In Python security, how do I parallelize workloads?

Learn how to effectively parallelize workloads in Python to enhance performance and efficiency, especially in security-related applications.

Python, parallelization, workloads, security, multiprocessing, threading, performance, efficiency


import multiprocessing

def worker_function(data):
    # Simulate a workload
    print(f"Processing {data}")

if __name__ == "__main__":
    data_list = ['task1', 'task2', 'task3', 'task4']
    # Create a pool of worker processes
    with multiprocessing.Pool(processes=4) as pool:
        pool.map(worker_function, data_list)
    

Python parallelization workloads security multiprocessing threading performance efficiency