How to Parallelize a While loop in Python? Last Updated : 22 Apr, 2024 Comments Improve Suggest changes Like Article Like Report Parallelizing a while loop in Python involves distributing the iterations of a loop across multiple processing units such as the CPU cores or computing nodes to execute them concurrently. This can significantly reduce the overall execution time of the loop, especially for tasks that are CPU-bound or require heavy computation. In this article, we'll explore various approaches to parallelizing a while loop in Python using different libraries and techniques. How to Parallelize a While loop in Python?Below, are the methods to explain how to Parallelise a while loop in Python: Parallelize a While loop Using concurrent.futuresIn this example, the below code uses ThreadPoolExecutor to parallelize a loop in Python. The function GFG represents the task to be performed in each iteration. The Geek function defines the loop's range and submits tasks to the executor for parallel execution. Each task corresponds to an iteration of the loop, processing a specific range defined by the start and end parameters. Python3 from concurrent.futures import ThreadPoolExecutor def GFG(start, end): print(f"Processing range ({start}, {end})") def Geek(): start = 0 end = 5 with ThreadPoolExecutor(max_workers=4) as executor: for i in range(start, end): executor.submit(GFG, i, i+1) if __name__ == "__main__": Geek() OutputProcessing range (0, 1) Processing range (1, 2) Processing range (2, 3) Processing range (3, 4) Processing range (4, 5) Parallelize a While loop Using MultiprocessingIn this example, below code parallelizes a While loop in Python using the multiprocessing module. It defines a function parallel_while_loop() which creates separate processes for each iteration of the loop using the Process class. Each process executes the GFG() function with iteration parameters. Python3 from multiprocessing import Process def GFG(start, end): # Perform computation or task within the loop print(f"Processing range ({start}, {end})") def parallel_while_loop(): # Define the range of iterations for the loop start = 0 end = 5 # Create a separate process for the each iteration processes = [] for i in range(start, end): process = Process(target=GFG, args=(i, i+1)) processes.append(process) process.start() # Wait for all processes to finish for process in processes: process.join() if __name__ == "__main__": parallel_while_loop() OutputProcessing range (0, 1) Processing range (1, 2) Processing range (2, 3) Processing range (4, 5) Processing range (3, 4) Comment More infoAdvertise with us Next Article How to Parallelize a While loop in Python? V vikas2gqb5 Follow Improve Article Tags : Python Python Programs Python-multithreading Practice Tags : python Similar Reads How to Emulate a Do-while loop in Python? 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