loop6.py

# SuperFastPython.com
# example of a parallel for loop with the ProcessPoolExecutor class
import concurrent.futures

# execute a task
def task(value):
    # add your work here...
    # return a result, if needed
    return value

# protect the entry point
if __name__ == '__main__':
    # create the pool with the default number of workers
    with concurrent.futures.ProcessPoolExecutor() as exe:
        # issue some tasks and collect futures
        futures = [exe.submit(task, i) for i in range(50)]
        # process results as tasks are completed
        for future in concurrent.futures.as_completed(futures):
            print(f'>got {future.result}')
        # issue one task for each call to the function
        for result in exe.map(task, range(50)):
            print(f'>got {result}')
    # report that all tasks are completed
    print('Done')