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ENH: Add lazy copy to replace #50746

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Merged
merged 17 commits into from
Jan 17, 2023
Merged

ENH: Add lazy copy to replace #50746

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b855f09
WIP: ENH: CoW support for replace
lithomas1 Jan 7, 2023
e27d788
Fix bugs, should work for 1-D
lithomas1 Jan 7, 2023
f638abd
Refactor to support more than one loc
lithomas1 Jan 9, 2023
bc3af5c
Don't access refs if None
lithomas1 Jan 10, 2023
66b957f
Flesh out tests, fix issues
lithomas1 Jan 12, 2023
4ecf604
Merge branch 'main' into enh-cow-replace
lithomas1 Jan 12, 2023
2266ab8
fix tests
lithomas1 Jan 12, 2023
7aee847
fixes
lithomas1 Jan 14, 2023
5f8fa06
Merge branch 'main' into enh-cow-replace
lithomas1 Jan 14, 2023
6dc05e1
Simplify block splitting logic
phofl Jan 14, 2023
6514131
Clear ref
phofl Jan 14, 2023
3849842
Adjust test
phofl Jan 14, 2023
f2b8a97
Fix test
phofl Jan 14, 2023
c1d90ca
Small fix
phofl Jan 14, 2023
e8e1ff2
Fix 32 bit test
phofl Jan 14, 2023
9e84de4
Adjust test
phofl Jan 14, 2023
7988a16
Update pandas/tests/copy_view/test_methods.py
phofl Jan 16, 2023
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23 changes: 12 additions & 11 deletions pandas/tests/copy_view/test_internals.py
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Original file line number Diff line number Diff line change
Expand Up @@ -100,15 +100,15 @@ def test_switch_options():
@pytest.mark.parametrize(
"locs, arr",
[
([0], np.array([-1, -2, -3])),
([1], np.array([-1, -2, -3])),
([5], np.array([-1, -2, -3])),
([0, 1], np.array([-1, -2, -3])),
([0, 2], np.array([-1, -2, -3])),
([0, 1, 2], np.array([-1, -2, -3])),
([1, 2], np.array([-1, -2, -3])),
([1, 3], np.array([-1, -2, -3])),
([1, 3], np.array([[-1, -2, -3], [-4, -5, -6]]).T),
([0], np.array([-1, -2, -3], dtype=np.intp)),
([1], np.array([-1, -2, -3], dtype=np.intp)),
([5], np.array([-1, -2, -3], dtype=np.intp)),
([0, 1], np.array([-1, -2, -3], dtype=np.intp)),
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cc @lithomas1 I don't think that this is valid or can be reached in this way. I think the dimension of your values has to be the same as your indexer. This raises if blk.should_store_value is False, because it does not get broadcast.

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You're right. Even for the non CoW, the iset operation doesn't fail(strangely), but printing the DataFrame afterwards does.

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Yep you get a block that has dimension 2 according to block placement but the underlying array has only one column, doesn’t really error when creating but as soon as you access it youll get into trouble :)

([0, 2], np.array([-1, -2, -3], dtype=np.intp)),
([0, 1, 2], np.array([-1, -2, -3], dtype=np.intp)),
([1, 2], np.array([-1, -2, -3], dtype=np.intp)),
([1, 3], np.array([-1, -2, -3], dtype=np.intp)),
([1, 3], np.array([[-1, -2, -3], [-4, -5, -6]], dtype=np.intp).T),
],
)
def test_iset_splits_blocks_inplace(using_copy_on_write, locs, arr):
Expand All @@ -122,9 +122,10 @@ def test_iset_splits_blocks_inplace(using_copy_on_write, locs, arr):
"c": [7, 8, 9],
"d": [10, 11, 12],
"e": [13, 14, 15],
"f": ["foo", "bar", "baz"],
}
},
dtype=np.intp,
)
df["f"] = ["a", "b", "c"]
df_orig = df.copy()
df2 = df.copy(deep=None) # Trigger a CoW (if enabled, otherwise makes copy)
df2._mgr.iset(locs, arr, inplace=True)
Expand Down