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ENH: Add lazy copy to pipe #50567

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Merged
merged 4 commits into from
Jan 6, 2023
Merged

ENH: Add lazy copy to pipe #50567

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aec8dd9
ENH: Add lazy copy to pipe
phofl Jan 4, 2023
6e7cf36
Add test and move copy
phofl Jan 5, 2023
0064a39
Merge branch 'main' into cow_pipe
phofl Jan 6, 2023
e9f3020
Rename
phofl Jan 6, 2023
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5 changes: 4 additions & 1 deletion pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5771,7 +5771,10 @@ def pipe(
... .pipe((func, 'arg2'), arg1=a, arg3=c)
... ) # doctest: +SKIP
"""
return common.pipe(self, func, *args, **kwargs)
result = common.pipe(self, func, *args, **kwargs)
if _using_copy_on_write():
return result.copy(deep=None)
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Should we pass in self.copy(deep=None) to the pipe, instead of shallow copying the result?

Or do we have guarantees at the moment about that a piped function can mutate the dataframe inplace?

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Good point, this should be the other way round, will adjust accordingly and add tests

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Moved and added another test modifying the object inplace

return result

# ----------------------------------------------------------------------
# Attribute access
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24 changes: 24 additions & 0 deletions pandas/tests/copy_view/test_methods.py
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Expand Up @@ -115,6 +115,30 @@ def test_rename_columns_modify_parent(using_copy_on_write):
tm.assert_frame_equal(df2, df2_orig)


def test_pipe(using_copy_on_write):
df = DataFrame({"a": [1, 2, 3], "b": 1.5})
df_orig = df.copy()

def testfunc(df):
return df

df2 = df.pipe(testfunc)

assert np.shares_memory(get_array(df2, "a"), get_array(df, "a"))

# mutating df2 triggers a copy-on-write for that column
df2.iloc[0, 0] = 0
if using_copy_on_write:
tm.assert_frame_equal(df, df_orig)
assert not np.shares_memory(get_array(df2, "a"), get_array(df, "a"))
else:
expected = DataFrame({"a": [0, 2, 3], "b": 1.5})
tm.assert_frame_equal(df, expected)

assert np.shares_memory(get_array(df2, "a"), get_array(df, "a"))
assert np.shares_memory(get_array(df2, "b"), get_array(df, "b"))


def test_reindex_columns(using_copy_on_write):
# Case: reindexing the column returns a new dataframe
# + afterwards modifying the result
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