pitrou commented on issue #48409:
URL: https://github.com/apache/arrow/issues/48409#issuecomment-3654615515
There's one complication that we should be careful about: if we change the
meaning the `__eq__`, then the use of equality in boolean context will result
in calling the `__bool__` of the result array (which is always true unless the
array is empty). `if x == y` would then always succeed if the arrays are not
empty, which I hope we agree is extremely error-prone:
```python
>>> bool(np.array([False, False, False]))
Traceback (most recent call last):
Cell In[15], line 1
bool(np.array([False, False, False]))
ValueError: The truth value of an array with more than one element is
ambiguous. Use a.any() or a.all()
>>> bool(pa.array([False, False, False]))
True
```
So, if we change the meaning the `__eq__` on arrays, we must also deprecate
`__bool__` like NumPy did. The cost and annoyance of that change may outweigh
the benefits of different `__eq__` semantics.
Perhaps it would be less disruptive if `__eq__` continues doing the Pythonic
thing of returning a bool, and `equals` is changed to call the compute
function. But that would make us different from NumPy (is that a problem?).
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