Add validation mode for mapper #59
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rt-phb
reviewed
Jun 6, 2024
rt-phb
reviewed
Jun 11, 2024
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| def test_matching_mapping_with_casting(self, input_df, matching_mapping): |
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data types match so this should not trigger any casting, right? maybe test_matching_mapping_without_validation. Some use _with_validation suffix and some not. As all except two tests apply validation would remove the suffix as the class name already indicates that it is about validation.
| column_to_nullify = "col_d" | ||
| mapping_ = deepcopy(matching_mapping) | ||
| mapping_.append((column_to_nullify, column_to_nullify, T.StringType())) | ||
| mapped_df = Mapper(mapping_, mode="rename_and_validate", missing_column_handling="nullify").transform(input_df) |
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did you think about making the mode an enum, like:
Suggested change
| mapped_df = Mapper(mapping_, mode="rename_and_validate", missing_column_handling="nullify").transform(input_df) | |
| mapped_df = Mapper(mapping_, mode=MapperMode.RENAME_AND_VALIDATE, missing_column_handling="nullify").transform(input_df) |
same as above, no need to implement this now
This was referenced Jun 13, 2024
rt-phb
approved these changes
Jun 13, 2024
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Adds new mode for the Mapper transformer:
rename_and_validate:All built-in, custom transformations (except renaming) and casts are disabled. The Mapper only renames the columns and validates that the output data type is the same as the input data type. The transformation will fail if any spooq / custom transformations (except
as_is) are defined!