[Docs] Prevent using mutable default arguments in flytesnacks

[MortalHappiness]

Description

Mutable default arguments is a common anti-pattern in Python. See https://docs.python-guide.org/writing/gotchas/#mutable-default-arguments for details. We should prevent using it in flytesnacks.

For example:

https://github.com/flyteorg/flytesnacks/blob/2d73e2a0892a56efc4fe3649db942e8270ccfe8c/examples/advanced_composition/advanced_composition/map_task.py#L13

Are you sure this issue hasn't been raised already?

• Yes

Have you read the Code of Conduct?

• Yes

[runllm]

Description

Mutable default arguments is a common anti-pattern in Python. See Mutable Default Arguments for details. We should prevent using it in flytesnacks.

For example:

https://github.com/flyteorg/flytesnacks/blob/2d73e2a0892a56efc4fe3649db942e8270ccfe8c/examples/advanced_composition/advanced_composition/map_task.py#L13

Are you sure this issue hasn't been raised already?

• Yes

Have you read the Code of Conduct?

• Yes

Sources:

• [flytekit] Non-primitive defaults to workflows #910
• https://discuss.flyte.org/t/432244/is-it-not-possible-to-have-default-arguments-for-lists-on-wo/
• https://discuss.flyte.org/t/426645/anyone-using-latest-mypy-and-have-this-issue-with-namedtuple/

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[eapolinario]

@MortalHappiness , please see flyteorg/flytesnacks#1685 (comment) and let me know what you think.

OTOH, enabling this in flytekit should be a no-brainer.

[MortalHappiness]

@eapolinario I still don't think it is a good pattern, especially in flytesnacks, which is the documentation for examples. Examples with anti-patterns may mislead users that are not proficient in Python to write these code.

Actually, I found this problem when I was working on this PR:
flyteorg/flytekit#2401

I know that if the default argument is used in workflow like the following:

@task
def t1(a: list[int]) -> list[int]:
    return a


@workflow
def wf(a: list[int] = [1, 2, 3]) -> list[int]:
    a.append(4)
    return t1(a=a)

It will show that TypeError: 'Promise' object is not callable. Therefore the list will not be modified.

However, in the PR that I mentioned above, I need to handle the case of @dynamic and @task. Therefore, users may write the following code

@task
def t1(a: list[int] = [1, 2, 3]) -> list[int]:
    a.append(4)
    return a

@workflow
def wf() -> list[int]:
    t1()
    return t1()

Note that t1 is called twice. In this case, should the result of wf be [1, 2, 3, 4] or [1, 2, 3, 4, 4]? If we make the list immutable, then the result should be [1, 2, 3, 4], which causes no problems. But in Python's perspective, although this is an anti-pattern, the "correct" result should be [1, 2, 3, 4, 4]. If users are migrated from an existing Python project, they may be confusing why the result of wf is different after adding the @task and @workflow decorator. Therefore, in my PR, if the default argument is a non-hashable object and no inputs are provided, a FlyteAssertion is raised instead to prevent this anti-pattern.