[Python] Add unittests for converter arrays with pandas masks

[asfimport]

Cover the changes in #11465

cc @amol-

Reporter: Krisztian Szucs / @kszucs
Assignee: Alessandro Molina / @amol-

PRs and other links:

• GitHub Pull Request #11481

_{Note: This issue was originally created as ARROW-14388. Please see the migration documentation for further details.}

[asfimport]

Alessandro Molina / @amol-:
@jorisvandenbossche @kszucs  I was able to reproduce the segfault using the provided test. I confirmed the test reproduces the issue by reverting the changes in #11465 and triggering the segfault.

I also added an additional check, that I verified does prevent the segfault replacing it with a proper Invalid("Invalid mask type") error to catch future regressions.

I couldn't find a way to trigger that error with current codebase on master, so it ends up being uncovered by a test. That's because with current codebase anything that is not a numpy.array gets converted to it so there is no way to end up into that situation normally. Ideally it's a kind of issue I would simulate by monkeypatching, but given that everything runs within Cython I can't monkeypatch get_values anyway the check is there and should prevent us from reintroducing the same issue in the future.

[asfimport]

Alessandro Molina / @amol-:
PS: If you are wondering about the pandas.Series values, those are exactly took from the pyspark test that triggered the segfault for me

test_createDataFrame_column_name_encoding (pyspark.sql.tests.test_arrow.ArrowTests) ... 
ARRAY 0    1
Name: a, dtype: int64 TYPE <class 'pandas.core.series.Series'>
---
MASK 0    False
Name: a, dtype: bool TYPE <class 'pandas.core.series.Series'>


Had test failures in pyspark.sql.tests.test_arrow ArrowTests with /Users/amol/ARROW/venv/bin/python3; see logs. 

[asfimport]

Joris Van den Bossche / @jorisvandenbossche:
Issue resolved by pull request 11481
#11481