yeandy commented on a change in pull request #16615:
URL: https://github.com/apache/beam/pull/16615#discussion_r806222736
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File path: sdks/python/apache_beam/dataframe/transforms_test.py
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@@ -73,29 +74,52 @@ def df_equal_to(expected):
class TransformTest(unittest.TestCase):
- def run_scenario(self, input, func):
+ def run_scenario(self, input, func, check_subset=False):
+ """
+ In order for us to perform non-deferred operations, we have
+ to enumerate all possible categories, even if they are
+ unobserved. The default Pandas implementation on the other hand
+ does not produce unobserved columns. This means when conducting
+ tests, we need to account for the fact that the Beam result may
+ be a superset of that of the Pandas result.
+
+ When ``check_subset`` is set to ``True``, we will only
+ check that all of the columns in the Pandas implementation is
+ contained in that of the Beam implementation.
Review comment:
No worries! The logic I added can support verifying if they are all 0s
or NaNs (or other values), depending on the expected operation behavior.
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