Hands-On Penetration Testing with Python

Multiprocess pooling

One of the coolest features of multiprocessing libraries is pooling. This lets us distribute the tasks evenly across all the processor cores, without having to worry about the number of processes that are run actively at one time. This implies that this module has the ability to spawn a group of processes in a batch. Let's say that we define the batch size as 4, which is the number of processor cores we may have. This means that, at any time, the maximum number of processes that can be executed is four and if one of the processes completes its execution, meaning we now have three running processes, the module automatically picks the next set of processes to make the batch size equal to four again. The process will continue ...