How does NumPy handle large array slicing without performance loss?

NumPy uses view-based slicing with stride arithmetic to avoid copying large arrays.

Even for large arrays, slicing only modifies metadata (shape, strides, offset). This makes slicing operations constant-time regardless of array size. However, repeated slicing may degrade locality and performance.