Output column metadata

You can read and write the column descriptions and column typeclasses for your output datasets in Code Respository Transforms.

Updating column descriptions in Code Repository Transforms

You can add output column descriptions to your output datasets by providing the optional column_descriptions argument to the write_dataframe() function of the TransformOutput.

• This argument should be a dict ↗ with keys of column names and values of column descriptions. Column descriptions are limited up to 800 characters in length.
• The code will automatically compute the intersection of the column names available on your DataFrame ↗ and the keys in the dict ↗ you provide, so it will not try to put descriptions on columns that don't exist.

Example: Write column descriptions in Code Repository Transforms

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from transforms.api import transform, Input, Output


@transform(
    my_output=Output("/my/output"),
    my_input=Input("/my/input"),
)
def my_compute_function(my_input, my_output):
    my_output.write_dataframe(
        my_input.dataframe(),
        column_descriptions={
            "col_1": "col 1 description"
        }
    )

Column typeclasses

The column_typeclasses property gives back a structured Dict<str, List<Dict<str, str>>>, which maps column names to their column typeclasses.

• Each typeclass in the List is a Dict[str, str] object.
  • This Dict object must only use the keys "name" and "kind". Each of these keys maps to the corresponding string the user wants.

An example column_typeclasses value would be {"my_column": [{"name": "my_typeclass_name", "kind": "my_typeclass_kind"}]}.

Example: Read and write column descriptions and typeclasses in Code Repository Transforms

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from transforms.api import transform, Input, Output


@transform(
    my_output=Output("ri.foundry.main.dataset.my-output-dataset"),
    my_input=Input("ri.foundry.main.dataset.my-input-dataset"),
)
def my_compute_function(my_input, my_output):
    recent = my_input.dataframe().limit(10)

    existing_typeclasses = my_input.column_typeclasses
    existing_descriptions = my_input.column_descriptions

    my_output.write_dataframe(
        recent,
        column_descriptions=existing_descriptions,
        column_typeclasses=existing_typeclasses
    )