apply_async callback function not being called

I am a newbie to python,i am have function that calculate feature for my data and then return a list that should be processed and written in file.,..i am using Pool to do the calculation and then and use the callback function to write into file,however the callback function is not being call,i ve put some print statement in it but it is definetly not being called. my code looks like this:

def write_arrow_format(results):
print("writer called")
results[1].to_csv("../data/model_data/feature-"+results[2],sep='\t',encoding='utf-8')
with open('../data/model_data/arow-'+results[2],'w') as f:
     for dic in results[0]:
         feature_list=[]
         print(dic)
         beginLine=True
         for key,value in dic.items():
              if(beginLine):
                feature_list.append(str(value))
                beginLine=False
              else:
                feature_list.append(str(key)+":"+str(value))
         feature_line=" ".join(feature_list)
         f.write(feature_line+"\n")


def generate_features(users,impressions,interactions,items,filename):
    #some processing 
    return [result1,result2,filename]





if __name__=="__main__":
   pool=mp.Pool(mp.cpu_count()-1)

   for i in range(interval):
       if i==interval:
          pool.apply_async(generate_features,(users[begin:],impressions,interactions,items,str(i)),callback=write_arrow_format)
       else:
           pool.apply_async(generate_features,(users[begin:begin+interval],impressions,interactions,items,str(i)),callback=write_arrow_format)
           begin=begin+interval
   pool.close()
   pool.join()

It's not obvious from your post what is contained in the list returned by generate_features. However, if any of result1, result2, or filename are not serializable, then for some reason the multiprocessing lib will not call the callback function and will fail to do so silently. I think this is because the multiprocessing lib attempts to pickle objects before passing them back and forth between child processes and the parent process. If anything you're returning isn't "pickleable" (i.e not serializable) then the callback doesn't get called.

I've encountered this bug myself, and it turned out to be an instance of a logger object that was giving me troubles. Here is some sample code to reproduce my issue:

import multiprocessing as mp
import logging 

def bad_test_func(ii):
    print('Calling bad function with arg %i'%ii)
    name = "file_%i.log"%ii
    logging.basicConfig(filename=name,level=logging.DEBUG)
    if ii < 4:
        log = logging.getLogger()
    else:
        log = "Test log %i"%ii
    return log

def good_test_func(ii):
    print('Calling good function with arg %i'%ii)
    instance = ('hello', 'world', ii)
    return instance

def pool_test(func):
    def callback(item):
        print('This is the callback')
        print('I have been given the following item: ')
        print(item)
    num_processes = 3
    pool = mp.Pool(processes = num_processes)
    results = []
    for i in range(5):
        res = pool.apply_async(func, (i,), callback=callback)
        results.append(res)
    pool.close()
    pool.join()

def main():

    print('#'*30)
    print('Calling pool test with bad function')
    print('#'*30)

    pool_test(bad_test_func)

    print('#'*30)
    print('Calling pool test with good function')
    print('#'*30)
    pool_test(good_test_func)

if __name__ == '__main__':
    main()

Hopefully this helpful and points you in the right direction.