Tier 2 optimizer: refactor to reuse constant symbols

Feature or enhancement

Proposal:

Right now the optimizer loses information across constant values. Say for example

def test_propagate_constants_sources(self):
    def thing(unused):
        x = 0
        for _ in range(100):
            x = 1
            y = Foo.attr + Foo.attr
            # Type information of `Foo_attr` is not propagated to here.
            z = Foo.attr + Foo.attr
        return x
    
    class Foo:
        attr = 1

    res, ex = self._run_with_optimizer(thing, 1)
    opnames = list(iter_opnames(ex))
    self.assertIsNotNone(ex)
    guard_type_version_count = opnames.count("_GUARD_BOTH_INT")
    # Test fails, because we insert 2 type guards instead of 1 (ie type information is not propagated, and guards are repeated)
    self.assertEqual(guard_type_version_count, 1)

After we promote Foo.attr to constants, we don't keep source information, so we don't keep track that the first Foo.attr is the same as the subsequent ones. Then LOAD_CONST_INLINE loads a brand new constant symbol each time, with no information.

https://github.com/python/cpython/blob/main/Python/optimizer_bytecodes.c#L422

A possible solution would be to keep some sort of ID for all constant promotions around.

Has this already been discussed elsewhere?

No response given

Links to previous discussion of this feature:

No response