How does NumPy handle internal memory strides during transpose operations?

Transpose swaps stride metadata without moving underlying data.

Instead of copying memory, transpose simply rearranges how strides are interpreted. This means that row-major data becomes column-accessible without relocation. However, this can lead to non-contiguous memory layouts, affecting downstream performance.