What is meant by time-limited processor tasks, and how to work with them?

Tasks limited by CPU time, are those for which the main constraint is the processor's runtime, not, for example, I/O or network waiting. Such tasks heavily utilize the CPU and require optimization of computations.

How to work with them in Python:

• Use efficient algorithms and data structures to reduce the number of operations.
• Profile the code (e.g., with cProfile) to find bottlenecks.
• Use multiprocessing if necessary (multiprocessing module), as GIL limits multithreading in CPU-bound tasks.
• Use native extensions (Cython, Numba) to speed up critical sections.
• Use libraries with optimized code (NumPy, pandas) instead of pure Python.

Example of using multiprocessing for a CPU-bound task:

from multiprocessing import Pool

def heavy_computation(x):
    # Some intensive computation
    return x * x

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