What approaches and tools are used in developing and optimizing CPU-intensive tasks?

The following approaches and tools are used in Python for developing and optimizing tasks with high CPU load:

• Code profiling: using modules cProfile, profile to identify bottlenecks.
• Algorithm optimization: choosing more efficient algorithms and data structures.
• Using multiprocessing: the multiprocessing module allows running multiple processes, bypassing the GIL limitation.
• Using native extensions: writing critical sections in C/C++ or using libraries like NumPy, which are implemented in C.
• Asynchronous programming: for tasks with I/O waiting, to avoid blocking the CPU.

Example of using multiprocessing:

from multiprocessing import Pool

def heavy_computation(x):
    # some resource-intensive function
    return x * x

if __name__ == '__main__':
    with Pool(4) as p:
        results = p.map(heavy_computation, range(10))
    print(results)

This approach allows efficient utilization of multiple CPU cores.