I am really surprised at the resistance against defining `__eq__` on the target objects. Every time this problem has cropped up in code I was working on (including code part of very large corporate code bases) the obvious solution was to define `__eq__`. The only reason I can think of why you are so resistant to this would be due to poor development practices, e.g. adding tests long after the "main" code has already been deployed, or having a separate team write tests.

Regarding `__hash__`, it is a very bad idea to call `super().__hash__()`! Unless your `__eq__` also just calls `super().__eq__(other)` (and what would be the point of that?), defining `__hash__` that way will cause irreproducible behavior where *sometimes* an object that is equal to a dict key will not be found in the dict even though it is already present, because the two objects have different hash values. Defining `__hash__` as `id(self)` is no better. In fact, defining `__hash__` as returning the constant `42` is better, because it is fine if two objects that *don't* compare equal still have the same hash value (but not the other way around).

The right way to define `__hash__` is to construct a tuple of all the attributes that are considered by `__eq__` and return the `hash()` of that tuple. (In some cases you can make it faster by leaving some expensive attribute out of the tuple -- again, that's fine, but don't consider anything that's not used by `__eq__`.)

Finally, dataclasses get you all this for free, and they are the future.

On Sun, Jul 26, 2020 at 7:48 PM Henry Lin <hlin117@gmail.com> wrote:
@Steven D'Aprano All good ideas ☺ I'm in agreement that we should be building solutions which are generalizable.

Are there more concerns people would like to bring up when considering the problem of object equality?

On Sun, Jul 26, 2020 at 9:25 PM Steven D'Aprano <steve@pearwood.info> wrote:
On Sun, Jul 26, 2020 at 11:12:39PM +0200, Alex Hall wrote:

> There's another reason people might find this useful - if the objects have
> differing attributes, the assertion can show exactly which ones, instead of
> just saying that the objects are not equal.

That's a good point.

I sat down to start an implementation, when a fundamental issue with
this came to mind. This proposed comparison is effectively something
close to:

    vars(actual) == vars(expected)

only recursively and with provision for objects with `__slots__` and/or
no `__dict__`. And that observation lead me to the insight that as tests
go, this is a risky, unreliable test.

A built-in example:

    actual = lambda: 1  # simulate some complex object
    expected = lambda: 2  # another complex object
    vars(actual) == vars(expected)  # returns True

So this is a comparison that needs to be used with care. It is easy for
the test to pass while the objects are nevertheless not what you expect.

Having said that, another perspective is that unittest already has a
smart test for comparing dicts, assertDictEqual, which is automatically
called by assertEqual.


So it may be sufficient to have a utility function that copies
an instance's slots and dict into a dict, and then compare dicts. Here's
a sketch:

    d1 = vars(actual).copy()
    d1.update({key: value for key in actual.__slots__})
    # Likewise for d2 from expected
    self.assertEqual(d1, d2)

Make that handle the corner cases where objects have no instance dict or
slots, and we're done.

Thinking aloud here.... I see this as a kind of copy operation, and
think this would be useful outside of testing. I've written code to copy
attributes from instances on multiple occasions. So how about a new
function in the `copy` module to do so:

    copy.getattrs(obj, deep=False)

that returns a dict. Then the desired comparison could be a thin

    def assertEqualAttrs(self, actual, expected, msg=None):
        self.assertEqual(getattrs(actual), getattrs(expected))

I'm not keen on a specialist test function, but I'm warming to the idea
of exposing this functionality in a more general, and hence more useful,

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