👋 is it possible to create an annotated

FlyteSchema

object that also includes metadata on whether a particular column is nullable vs required, along with its type?

can you take a look at the structured dataset object instead? structured datasets support a broader set of types.

thanks for the response - can you share an example of how i can annotate a structured dataset to also include info on whether null values are allowed? dont see anything on this topic in the documentation

alt: py 3.9 supports js style unions

field: str | None

you should be able to use optional types in structured dataset columns yes.

@lively-sundown-82704 is this what you want?

cols = kwtypes(Name=str, Age=typing.Optional[int], Height=int)


@task
def get_df(a: int) -> Annotated[pd.DataFrame, cols]:
    return pd.DataFrame({"Name": ["Tom", "Joseph"], "Adg": [a, None], "Height": [160, 178]})

yeah thats what im looking for! for now we're not relying on flyte to perform the actual enforcement of types - our application can handle that after serialization / deserialization - but it would be great if in the future we can have some sort of guarantee that e.g. a structured dataset does not contain any nulls after deserialization if the column isnt optional

Have you try Pandera plugin? it provides a flexible and expressive interface for defining schemas for tabular data. https://docs.flyte.org/projects/cookbook/en/latest/auto/integrations/flytekit_plugins/pandera_examples/index.html