Problem Statement
For performance, when do you choose threading versus multiprocessing in Python?
Explanation
Threads work best for I O bound tasks, like network calls or disk waits. While one thread blocks, others can run, and the program makes progress. The Global Interpreter Lock limits true parallel CPU execution, but I O overlap still helps a lot.
For CPU bound work, use multiprocessing to run multiple processes that bypass the Global Interpreter Lock. Share data carefully, batch work to reduce pickling costs, and consider using native extensions when possible.
Code Solution
SolutionRead Only
# I O bound: threading # CPU bound: multiprocessing # mix with concurrent.futures for a simple API
