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.
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Use the multiprocessing Module to Parallelize the for Loop in Python
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)
0, 1, 3, 6, 10
Use the joblib Module to Parallelize the for Loop in Python
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))
[1.0, 0.0, 1.0, 1.0, 1.0, 1.4142135623730951, 1.0, 1.7320508075688772, 1.0, 2.0]
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Use the asyncio Module to Parallelize the for Loop in Python
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')
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
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