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schrockn avatar schrockn commented on May 18, 2024

So I think this will be an excellent issue for you to work through some of the abstractions.

Currently this function creates a dependency between two dataframe-flavored solids:

def create_dagster_pd_dependency_input(solid):
    check.inst_param(solid, 'solid', Solid)

    def dependency_input_fn(context, arg_dict):
        check.inst_param(context, 'context', DagsterExecutionContext)
        path = check.str_elem(arg_dict, 'path')
        frmt = check.str_elem(arg_dict, 'format')

        df = _read_df(path, frmt)

        context.metric('rows', df.shape[0])

        return df

    return create_single_source_input(
        name=solid.name,
        source_fn=dependency_input_fn,
        argument_def_dict={
            'path': types.PATH,
            'format': types.STRING,
        },
        depends_on=solid,
        source_type='CSVORPARQUET',
    )

This should instead construct two separate sources for the input. One CSV, one Parquet. (Also adding JSON would make sense etc).

from dagster.

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