then I don't even have to use a queue.

– Shihab Khan
Nov 22 '18 at 9:53

add a comment |

Thanks a lot. Actually @Dušan, the problem which I am facing is that I don't have a single variable I'd have to put in a Queue. I have a function that generates a lot of data. I'm trying to store that data from each iteration so that I can use them later on for validating/checking my results. Is there any efficient way to do that? It seems to be that I'll have to do this for each of the variables.

– Shihab Khan
Nov 22 '18 at 9:34

1

You can put all variables you want to return from your function to a dict and then put that dict to the Queue, e.g. q.put({'data1': [1,2,3], 'data2': (0.5, 0.6)}).

– Dušan Maďar
Nov 22 '18 at 9:43

This sounds like a good idea. If I can make the function return this dictionary then I don't even have to use a queue.

– Shihab Khan
Nov 22 '18 at 9:53

Thanks a lot. Actually @Dušan, the problem which I am facing is that I don't have a single variable I'd have to put in a Queue. I have a function that generates a lot of data. I'm trying to store that data from each iteration so that I can use them later on for validating/checking my results. Is there any efficient way to do that? It seems to be that I'll have to do this for each of the variables.

– Shihab Khan
Nov 22 '18 at 9:34

You can put all variables you want to return from your function to a dict and then put that dict to the Queue, e.g. q.put({'data1': [1,2,3], 'data2': (0.5, 0.6)}).

– Dušan Maďar
Nov 22 '18 at 9:43

This sounds like a good idea. If I can make the function return this dictionary then I don't even have to use a queue.

– Shihab Khan
Nov 22 '18 at 9:53

add a comment |

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