Numpy chose to violate the principal of equality by having __eq__ not return a bool. So a numpy type can't be used reliably outside of the numpy DSL. -gps On Tue, Dec 22, 2020, 11:51 AM Alan G. Isaac <alan.isaac@gmail.com> wrote:
Here, `seq1 == seq2` produces a boolean array (i.e., an array of boolean values). hth, Alan Isaac
On 12/22/2020 2:28 PM, Ivan Pozdeev via Python-Dev wrote:
You sure about that? For me, bool(np.array) raises an exception:
In [12]: np.__version__ Out[12]: '1.19.4'
In [11]: if [False, False]==np.array([False, False]): print("foo") <...>
ValueError: The truth value of an array with more than one element is ambiguous.
Use a.any() or a.all()
The following test fails because because `seq1 == seq2` returns a (boolean) NumPy array whenever either seq is a NumPy array.
import unittest import numpy as np unittest.TestCase().assertSequenceEqual([1.,2.,3.], np.array([1.,2.,3.]))
I expected `unittest` to rely only on features of a `collections.abc.Sequence`, which based on https://docs.python.org/3/glossary.html#term-sequence, I believe are satisfied by a NumPy array. Specifically, I see no requirement that a sequence implement __eq__ at all much less in any
On 22.12.2020 21:52, Alan G. Isaac wrote: particular way.
In short: a test named `assertSequenceEqual` should, I would think,
work for any sequence and therefore (based on the available documentation) should not
depend on the class-specific implementation of __eq__.
Is that wrong?
Thank you, Alan Isaac _______________________________________________ Python-Dev mailing list -- python-dev@python.org To unsubscribe send an email to python-dev-leave@python.org https://mail.python.org/mailman3/lists/python-dev.python.org/ Message archived at
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