Threading vs Multiprocess vs Twisted in Python

Question

Can I get help converting this code from Threading to Mutliprocess. Then can anyone help convert this code usinf twisted.

Would there be a gain from using twisted to upload db
within Python vs External tools.

import  os, pyodbc, sys, threading, Queue


class WorkerThread(threading.Thread):
    def __init__(self, queue):
        threading.Thread.__init__(self)
        self.queue = queue

    def run(self):
        while 1:
            try: # take a job from the queue
                type  = self.queue.get_nowait()

            except Queue.Empty:
                raise SystemExit

            try:
               cxn = pyodbc.connect('DSN=MySQL;PWD=MLML;Option=3') 
               csr = cxn.cursor()    
               # Inserts,update, CRUD

            except:
               # count = count +1
                print 'DB Error', type

if __name__ == '__main__':
    connections =  25

    sml = ('A', 'B', 'C','D',)
    # build a queue with tuples
    queue = Queue.Queue()

    for row in sml:
        if not row or row[0] == "#":
            continue
        queue.put(row) 

    threads = []
    for dummy in range(connections):
        t = WorkerThread(queue)
        t.start()
        threads.append(t)

    # wait for all threads to finish
    for thread in threads:
        thread.join()

    sys.stdout.flush()

#csr.close()
#cxn.close()
print 'Finish'  

Answer 1

Updated : JP mentioned the txpostgres and txmysql modules, which I wasn't aware of. These allow Twisted to access both databases asynchronously (without using a thread pool).

Note that if you decide to use Twisted's enterprise adbapi, it will end up using a thread pool to handle database connections, roughly the equivalent of your existing example. See the docs on using Twisted's enterprise database module .

You should be able to directly translate your thread/queue-based code to use the multiprocessing module, by replacing your threads with Process instances, and uing the multiprocessing Queue implementation. See the multiprocessing docs .