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https://issues.apache.org/jira/browse/BEAM-11839?focusedWorklogId=585264&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-585264
]
ASF GitHub Bot logged work on BEAM-11839:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 19/Apr/21 17:10
Start Date: 19/Apr/21 17:10
Worklog Time Spent: 10m
Work Description: ibzib commented on a change in pull request #14552:
URL: https://github.com/apache/beam/pull/14552#discussion_r616027375
##########
File path: sdks/python/apache_beam/dataframe/frames_test.py
##########
@@ -37,71 +37,109 @@
})
+def _get_deferred_args(*args):
+ return [
+ frame_base.DeferredFrame.wrap(
+ expressions.ConstantExpression(arg, arg[0:0])) for arg in args
+ ]
+
+
class DeferredFrameTest(unittest.TestCase):
- def _run_test(self, func, *args, distributed=True, expect_error=False):
- deferred_args = [
- frame_base.DeferredFrame.wrap(
- expressions.ConstantExpression(arg, arg[0:0])) for arg in args
- ]
+ def _run_error_test(self, func, *args):
+ """Verify that func(*args) raises the same exception in pandas and in Beam.
+
+ Note that for Beam this only checks for exceptions that are raised during
+ expression generation (i.e. construction time). Execution time exceptions
+ are not helpful."""
+ deferred_args = _get_deferred_args(*args)
+
+ # Get expected error
try:
- expected = func(*args)
+ _ = func(*args)
except Exception as e:
- if not expect_error:
- raise
expected = e
else:
- if expect_error:
- raise AssertionError(
- "Expected an error but computing expected result successfully "
- f"returned: {expected}")
+ raise AssertionError(
+ "Expected an error but computing expected result successfully "
+ f"returned: {expected}")
Review comment:
Wouldn't `expected` be undefined here now?
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Issue Time Tracking
-------------------
Worklog Id: (was: 585264)
Time Spent: 2h 50m (was: 2h 40m)
> Attach a "reason" message to Singleton partitioning
> ---------------------------------------------------
>
> Key: BEAM-11839
> URL: https://issues.apache.org/jira/browse/BEAM-11839
> Project: Beam
> Issue Type: Improvement
> Components: sdk-py-core
> Reporter: Brian Hulette
> Priority: P2
> Labels: dataframe-api
> Time Spent: 2h 50m
> Remaining Estimate: 0h
>
> When Singleton partitioning is required, we should be able to attach a reason
> to it so we can raise a helpful message to the user later, e.g.
> {{partitionings.Singleton(reason="Only 'pearson' correlation can be computed
> in a distributed manner, other methods require Singleton partitioning")}}
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