Hi All, When the repr of an array is shown, currently the dtype and shape are explicitly listed if these cannot be directly inferred from the list that is shown, i.e., if the dtype is not float64 or int64, and if the size of the array is zero, but the shape not the simple (0,). For instance, ``` np.empty((10,2,0), dtype="i2") array([], shape=(10, 2, 0), dtype=int16) ``` I propose to also show the shape for the (rare) case that an array is summarized, i.e., when it has more than the default threshold of 1000 elements, and elements are replaced by `...`. The logic is that also in that case it is no longer clear what the shape actually is, which is useful information (e.g., if working in a notebook -- which is the original use case at https://github.com/numpy/numpy/issues/27461). I have a PR for that at https://github.com/numpy/numpy/pull/27482 which would lead to the following: ``` np.arange(1001) array([ 0, 1, 2, ..., 998, 999, 1000], shape=(1001,)) ``` Just to be sure: this PR causes *no* change for any arrays with sizes less than a 1000, so I do not believe this change will lead to a lot of unnecessary churn for down-stream packages. Indeed, between numpy and astropy (which has lots of doctests), the only changes to (doc)tests that were needed are the very few for arrays where the "threshold" is explicitly exceeded. One irritant is that the shape is not an argument that can be passed in to an `np.array` call. While this is just as much the case for zero-sized arrays, perhaps a better solution would be to move the shape information out of the parentheses, e.g., using ``...) # shape=(...)``. I can change the PR to do that if that's the consensus. All the best, Marten