feat: Export Results as Dataframe #100
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Pipeline failure fix is raised here - #99 |
…ython into users/priya/results-dataframe-utility
SSSantosh18
requested changes
Mar 6, 2025
| results: The list of results to normalize. | ||
| Returns: | ||
| A Pandas DataFrame with the normalized queried results. |
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add documentation for the code structure
| expected_results_dict = [] | ||
| for result in results: | ||
| expected_results_dict.append(result.dict(exclude_unset=True)) | ||
| expected_results_dataframe = pd.json_normalize(expected_results_dict, sep=".") |
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lets manually create a df for expected data, it helps see the actual df structure
| keywords=[], | ||
| ), | ||
| Result( | ||
| status=Status(status_type=StatusType.PASSED), |
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there are some static methods available inside Status like Status.Passed(). It can be used
| assert isinstance(results_dataframe, pd.DataFrame) | ||
| assert len(results_dataframe) == 3 | ||
| assert len(results_dataframe.columns.tolist()) == 7 | ||
| assert results_dataframe.equals(expected_results_dataframe) |
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a assert function part of pandas library was used in products utility. we can make use of that
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| @pytest.mark.enterprise | ||
| class TestTestmonitorDataframeUtilities: | ||
| def test__convert_results_to_dataframe__returns_results_dataframe(self, results): |
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add one test where the result contains all the fields value set
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What does this Pull Request accomplish?
This PR adds utility to export Results as a normalized pandas Dataframe.
Why should this Pull Request be merged?
This utility can be useful to get the results data in the form of a Dataframe which can be useful for further processing.
What testing has been done?
Unit tests are included.