kszucs commented on a change in pull request #8349:
URL: https://github.com/apache/arrow/pull/8349#discussion_r502490505
##########
File path: python/pyarrow/tests/test_convert_builtin.py
##########
@@ -1903,18 +1946,40 @@ def test_dictionary_from_strings():
assert a.dictionary.equals(expected_dictionary)
-def _has_unique_field_names(ty):
- if isinstance(ty, pa.StructType):
- field_names = [field.name for field in ty]
- return len(set(field_names)) == len(field_names)
- else:
- return True
[email protected]('unit', ['s', 'ms', 'us', 'ns'])
+def test_duration_array_roundtrip_corner_cases(unit):
+ # Corner case discovered by hypothesis: there were implicit conversions to
+ # unsigned values resulting wrong values with wrong signs.
+ ty = pa.duration(unit)
+ arr = pa.array([-2147483000], type=ty)
+ restored = pa.array(arr.to_pylist(), type=ty)
Review comment:
Updated.
##########
File path: python/pyarrow/tests/test_convert_builtin.py
##########
@@ -1903,18 +1946,40 @@ def test_dictionary_from_strings():
assert a.dictionary.equals(expected_dictionary)
-def _has_unique_field_names(ty):
- if isinstance(ty, pa.StructType):
- field_names = [field.name for field in ty]
- return len(set(field_names)) == len(field_names)
- else:
- return True
[email protected]('unit', ['s', 'ms', 'us', 'ns'])
+def test_duration_array_roundtrip_corner_cases(unit):
+ # Corner case discovered by hypothesis: there were implicit conversions to
+ # unsigned values resulting wrong values with wrong signs.
+ ty = pa.duration(unit)
+ arr = pa.array([-2147483000], type=ty)
+ restored = pa.array(arr.to_pylist(), type=ty)
+ assert arr.equals(restored)
+
+
[email protected]
+def test_roundtrip_nanosecond_resolution_pandas_temporal_objects():
+ # corner case discovered by hypothesis: preserving the nanoseconds on
+ # conversion from a list of Timedelta and Timestamp objects
+ import pandas as pd
+
+ ty = pa.duration('ns')
+ arr = pa.array([9223371273709551616], type=ty)
+ data = arr.to_pylist()
+ assert isinstance(data[0], pd.Timedelta)
+ restored = pa.array(data, type=ty)
Review comment:
Updated.
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