the error message for accidentally irregular arrays is confusing

Someone using my code reported this error message, and I would have been able to track down the problem more quickly if the message had been more informative, maybe like ValueError: setting an irregularly shaped array with a non-object dtype instead of ValueError: setting an array element with a sequence.

>>> import numpy as np
>>> np.array([[0, 1], [2]]).dtype
dtype('O')
>>> np.array([[0, 1], [2]], dtype=int).dtype
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

[seberg]

The remaining corner case(s) are now also deprecated in master, so closing. The original case currently gives:

ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part.

which is probably not great, but much better than no information. Ideas for improvements welcome.

[njsmith]

@agriffing: I think we have a pretty good pile of evidence that there’s a problem here now 😃. Any interest in having a go at a making a solution?

On Mon, Feb 9, 2015 at 8:38 AM, argriffing [e-mail] wrote:

I also think we should seriously consider implementing #5353 https://github.com/numpy/numpy/issues/5353 (don’t create object arrays unless dtype=object is explicitly specified) and making it so np.ndarray only treats list objects specially, with tuples and other sequence types being treats as array elements instead.

A similar question again on the mailing list http://mail.scipy.org/pipermail/numpy-discussion/2015-February/072240.html, regarding over-coercion of arrays of tuples into high dimensional arrays.

— Reply to this email directly or view it on GitHub https://github.com/numpy/numpy/issues/5303#issuecomment-73541097.

Nathaniel J. Smith – http://vorpus.org