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 most suitable approach for handling input/output (I/O) bound tasks among the options of multi-threading, multi-processing, both, or neither. It is exploring the efficiency and appropriateness of these methods in the context of tasks that primarily involve waiting for I/O operations to complete.
Answer
Both multi-threading and multi-processing perform well for I/O bound tasks.
For I/O bound tasks, both multi-threading and multi-processing perform well.
Answer for screen readers
For I/O bound tasks, both multi-threading and multi-processing perform well.
More Information
Both approaches have their advantages: multi-threading can be simpler and has lower memory overhead, while multi-processing avoids the GIL in Python, which can be beneficial.
Tips
Avoid assuming one is always superior to the other without considering the specific requirements and constraints of the task.
Sources
- The web page with info on - Guide to concurrency and parallelism - toptal.com
- Multithreading vs multiprocessing in I/O bound processes - stackoverflow.com
- Threading or multiprocessing - Python discussion - discuss.python.org
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