Combine Pool map with shared memory Array in Python multiprocessing

In Step 2, we create a shared memory array using the Array class from the multiprocessing module. The array type is specified as 'i' for integers, and the size is set to shared_array_size.
In Step 3, we define a function (process_data) that processes a given index and modifies the corresponding element in the shared memory array.
Finally, we print the results and the contents of the shared memory array after processing.
By using a shared memory array, you enable multiple processes to work on the data simultaneously, improving the efficiency of parallel processing tasks. This approach is particularly useful when dealing with large datasets or computationally intensive tasks.
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