How does NumPy handle multi-dimensional slicing internally?

Multi-dimensional slicing adjusts strides and offsets without copying data.

When slicing an ndarray, NumPy does not copy memory but recalculates the view's shape, strides, and starting pointer. Each dimension contributes to stride computation, enabling efficient subarray creation. However, complex slicing may break contiguity and degrade performance.