Allow to pass through columns

I have a dataframe with a lot of columns (>100) and would like to not need to specify all of them.
Would it be possiuble to support a strict = False mode and/or to specify types for multiple columns?

Maybe such an api:

class FeaturesForwardModelSchema(dy.Schema):
    claim = dy.String(primary_key=True, nullable=False)
    cost = dy.Int64(primary_key=True, nullable=False)
    dataframely_options: DataframelyOptions(strict=False)

df = pl.DataFrame({
    "claim": ["a"],
    "cost": [1],
    "extra_col": ["foo"],
})

df_validated = FeaturesForwardModelSchema.validate(df)
df_validated["extra_col"]

alternatively, maybe something like this?

FeaturesForwardModelSchema.validate(df, strict=False)

Although this could be quite annoying, needing to specify it every time

Start by tracing the FeaturesForwardModelSchema.validate entry point and the proposed DataframelyOptions configuration. Compare the two strict=False API alternatives and define how validation should retain unspecified columns; done means the example preserves extra_col while still validating claim and cost, with tests covering the chosen API.