Python 3 Object-Oriented Programming - Third Edition

Thread overhead

One final limitation of threads, as compared to the asynchronous system we will be discussing later, is the cost of maintaining each thread. Each thread takes up a certain amount of memory (both in the Python process and the operating system kernel) to record the state of that thread. Switching between the threads also uses a (small) amount of CPU time. This work happens seamlessly without any extra coding (we just have to call start() and the rest is taken care of), but the work still has to happen somewhere.

This can be alleviated somewhat by structuring our workload so that threads can be reused to perform multiple jobs. Python provides a ThreadPool feature to handle this. It is shipped as part of the multiprocessing library ...