I would like to share the first formal draft of
NEP 50: Promotion rules for Python scalars
with everyone. The full text can be found here:
NEP 50 is an attempt to remove value-based casting/promotion. We wish to replace it with clearer rules for the resulting dtype when mixing NumPy arrays and Python scalars. As a brief example, the proposal allows the following (unchanged):
>>> np.array([1, 2, 3], dtype=np.int8) + 100 np.array([101, 102, 103], dtype=np.int8)
While clearing up confusion caused by the value-inspecting behavior that we see sometimes, such as:
>>> np.array([1, 2, 3], dtype=np.int8) + 300 np.array([301, 302, 303], dtype=np.int16) # note the int16
Where 300 is too large to fit an
int8. As well as removing the special behavior of 0-D arrays or NumPy scalars:
>>> res = np.array(1, dtype=np.int8) + 100 >>> res.dtype dtype('int64')
This is the continuation of a long discussion (see the “Discussion” section), including the poll I once posted: Poll: Future NumPy behavior when mixing arrays, NumPy scalars, and Python scalars
I would be happy for any feadback, be it just editorial or fundamental discussion. There are many alternatives which I have tried to capture in the NEP.
For smaller edits, don’t hesitate to open a NumPy PR, or propose edits on my branch (you can use the edit button to create a PR): numpy/nep-0050-scalar-promotion.rst at nep50 · seberg/numpy · GitHub
An important part of moving forward will be assessing the real world impact. To start that process, I have created a branch as a draft PR (at this time): API: Introduce optional (and partial) NEP 50 weak scalar logic by seberg · Pull Request #21626 · numpy/numpy · GitHub
It is missing some parts, but should allow preliminary testing. The main missing part is that the integer warnings and errors are less strict than proposed in the NEP.
It would be invaluable to get a better idea to what extent existing code, especially end-user code, is affected by the proposed changes.
Thanks in advance for any input! This is a big, complicated proposal, but finding a way forward will hopefully clear up a source of confusion and inconsistencies that make both maintainers and users life harder.