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NumPy

The foundational Python library for fast numerical arrays and vectorized math.

When to use: Any numerical computation; every preprocessing or metric step.

Example: a = np.arange(1_000_000); a.sum() runs in ~1 ms vs ~50 ms for sum(range(1M)).

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