Python Parallel Programming Cookbook by 2015

Author:2015
Language: eng
Format: epub, mobi
Publisher: Packt Publishing

In the main program, we execute the task that will be performed in a sequential mode:

if __name__ == "__main__": for item in number_list: evaluate_item(item)

Also, in a parallel mode, we will use the concurrent.futures module's pooling capability for a thread pool:

with concurrent.futures.ThreadPoolExecutor(max_workers=5)\ as executor: for item in number_list: executor.submit(evaluate_item, item)

The ThreadPoolExecutor executes the given task using one of its internally pooled threads. It manages five threads working on its pool. Each thread takes a job out from the pool and executes it. When the job is executed, it takes the next job to be processed from the thread pool.

When all the jobs are processed, the execution time is printed:

print ("Thread pool execution in " + \ str(time.clock() - start_time_1), "seconds")

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