Which approach is better for I/O bound tasks? a) multi-threading b) multi-processing c) both perform well d) neither is suitable
Understand the Problem
The question is asking about the best approach for handling input/output bound tasks among the provided options, which include multi-threading, multi-processing, both options performing well, or neither being suitable.
Answer
Both perform well, with a slight preference for multithreading.
The final answer is both perform well for I/O-bound tasks, with multithreading generally being a marginally preferred choice due to simplicity and lower memory overhead.
Answer for screen readers
The final answer is both perform well for I/O-bound tasks, with multithreading generally being a marginally preferred choice due to simplicity and lower memory overhead.
More Information
For I/O-bound tasks, both multithreading and multiprocessing can improve performance because they allow the main task to continue running while waiting for slow I/O operations. However, multithreading tends to have lower resource overhead due to a single memory space.
Tips
A common mistake is choosing multiprocess over multithread for I/O-bound tasks due to misconceptions about CPU-bound constraints in Python's Global Interpreter Lock (GIL). Multithreading usually works sufficiently for I/O-bound tasks.
Sources
- python - Multithreading vs multiprocessing in I/O bound processes - stackoverflow.com
- Which approach is better for I/O bound tasks? a) multi-threading b ... - quizgecko.com
- Python Multithreading Tutorial: Concurrency and Parallelism | Toptal® - toptal.com
AI-generated content may contain errors. Please verify critical information
