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test_string_arrow.py
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import pickle
import re
import numpy as np
import pytest
from pandas.compat import pa_version_under7p0
import pandas as pd
import pandas._testing as tm
from pandas.core.arrays.string_ import (
StringArray,
StringDtype,
)
from pandas.core.arrays.string_arrow import ArrowStringArray
skip_if_no_pyarrow = pytest.mark.skipif(
pa_version_under7p0,
reason="pyarrow>=7.0.0 is required for PyArrow backed StringArray",
)
@skip_if_no_pyarrow
def test_eq_all_na():
a = pd.array([pd.NA, pd.NA], dtype=StringDtype("pyarrow"))
result = a == a
expected = pd.array([pd.NA, pd.NA], dtype="boolean[pyarrow]")
tm.assert_extension_array_equal(result, expected)
def test_config(string_storage):
with pd.option_context("string_storage", string_storage):
assert StringDtype().storage == string_storage
result = pd.array(["a", "b"])
assert result.dtype.storage == string_storage
expected = (
StringDtype(string_storage).construct_array_type()._from_sequence(["a", "b"])
)
tm.assert_equal(result, expected)
def test_config_bad_storage_raises():
msg = re.escape("Value must be one of python|pyarrow")
with pytest.raises(ValueError, match=msg):
pd.options.mode.string_storage = "foo"
@skip_if_no_pyarrow
@pytest.mark.parametrize("chunked", [True, False])
@pytest.mark.parametrize("array", ["numpy", "pyarrow"])
def test_constructor_not_string_type_raises(array, chunked):
import pyarrow as pa
array = pa if array == "pyarrow" else np
arr = array.array([1, 2, 3])
if chunked:
if array is np:
pytest.skip("chunked not applicable to numpy array")
arr = pa.chunked_array(arr)
if array is np:
msg = "Unsupported type '<class 'numpy.ndarray'>' for ArrowExtensionArray"
else:
msg = re.escape(
"ArrowStringArray requires a PyArrow (chunked) array of string type"
)
with pytest.raises(ValueError, match=msg):
ArrowStringArray(arr)
@skip_if_no_pyarrow
def test_from_sequence_wrong_dtype_raises():
with pd.option_context("string_storage", "python"):
ArrowStringArray._from_sequence(["a", None, "c"], dtype="string")
with pd.option_context("string_storage", "pyarrow"):
ArrowStringArray._from_sequence(["a", None, "c"], dtype="string")
with pytest.raises(AssertionError, match=None):
ArrowStringArray._from_sequence(["a", None, "c"], dtype="string[python]")
ArrowStringArray._from_sequence(["a", None, "c"], dtype="string[pyarrow]")
with pytest.raises(AssertionError, match=None):
with pd.option_context("string_storage", "python"):
ArrowStringArray._from_sequence(["a", None, "c"], dtype=StringDtype())
with pd.option_context("string_storage", "pyarrow"):
ArrowStringArray._from_sequence(["a", None, "c"], dtype=StringDtype())
with pytest.raises(AssertionError, match=None):
ArrowStringArray._from_sequence(["a", None, "c"], dtype=StringDtype("python"))
ArrowStringArray._from_sequence(["a", None, "c"], dtype=StringDtype("pyarrow"))
with pd.option_context("string_storage", "python"):
StringArray._from_sequence(["a", None, "c"], dtype="string")
with pd.option_context("string_storage", "pyarrow"):
StringArray._from_sequence(["a", None, "c"], dtype="string")
StringArray._from_sequence(["a", None, "c"], dtype="string[python]")
with pytest.raises(AssertionError, match=None):
StringArray._from_sequence(["a", None, "c"], dtype="string[pyarrow]")
with pd.option_context("string_storage", "python"):
StringArray._from_sequence(["a", None, "c"], dtype=StringDtype())
with pytest.raises(AssertionError, match=None):
with pd.option_context("string_storage", "pyarrow"):
StringArray._from_sequence(["a", None, "c"], dtype=StringDtype())
StringArray._from_sequence(["a", None, "c"], dtype=StringDtype("python"))
with pytest.raises(AssertionError, match=None):
StringArray._from_sequence(["a", None, "c"], dtype=StringDtype("pyarrow"))
@pytest.mark.skipif(
not pa_version_under7p0,
reason="pyarrow is installed",
)
def test_pyarrow_not_installed_raises():
msg = re.escape("pyarrow>=7.0.0 is required for PyArrow backed")
with pytest.raises(ImportError, match=msg):
StringDtype(storage="pyarrow")
with pytest.raises(ImportError, match=msg):
ArrowStringArray([])
with pytest.raises(ImportError, match=msg):
ArrowStringArray._from_sequence(["a", None, "b"])
@skip_if_no_pyarrow
@pytest.mark.parametrize("multiple_chunks", [False, True])
@pytest.mark.parametrize(
"key, value, expected",
[
(-1, "XX", ["a", "b", "c", "d", "XX"]),
(1, "XX", ["a", "XX", "c", "d", "e"]),
(1, None, ["a", None, "c", "d", "e"]),
(1, pd.NA, ["a", None, "c", "d", "e"]),
([1, 3], "XX", ["a", "XX", "c", "XX", "e"]),
([1, 3], ["XX", "YY"], ["a", "XX", "c", "YY", "e"]),
([1, 3], ["XX", None], ["a", "XX", "c", None, "e"]),
([1, 3], ["XX", pd.NA], ["a", "XX", "c", None, "e"]),
([0, -1], ["XX", "YY"], ["XX", "b", "c", "d", "YY"]),
([-1, 0], ["XX", "YY"], ["YY", "b", "c", "d", "XX"]),
(slice(3, None), "XX", ["a", "b", "c", "XX", "XX"]),
(slice(2, 4), ["XX", "YY"], ["a", "b", "XX", "YY", "e"]),
(slice(3, 1, -1), ["XX", "YY"], ["a", "b", "YY", "XX", "e"]),
(slice(None), "XX", ["XX", "XX", "XX", "XX", "XX"]),
([False, True, False, True, False], ["XX", "YY"], ["a", "XX", "c", "YY", "e"]),
],
)
def test_setitem(multiple_chunks, key, value, expected):
import pyarrow as pa
result = pa.array(list("abcde"))
expected = pa.array(expected)
if multiple_chunks:
result = pa.chunked_array([result[:3], result[3:]])
expected = pa.chunked_array([expected[:3], expected[3:]])
result = ArrowStringArray(result)
expected = ArrowStringArray(expected)
result[key] = value
tm.assert_equal(result, expected)
@skip_if_no_pyarrow
def test_setitem_invalid_indexer_raises():
import pyarrow as pa
arr = ArrowStringArray(pa.array(list("abcde")))
with pytest.raises(IndexError, match=None):
arr[5] = "foo"
with pytest.raises(IndexError, match=None):
arr[-6] = "foo"
with pytest.raises(IndexError, match=None):
arr[[0, 5]] = "foo"
with pytest.raises(IndexError, match=None):
arr[[0, -6]] = "foo"
with pytest.raises(IndexError, match=None):
arr[[True, True, False]] = "foo"
with pytest.raises(ValueError, match=None):
arr[[0, 1]] = ["foo", "bar", "baz"]
@skip_if_no_pyarrow
def test_pickle_roundtrip():
# GH 42600
expected = pd.Series(range(10), dtype="string[pyarrow]")
expected_sliced = expected.head(2)
full_pickled = pickle.dumps(expected)
sliced_pickled = pickle.dumps(expected_sliced)
assert len(full_pickled) > len(sliced_pickled)
result = pickle.loads(full_pickled)
tm.assert_series_equal(result, expected)
result_sliced = pickle.loads(sliced_pickled)
tm.assert_series_equal(result_sliced, expected_sliced)