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[ArrowStringArray] PERF: use pyarrow.compute.utf8_length if available #41248

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Merged
merged 1 commit into from
May 4, 2021
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[ArrowStringArray] PERF: use pyarrow.compute.utf8_length if available #41248

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9 changes: 9 additions & 0 deletions pandas/core/arrays/string_arrow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,6 +41,7 @@
from pandas.core.arraylike import OpsMixin
from pandas.core.arrays.base import ExtensionArray
from pandas.core.arrays.boolean import BooleanDtype
from pandas.core.arrays.integer import Int64Dtype
from pandas.core.indexers import (
check_array_indexer,
validate_indices,
Expand Down Expand Up @@ -858,6 +859,14 @@ def _str_isupper(self):
else:
return super()._str_isupper()

def _str_len(self):
# utf8_length added in pyarrow 4.0.0
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we should do this as a more general check i think (e.g. maybe defined a pyarrow_gt_400 or similar to what we do elsewhere rather than rely on checks like this (e.g. create a pyarrow.compat or similar). but let's create an issue and do a followup.

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sgtm

if hasattr(pc, "utf8_length"):
result = pc.utf8_length(self._data)
return Int64Dtype().__from_arrow__(result)
else:
return super()._str_len()

def _str_lower(self):
return type(self)(pc.utf8_lower(self._data))

Expand Down
16 changes: 10 additions & 6 deletions pandas/tests/strings/test_strings.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,6 @@
MultiIndex,
Series,
isna,
notna,
)
import pandas._testing as tm

Expand Down Expand Up @@ -402,14 +401,19 @@ def test_join():
tm.assert_almost_equal(rs, xp)


def test_len():
values = Series(["foo", "fooo", "fooooo", np.nan, "fooooooo"])
def test_len(any_string_dtype):
values = Series(
["foo", "fooo", "fooooo", np.nan, "fooooooo", "foo\n", "あ"],
dtype=any_string_dtype,
)

result = values.str.len()
exp = values.map(lambda x: len(x) if notna(x) else np.nan)
tm.assert_series_equal(result, exp)
expected_dtype = "float64" if any_string_dtype == "object" else "Int64"
expected = Series([3, 4, 6, np.nan, 8, 4, 1], dtype=expected_dtype)
tm.assert_series_equal(result, expected)

# mixed

def test_len_mixed():
mixed = Series(
[
"a_b",
Expand Down