starting multiple threads using python?

Question

I am trying to gulp threading, and started with Python Module of the week examples:

according to below code

import threading

def worker(arg=None):
    """thread worker function"""
    print 'Worker thread: %s\n' % arg
    return

threads = []
for i in range(5):
    t = threading.Thread(target=worker, args=str(i), name="threadingPrac")
    threads.append(t)
    t.start()

does this mean that I am starting 5 threads ?

I have just started with threading so want to understand it better.

Christian Berendt · Accepted Answer · 2014-06-11 13:16:55Z

1

Yes.

Add import time and time.sleep(5) after the print statement to better see it.

import threading
import time

def worker(arg=None):
    """thread worker function"""
    print 'Worker thread: %s\n' % arg
    time.sleep(5)
    return

threads = []
for i in range(5):
    t = threading.Thread(target=worker, args=str(i), name="threadingPrac")
    threads.append(t)
    t.start()

answered Jun 11, 2014 at 13:16

Christian Berendt

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6 Comments

Ciasto piekarz Over a year ago

what I don't understand is these threads don't start simultaneously because for loop executes each thread one by one, so in what way threading will be helpful ? does that mean while the first thread is started and second is called at next iteration level then the second thread will executes parallely with the first thread and so forth ?

Christian Berendt Over a year ago

Maybe you should read some general texts about threads. You could start at en.wikipedia.org/wiki/Thread_(computing).

Aashish P Over a year ago

@san yes you are correct. Each subsequent threads will starts in each loop and do their operation. Python suffers from GIL, so you should consider using threads only in case of i/o bound tasks and not computational one. In case of computational tasks and want to achieve parallel processing, you should go for multiprocessing.

Ciasto piekarz Over a year ago

can you point me to an example that shows computational task and threading fails?

dano Over a year ago

@san It's not that threading actually "fails", it's that because of the Global Interpreter Lock (GIL), most of the time only one thread can actually execute at a time, even if you have multiple CPU cores. So using threads for CPU-bound tasks will usually not be faster than using a single thread. It's even slower than a single thread sometimes, because of the extra overhead of switching between the threads over and over. When you want to parallelize CPU-bound tasks, use multiprocessing, which uses multiple processes instead of threads, and therefore isn't affected by the GIL.

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Deelaka · Accepted Answer · 2014-06-11 13:17:56Z

0

Yes you can check the length of the list threads by adding this line at the bottom of your code:

print len(threads)

Output:

5 #Number of threads

answered Jun 11, 2014 at 13:17

Deelaka

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