How would you optimize a Python function that is found to be CPU-bound during profiling?
- a) Use a Just-In-Time (JIT) compiler like PyPy.
- b) Increase the number of threads to parallelize the code.
- c) Optimize the algorithm or use data structures that are more efficient.
- d) Use a faster computer for running the code.
When a Python function is CPU-bound, the most effective optimization is usually to optimize the algorithm or use more efficient data structures. JIT compilation (a) can help in some cases, but it may not be as effective as algorithmic improvements. Increasing the number of threads (b) might help if the code can be parallelized, but this is not always the case. Using a faster computer (d) is generally not a solution to CPU-bound code as it doesn't address the underlying inefficiencies.
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