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ENH: Add lazy copy for sort_index #50491

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Jan 3, 2023
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ENH: Add lazy copy for sort_index #50491

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ENH: Add lazy copy for sort_index
phofl Dec 29, 2022
0a5c9e6
Update conftest.py
phofl Jan 3, 2023
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1 change: 1 addition & 0 deletions pandas/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1903,6 +1903,7 @@ def using_copy_on_write() -> bool:
"""
Fixture to check if Copy-on-Write is enabled.
"""
pd.options.mode.copy_on_write = True
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I suppose this is a leftover from local testing?

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Yes, thanks for noticing

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BTW, for testing, you can set the env variable PANDAS_COPY_ON_WRITE=1 pytest ..., which is of course a bit verbose. What I do locally is that I have an alias in my bashrc, so I can just do COW pytest ..., and then it is quite easy to switch between COW pytest ... or pytest ... when I want to run a specific test while developing with both COW enabled or not.

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Yeah agreed, did this when running tests in PyCharm

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Ah, I can't speak for PyCharm ;)

return pd.options.mode.copy_on_write and pd.options.mode.data_manager == "block"


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2 changes: 1 addition & 1 deletion pandas/core/generic.py
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Expand Up @@ -4934,7 +4934,7 @@ def sort_index(
if inplace:
result = self
else:
result = self.copy()
result = self.copy(deep=None)

if ignore_index:
result.index = default_index(len(self))
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17 changes: 17 additions & 0 deletions pandas/tests/copy_view/test_methods.py
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Expand Up @@ -405,6 +405,23 @@ def test_reindex_like(using_copy_on_write):
tm.assert_frame_equal(df, df_orig)


def test_sort_index(using_copy_on_write):
# GH 49473
ser = Series([1, 2, 3])
ser_orig = ser.copy()
ser2 = ser.sort_index()

if using_copy_on_write:
assert np.shares_memory(ser.values, ser2.values)
else:
assert not np.shares_memory(ser.values, ser2.values)

# mutating ser triggers a copy-on-write for the column / block
ser2.iloc[0] = 0
assert not np.shares_memory(ser2.values, ser.values)
tm.assert_series_equal(ser, ser_orig)


def test_reorder_levels(using_copy_on_write):
index = MultiIndex.from_tuples(
[(1, 1), (1, 2), (2, 1), (2, 2)], names=["one", "two"]
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