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test: restore original udf in the remote function test, use supported type in the test data #996

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test: restore original udf in the remote function test, use supported type in the test data #996

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c59bbe5
test: fix test_df_apply_axis_1_complex by converting numpy value
chelsea-lin Sep 17, 2024
0b1d0ff
undo all changes
chelsea-lin Sep 24, 2024
f549683
improve numpy value handling in gcf code
shobsi Sep 25, 2024
24ca8b7
Merge remote-tracking branch 'github/main' into main_chelsealin_remot…
shobsi Sep 25, 2024
0eb0914
enable the multiindex axis=1 test back
shobsi Sep 25, 2024
8fae976
nit reword comment
shobsi Sep 25, 2024
c6ed768
Revert "improve numpy value handling in gcf code"
shobsi Sep 27, 2024
f8ce74f
Merge remote-tracking branch 'github/main' into main_chelsealin_remot…
shobsi Sep 27, 2024
4175aea
Merge branch 'main' into main_chelsealin_remotetest
shobsi Sep 27, 2024
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42 changes: 24 additions & 18 deletions tests/system/large/test_remote_function.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1670,7 +1670,11 @@ def analyze(row):
(3, 4): ["pq", "rs", "tu"],
(5.0, "six", 7): [8, 9, 10],
'raise Exception("hacked!")': [11, 12, 13],
}
},
# Default pandas index has non-numpy type, whereas bigframes is
# always numpy-based type, so let's use the index compatible
# with bigframes. See more details in b/369689696.
index=pandas.Index([0, 1, 2], dtype=pandas.Int64Dtype()),
),
id="all-kinds-of-column-names",
),
Expand All @@ -1681,17 +1685,22 @@ def analyze(row):
"y": [1.5, 3.75, 5],
"z": ["pq", "rs", "tu"],
},
index=pandas.MultiIndex.from_tuples(
[
("a", 100),
("a", 200),
("b", 300),
]
index=pandas.MultiIndex.from_frame(
pandas.DataFrame(
{
"idx0": pandas.Series(
["a", "a", "b"], dtype=pandas.StringDtype()
),
"idx1": pandas.Series(
[100, 200, 300], dtype=pandas.Int64Dtype()
),
}
)
),
),
id="multiindex",
marks=pytest.mark.skip(
reason="TODO(b/368639580) revert this skip after fix"
reason="TODO: revert this skip after this pandas bug is fixed: https://github.com/pandas-dev/pandas/issues/59908"
),
),
pytest.param(
Expand All @@ -1701,6 +1710,10 @@ def analyze(row):
[20, 3.75, "rs"],
[30, 8.0, "tu"],
],
# Default pandas index has non-numpy type, whereas bigframes is
# always numpy-based type, so let's use the index compatible
# with bigframes. See more details in b/369689696.
index=pandas.Index([0, 1, 2], dtype=pandas.Int64Dtype()),
columns=pandas.MultiIndex.from_arrays(
[
["first", "last_two", "last_two"],
Expand Down Expand Up @@ -1729,10 +1742,8 @@ def test_df_apply_axis_1_complex(session, pd_df):

def serialize_row(row):
custom = {
"name": row.name.item() if hasattr(row.name, "item") else row.name,
"index": [
idx.item() if hasattr(idx, "item") else idx for idx in row.index
],
"name": row.name,
"index": [idx for idx in row.index],
"values": [
val.item() if hasattr(val, "item") else val for val in row.values
],
Expand All @@ -1756,12 +1767,7 @@ def serialize_row(row):
bf_result = bf_df.apply(serialize_row_remote, axis=1).to_pandas()
pd_result = pd_df.apply(serialize_row, axis=1)

# bf_result.dtype is 'string[pyarrow]' while pd_result.dtype is 'object'
# , ignore this mismatch by using check_dtype=False.
#
# bf_result.index[0].dtype is 'string[pyarrow]' while
# pd_result.index[0].dtype is 'object', ignore this mismatch by using
# check_index_type=False.
# ignore known dtype difference between pandas and bigframes
pandas.testing.assert_series_equal(
pd_result, bf_result, check_dtype=False, check_index_type=False
)
Expand Down