BUG: Stable ScalarType ordering
#29761
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Can we have a test that asserts the hard-coded sorted order? |
ngoldbaum
reviewed
Sep 18, 2025
| (np.bytes_, np.str_), | ||
| (np.str_, np.void), | ||
| # bouncy castles | ||
| (np.datetime64, np.timedelta64), |
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Total quibble but I think you can write this with just a single static list and then generate these tuples with e.g. itertools.pairwise.
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I wanted to do that at first. But I then decided against that because I didn't want to set the (IMO arbitrary) "kind" group ordering in stone (bool < complexfloating < np.floating < np.signedinteger < bouncy castles < object < flexible < unsignedinteger).
ngoldbaum
approved these changes
Sep 18, 2025
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The key used to sort
np.ScalarTypeis not unique (e.g.int64andlonglongon linux both have key('i', '8')). To remove duplicates,setis used, whose iteration order depends on the hashes of the containing scalartype classes. So in case of ties, the hash would be the tiebreaker. The problem is that these hashes are arbitrary, leading to differences inScalarTypeorder between platforms, python versions, machines, etc.In case you're wondering why I care: Stubtest is currently reporting errors for
ScalarTypefor certain platform and python versions: https://github.com/numpy/numtype/actions/runs/17778048694/job/50530549124?pr=706. And I'm sure you can imagine that it wasn't easy to figure out what was going on here (especially if you consider the stubtest error spaghetti output, but I digress). Hence the pedantic "backport candidate" label ;)