"setting an array element with a sequence" error could be improved.

[amueller]

This is a bit of a nitpick, but I think this would improve user-friendlyness.
Currently np.asarray([[1, 2], [2, 3, 4]], dtype=np.float) yields "setting an array element with a sequence."

I think it would be more helpful if it yielded something like "Can't create array from lists. Column length %d of column %d doesn't match column length %d."

I imagine the error bubbles up from somewhere deep in the code and makes perfect sense where it is raised. It is just something that comes up a lot, and a more friendly and / or informative message could be helpful. So maybe we could catch it further up and include more information if possible.

[argriffing]

This is a duplicate of #5303.

[amueller]

indeed, sorry for the noise.

[argriffing]

Re-opening in light of #5303 (comment).

There are a few different but related issues. One issue is explicit vs. implicit dtype=object array creation. The github issue for that is #5353 (also #6070, I see). Another issue is the possibility to create ndarrays of objects with conformable shapes without automatically peeking into those objects and trying to figure out what the user wants. That issue is #5933.

We could keep this issue open, for improving the error message for specific cases like np.asarray([[1, 2], [2, 3, 4]], dtype=np.float). If the error message could be special-cased for np.asarray(a, dtype=b) even for really specific kinds of a and b, this could be useful. For example, maybe a special case could apply when a is a Python list recursively containing more lists and numeric values (and maybe only when the all leaves of the tree defined by the list all share the same depth?) and where b is some simple numeric dtype.

Here are a few more cases that give the same error message, but which may or may not be in the scope of this issue.

>>> np.array([[[1, 2], [3, 4], [5, 6]], [[1], [2], [3]]], dtype=int)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

>>> np.array([[1, 2, 3], 4], dtype=int)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

>>> np.array([(1, 2), (2, 3, 4)], dtype=int)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: setting an array element with a sequence.

[amueller]

Thanks for your summary. I think we are on the same page.
Btw, my motivation was that this might be inside a library, and it might be very non-obvious to the user why a line is failing. I probably won't have time to work on this right now :-/

[argriffing]

Here's an analogous example with structured arrays, giving a different error message.

>>> np.array([[(1, 1), (2, 2)], [(2, 2), (3, 3), (4, 4)]], dtype=[('foo', '>i4'), ('bar', '>i4')])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: expected a readable buffer object

When the lists are conformable there is no error.

>>> np.array([[(1, 1), (2, 2), (3, 3)], [(2, 2), (3, 3), (4, 4)]], dtype=[('foo', '>i4'), ('bar', '>i4')])
array([[(1, 1), (2, 2), (3, 3)],
       [(2, 2), (3, 3), (4, 4)]], 
      dtype=[('foo', '>i4'), ('bar', '>i4')])

[amueller]

I wanna bump this in sight of the BoF in terms of directions. I think better error messages in general would be great, with this my "favorite" examples.

[rgommers]

Thanks @amueller. This has 31 thumbs up, clearly valuable - tagging for the next release to make sure it doesn't drift down the list again.

A new issue/strategy for better error messages in general would also be useful. Could be good to discuss during the sprint.

[amueller]

I tried to think about others and/or come up with general strategies but drew a blank. Maybe looking at highly voted stack overflow issues might help to find common problems? (Gonna do that for sklearn right now lol).

[amueller]

Hmm most errors are install errors or this one lol https://stackoverflow.com/search?q=%5Bnumpy%5D+error&tab=votes