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Defaults id_column to None for PIGs & tests - #141
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| class TestPigTablesGeneration: | ||
| @pytest.mark.parametrize("id_col_name", [None, "col_id"]) # test None as this is the default value in generate pig tabels | ||
| def test_col_id(self, id_col_name): |
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Suggested change
| deftest_col_id(self, id_col_name): | |
| deftest_col_id(self, id_col_name: str|None): |
This is only possible for python 3.10 and above. I am wondering should I use this or the older version by importing typing and using typing.Union[str, None] for backwards compatibility reasons ? Or how does that actually work ?
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You could use Optional instead, which has the same functionality as Union, but is more readable.
Suggested change
| deftest_col_id(self, id_col_name): | |
| deftest_col_id(self, id_col_name: Optional[str]): |
| 'avg_target': [0.0, 0.5, 1.0, 0.0, 0.6666666666666666, 0.0, 1.0, 0.0] | ||
| }) | ||
| pd.testing.assert_frame_equal(out, expected) No newline at end of file |
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| pd.testing.assert_frame_equal(out, expected) | |
| pd.testing.assert_frame_equal(out, expected) | |
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Story title
Remove mandatory id column #135
Changes made
Altered the calculate_pig_table & generate_pig_tables method such that the column_id_name is no longer needed, it was not really needed for the calculations in the background anyway.
Added a test in order to check if it still gives back the same results than before.
How does the solution address the problem
This PR provides the column_id_name by default with None. In that way, the Data scientist can just forget about the column_ID and the code still is backwards compatible.
Linked issues
Resolves#135