python parallel for loop Use the multiprocessing Module, Use the joblib Module and Use the asyncio Module to Parallelize the for Loop in Python Example with demo.
python parallel for loop – Quick and Easy Parallelization in Python
python parallel for loop : Parallel for Loop in Python. This post will cover the implementation of a for loop with multiprocessing and with multithreading.
We will be making multiple requests.
Use the multiprocessing Module to Parallelize the for Loop in Python
Example
import multiprocessing
def sumall(value):
return sum(range(1, value + 1))
get_ranks = multiprocessing.Pool()
answer = get_ranks.map(sumall,range(0,5))
print(answer)
Result
0, 1, 3, 6, 10
Use the joblib Module to Parallelize the for Loop in Python
Example
from joblib import Parallel, delayed
import math
def get_ranks(i, j):
time.sleep(1)
return math.sqrt(i**j)
Parallel(n_jobs=2)(delayed(get_ranks)(i, j) for i in range(5) for j in range(2))
Result
[1.0, 0.0, 1.0, 1.0, 1.0, 1.4142135623730951, 1.0, 1.7320508075688772, 1.0, 2.0]
Don’t Miss : For Loop Increment By 2 In Python
Use the asyncio Module to Parallelize the for Loop in Python
Example
import asyncio
import time
def background(f):
def wrapped(*args, **kwargs):
return asyncio.get_event_loop().run_in_executor(None, f, *args, **kwargs)
return wrapped
@background
def get_ranks(argument):
time.sleep(2)
print('function finished for '+str(argument))
for i in range(10):
get_ranks(i)
print('loop finished')
Result
ended execution for 4 ended execution for 8 ended execution for 0 ended execution for 3 ended execution for 6 ended execution for 2 ended execution for 5 ended execution for 7 ended execution for 9 ended execution for 1
I hope you get an idea about python parallel for loop.
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