I have a task that outputs a tuple of data_frames, and other tasks that output individual data_frames. I'm trying to think of a good way to reduce them into one tuple of data_frames so I can use a single map task over them. So far, I've tried extending a list and coercing back to a tuple, and a few other methods that have failed. There's likely a parsimonious way to do this that I'm missing

How would you do it without Prefect? Can you share a code snippet showing that?

I wonder if I can just unpack the tuple to combine it:

task.map([*tupled_data_frames, data_frame2, data_frame3])

unpacking won't work because in 1.0 you can only construct a DAG in your Flow - you can try but I'm 95% sure it won't work

Flow run SUCCESS! All data frames were written to Snowflake. That's neat, I didn't think that would work.

oh wow, could you share your Flow code? just the flow constructor without actual tasks

Sure:

with Flow(
    FLOW_NAME,
    storage=Config.storage(project=PROJECT, file_name=FILE_NAME),
    result=S3Result(bucket="EDITED"),
    run_config=Config.run(),
) as flow:

    with case(save_snowflake, True):  # type: ignore

        load_snowflake.map(
            data_payload=[*reservations, owners, properties, amenities],
            drop=unmapped(drop_snowflake),
        )

thanks for sharing!