CODEWITHSUNDEEP
pythonmultithreading
user8904897
user8904897

Reputation: 21

Passing arguments to a function from list using Threads in python

I am trying to pass arguments to a function from a list using threads in python (Note:The values to the function should not be hard-coded and all the elements of the list will be passed.) Please look at the sample code here:

from threading import Thread
list=['john','doe','srav','dev','app']
def m1(name,prefix):
    for ele in range(2):
        print(name +prefix)

def main1():
    t1=Thread(target=m1,args=('abcd','john'))
    t2 = Thread(target=m1, args=('abcd', 'doe'))
    t1.start()
    t2.start()

if __name__ == '__main__':
    main1()

Here i hard-coded the values to the function ('john','doe')instead of that pass from the list and all the elements will be passed.

Upvotes: 2

Views: 1387

Answers (2)

Mad Physicist
Mad Physicist

Reputation: 114518

Your tasks are well suited for use with the concurrent.futures module. In particular, Executor.map applies a function to the elements of an iterable.

You can use something similar to the ThreadPoolExecutor example in the docs:

from concurrent.futures import ThreadPoolExecutor
from itertools import repeat

names = ['john', 'doe', 'srav', 'dev', 'app']
def m1(name, prefix):
    for _ in range(2):
        print(name + prefix)

with ThreadPoolExecutor(2) as executor:
    executor.map(m1, repeat('abcd', len(names)), names)

If you find the repeat syntax to be awkward, you have a couple of alternatives:

with ThreadPoolExecutor(2) as executor:
    for name in names:
        executor.submit(m1, 'abcd', name)

OR

with ThreadPoolExecutor(2) as executor:
    executor.map(lambda name: m1('abcd', name), names)

In all cases, the with block will implicitly call executor.shutdown, which will wait for all the tasks to complete.

As a rule, don't call a variable list: it will shadow the name of the builtin class.

Upvotes: 3

xpa1492
xpa1492

Reputation: 1973

I am not sure if I completely understand what you are looking to achieve. My understanding is that you want to start a separate thread for each value in your list, so each value gets processed "in parallel". I modified your main1 function to do so:

def main1():
  threads = [Thread(target=m1,args=('abcd',x)) for x in list]
  for thread in threads: thread.start()
  for thread in threads: thread.join()

threads = [Thread(target=m1,args=('abcd',x)) for x in list] creates a separate thread for each value in the list.

for thread in threads: thread.start() starts each thread.

for thread in threads: thread.join() makes sure each thread is finished before returning from the main1 function (if you would rathee return immediately, just delete this line).

Upvotes: 1

Related Questions