Careful considerations need to be made while implementing multiprocessing reduction operators in Python, especially if the program utilizes task queues and result queues to facilitate communication across the consumer processes.
The operations of various real-world problems resemble reduction operators, and the use of concurrency and parallelism for these problems could greatly improve efficiency and thus productivity of the programs processing them. It is therefore important to be able to identify these problems, and relate back to the concept of reduction operators to implement their solutions.
In the next chapter, we will be discussing a specific real-world application for multiprocessing programs in Python: image processing. We will be going over the basic ideas behind image processing and how concurrency—specifically multiprocessing—could be applied...