Bug: unexpected behavior with `seed_random`

[vkcku]

    name = Use(ModelFactory.__random__.choice, ["rule", "group_rule", "misc_rule"])
    color = Use(ModelFactory.__random__.choice, ["green", "red", "purple"])
    type = Use(ModelFactory.__random__.choice, ["input", "checkbox", "list", "link"])

shouldn't ModelFactory.seed_random(10) make the above work?

it only works doing like @Alc-Alc said

    name = lambda: RuleFactory.__random__.choice(["rule", "group_rule", "misc_rule"])
    color = lambda: RuleFactory.__random__.choice(["green", "red", "purple"])
    type = lambda: RuleFactory.__random__.choice(["input", "checkbox", "list", "link"])

But this gives an warning: https://docs.astral.sh/ruff/rules/lambda-assignment/ and it's a little bit ugly.

Originally posted by @JobaDiniz in https://github.com/litestar-org/polyfactory/discussions/578#discussioncomment-10366326

The use of Use doesn't result in deterministic behavior even if one calls BaseFactory.seed_random(some_seed). This is due to how we're implementing seed_random. We create a new Random instance with the given seed instead of reseeding the existing instance. This means that the cls.random.choice function that's referenced is the method associated with the Random instance before we call seed_random. Thus, you don't get the deterministic behavior.

This should be fixed so that seed_instance reseeds the existing random instance we have instead of creating a new one.

[priyankc]

@guacs I've generated a patch along with a repro test case to verify patch. Like you mentioned in the issue, avoiding new Random instance fixed it.

Happy to raise a PR, or cool if you want to do it. It's a simple fix. Please let me know.

More details here: https://workback.ai/litestar-org/polyfactory/issues/580

[priyankc]

@guacs I was working on another PR and thought I would just go ahead and create a PR to save you some work. I've created the PR against my fork.