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- import numpy as np
- import pytest
- from pandas.core.dtypes.common import ensure_platform_int
- import pandas as pd
- from pandas import Float64Index, Index, Int64Index, RangeIndex
- import pandas._testing as tm
- from ..test_numeric import Numeric
- # aliases to make some tests easier to read
- RI = RangeIndex
- I64 = Int64Index
- F64 = Float64Index
- OI = Index
- class TestRangeIndex(Numeric):
- _holder = RangeIndex
- _compat_props = ["shape", "ndim", "size"]
- @pytest.fixture(
- params=[
- RangeIndex(start=0, stop=20, step=2, name="foo"),
- RangeIndex(start=18, stop=-1, step=-2, name="bar"),
- ],
- ids=["index_inc", "index_dec"],
- )
- def indices(self, request):
- return request.param
- def create_index(self):
- return RangeIndex(start=0, stop=20, step=2)
- def test_can_hold_identifiers(self):
- idx = self.create_index()
- key = idx[0]
- assert idx._can_hold_identifiers_and_holds_name(key) is False
- def test_too_many_names(self):
- index = self.create_index()
- with pytest.raises(ValueError, match="^Length"):
- index.names = ["roger", "harold"]
- @pytest.mark.parametrize(
- "index, start, stop, step",
- [
- (RangeIndex(5), 0, 5, 1),
- (RangeIndex(0, 5), 0, 5, 1),
- (RangeIndex(5, step=2), 0, 5, 2),
- (RangeIndex(1, 5, 2), 1, 5, 2),
- ],
- )
- def test_start_stop_step_attrs(self, index, start, stop, step):
- # GH 25710
- assert index.start == start
- assert index.stop == stop
- assert index.step == step
- @pytest.mark.parametrize("attr_name", ["_start", "_stop", "_step"])
- def test_deprecated_start_stop_step_attrs(self, attr_name):
- # GH 26581
- idx = self.create_index()
- with tm.assert_produces_warning(FutureWarning):
- getattr(idx, attr_name)
- def test_copy(self):
- i = RangeIndex(5, name="Foo")
- i_copy = i.copy()
- assert i_copy is not i
- assert i_copy.identical(i)
- assert i_copy._range == range(0, 5, 1)
- assert i_copy.name == "Foo"
- def test_repr(self):
- i = RangeIndex(5, name="Foo")
- result = repr(i)
- expected = "RangeIndex(start=0, stop=5, step=1, name='Foo')"
- assert result == expected
- result = eval(result)
- tm.assert_index_equal(result, i, exact=True)
- i = RangeIndex(5, 0, -1)
- result = repr(i)
- expected = "RangeIndex(start=5, stop=0, step=-1)"
- assert result == expected
- result = eval(result)
- tm.assert_index_equal(result, i, exact=True)
- def test_insert(self):
- idx = RangeIndex(5, name="Foo")
- result = idx[1:4]
- # test 0th element
- tm.assert_index_equal(idx[0:4], result.insert(0, idx[0]))
- # GH 18295 (test missing)
- expected = Float64Index([0, np.nan, 1, 2, 3, 4])
- for na in (np.nan, pd.NaT, None):
- result = RangeIndex(5).insert(1, na)
- tm.assert_index_equal(result, expected)
- def test_delete(self):
- idx = RangeIndex(5, name="Foo")
- expected = idx[1:].astype(int)
- result = idx.delete(0)
- tm.assert_index_equal(result, expected)
- assert result.name == expected.name
- expected = idx[:-1].astype(int)
- result = idx.delete(-1)
- tm.assert_index_equal(result, expected)
- assert result.name == expected.name
- with pytest.raises((IndexError, ValueError)):
- # either depending on numpy version
- result = idx.delete(len(idx))
- def test_view(self):
- i = RangeIndex(0, name="Foo")
- i_view = i.view()
- assert i_view.name == "Foo"
- i_view = i.view("i8")
- tm.assert_numpy_array_equal(i.values, i_view)
- i_view = i.view(RangeIndex)
- tm.assert_index_equal(i, i_view)
- def test_dtype(self):
- index = self.create_index()
- assert index.dtype == np.int64
- def test_cached_data(self):
- # GH 26565, GH26617
- # Calling RangeIndex._data caches an int64 array of the same length at
- # self._cached_data. This test checks whether _cached_data has been set
- idx = RangeIndex(0, 100, 10)
- assert idx._cached_data is None
- repr(idx)
- assert idx._cached_data is None
- str(idx)
- assert idx._cached_data is None
- idx.get_loc(20)
- assert idx._cached_data is None
- 90 in idx
- assert idx._cached_data is None
- 91 in idx
- assert idx._cached_data is None
- idx.all()
- assert idx._cached_data is None
- idx.any()
- assert idx._cached_data is None
- df = pd.DataFrame({"a": range(10)}, index=idx)
- df.loc[50]
- assert idx._cached_data is None
- with pytest.raises(KeyError, match="51"):
- df.loc[51]
- assert idx._cached_data is None
- df.loc[10:50]
- assert idx._cached_data is None
- df.iloc[5:10]
- assert idx._cached_data is None
- # actually calling idx._data
- assert isinstance(idx._data, np.ndarray)
- assert isinstance(idx._cached_data, np.ndarray)
- def test_is_monotonic(self):
- index = RangeIndex(0, 20, 2)
- assert index.is_monotonic is True
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_decreasing is False
- assert index._is_strictly_monotonic_increasing is True
- assert index._is_strictly_monotonic_decreasing is False
- index = RangeIndex(4, 0, -1)
- assert index.is_monotonic is False
- assert index._is_strictly_monotonic_increasing is False
- assert index.is_monotonic_decreasing is True
- assert index._is_strictly_monotonic_decreasing is True
- index = RangeIndex(1, 2)
- assert index.is_monotonic is True
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_decreasing is True
- assert index._is_strictly_monotonic_increasing is True
- assert index._is_strictly_monotonic_decreasing is True
- index = RangeIndex(2, 1)
- assert index.is_monotonic is True
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_decreasing is True
- assert index._is_strictly_monotonic_increasing is True
- assert index._is_strictly_monotonic_decreasing is True
- index = RangeIndex(1, 1)
- assert index.is_monotonic is True
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_decreasing is True
- assert index._is_strictly_monotonic_increasing is True
- assert index._is_strictly_monotonic_decreasing is True
- def test_equals_range(self):
- equiv_pairs = [
- (RangeIndex(0, 9, 2), RangeIndex(0, 10, 2)),
- (RangeIndex(0), RangeIndex(1, -1, 3)),
- (RangeIndex(1, 2, 3), RangeIndex(1, 3, 4)),
- (RangeIndex(0, -9, -2), RangeIndex(0, -10, -2)),
- ]
- for left, right in equiv_pairs:
- assert left.equals(right)
- assert right.equals(left)
- def test_logical_compat(self):
- idx = self.create_index()
- assert idx.all() == idx.values.all()
- assert idx.any() == idx.values.any()
- def test_identical(self):
- index = self.create_index()
- i = Index(index.copy())
- assert i.identical(index)
- # we don't allow object dtype for RangeIndex
- if isinstance(index, RangeIndex):
- return
- same_values_different_type = Index(i, dtype=object)
- assert not i.identical(same_values_different_type)
- i = index.copy(dtype=object)
- i = i.rename("foo")
- same_values = Index(i, dtype=object)
- assert same_values.identical(index.copy(dtype=object))
- assert not i.identical(index)
- assert Index(same_values, name="foo", dtype=object).identical(i)
- assert not index.copy(dtype=object).identical(index.copy(dtype="int64"))
- def test_get_indexer(self):
- index = self.create_index()
- target = RangeIndex(10)
- indexer = index.get_indexer(target)
- expected = np.array([0, -1, 1, -1, 2, -1, 3, -1, 4, -1], dtype=np.intp)
- tm.assert_numpy_array_equal(indexer, expected)
- def test_get_indexer_pad(self):
- index = self.create_index()
- target = RangeIndex(10)
- indexer = index.get_indexer(target, method="pad")
- expected = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4], dtype=np.intp)
- tm.assert_numpy_array_equal(indexer, expected)
- def test_get_indexer_backfill(self):
- index = self.create_index()
- target = RangeIndex(10)
- indexer = index.get_indexer(target, method="backfill")
- expected = np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5], dtype=np.intp)
- tm.assert_numpy_array_equal(indexer, expected)
- def test_get_indexer_limit(self):
- # GH 28631
- idx = RangeIndex(4)
- target = RangeIndex(6)
- result = idx.get_indexer(target, method="pad", limit=1)
- expected = np.array([0, 1, 2, 3, 3, -1], dtype=np.intp)
- tm.assert_numpy_array_equal(result, expected)
- @pytest.mark.parametrize("stop", [0, -1, -2])
- def test_get_indexer_decreasing(self, stop):
- # GH 28678
- index = RangeIndex(7, stop, -3)
- result = index.get_indexer(range(9))
- expected = np.array([-1, 2, -1, -1, 1, -1, -1, 0, -1], dtype=np.intp)
- tm.assert_numpy_array_equal(result, expected)
- def test_join_outer(self):
- # join with Int64Index
- index = self.create_index()
- other = Int64Index(np.arange(25, 14, -1))
- res, lidx, ridx = index.join(other, how="outer", return_indexers=True)
- noidx_res = index.join(other, how="outer")
- tm.assert_index_equal(res, noidx_res)
- eres = Int64Index(
- [0, 2, 4, 6, 8, 10, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]
- )
- elidx = np.array(
- [0, 1, 2, 3, 4, 5, 6, 7, -1, 8, -1, 9, -1, -1, -1, -1, -1, -1, -1],
- dtype=np.intp,
- )
- eridx = np.array(
- [-1, -1, -1, -1, -1, -1, -1, -1, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0],
- dtype=np.intp,
- )
- assert isinstance(res, Int64Index)
- assert not isinstance(res, RangeIndex)
- tm.assert_index_equal(res, eres)
- tm.assert_numpy_array_equal(lidx, elidx)
- tm.assert_numpy_array_equal(ridx, eridx)
- # join with RangeIndex
- other = RangeIndex(25, 14, -1)
- res, lidx, ridx = index.join(other, how="outer", return_indexers=True)
- noidx_res = index.join(other, how="outer")
- tm.assert_index_equal(res, noidx_res)
- assert isinstance(res, Int64Index)
- assert not isinstance(res, RangeIndex)
- tm.assert_index_equal(res, eres)
- tm.assert_numpy_array_equal(lidx, elidx)
- tm.assert_numpy_array_equal(ridx, eridx)
- def test_join_inner(self):
- # Join with non-RangeIndex
- index = self.create_index()
- other = Int64Index(np.arange(25, 14, -1))
- res, lidx, ridx = index.join(other, how="inner", return_indexers=True)
- # no guarantee of sortedness, so sort for comparison purposes
- ind = res.argsort()
- res = res.take(ind)
- lidx = lidx.take(ind)
- ridx = ridx.take(ind)
- eres = Int64Index([16, 18])
- elidx = np.array([8, 9], dtype=np.intp)
- eridx = np.array([9, 7], dtype=np.intp)
- assert isinstance(res, Int64Index)
- tm.assert_index_equal(res, eres)
- tm.assert_numpy_array_equal(lidx, elidx)
- tm.assert_numpy_array_equal(ridx, eridx)
- # Join two RangeIndex
- other = RangeIndex(25, 14, -1)
- res, lidx, ridx = index.join(other, how="inner", return_indexers=True)
- assert isinstance(res, RangeIndex)
- tm.assert_index_equal(res, eres)
- tm.assert_numpy_array_equal(lidx, elidx)
- tm.assert_numpy_array_equal(ridx, eridx)
- def test_join_left(self):
- # Join with Int64Index
- index = self.create_index()
- other = Int64Index(np.arange(25, 14, -1))
- res, lidx, ridx = index.join(other, how="left", return_indexers=True)
- eres = index
- eridx = np.array([-1, -1, -1, -1, -1, -1, -1, -1, 9, 7], dtype=np.intp)
- assert isinstance(res, RangeIndex)
- tm.assert_index_equal(res, eres)
- assert lidx is None
- tm.assert_numpy_array_equal(ridx, eridx)
- # Join withRangeIndex
- other = Int64Index(np.arange(25, 14, -1))
- res, lidx, ridx = index.join(other, how="left", return_indexers=True)
- assert isinstance(res, RangeIndex)
- tm.assert_index_equal(res, eres)
- assert lidx is None
- tm.assert_numpy_array_equal(ridx, eridx)
- def test_join_right(self):
- # Join with Int64Index
- index = self.create_index()
- other = Int64Index(np.arange(25, 14, -1))
- res, lidx, ridx = index.join(other, how="right", return_indexers=True)
- eres = other
- elidx = np.array([-1, -1, -1, -1, -1, -1, -1, 9, -1, 8, -1], dtype=np.intp)
- assert isinstance(other, Int64Index)
- tm.assert_index_equal(res, eres)
- tm.assert_numpy_array_equal(lidx, elidx)
- assert ridx is None
- # Join withRangeIndex
- other = RangeIndex(25, 14, -1)
- res, lidx, ridx = index.join(other, how="right", return_indexers=True)
- eres = other
- assert isinstance(other, RangeIndex)
- tm.assert_index_equal(res, eres)
- tm.assert_numpy_array_equal(lidx, elidx)
- assert ridx is None
- def test_join_non_int_index(self):
- index = self.create_index()
- other = Index([3, 6, 7, 8, 10], dtype=object)
- outer = index.join(other, how="outer")
- outer2 = other.join(index, how="outer")
- expected = Index([0, 2, 3, 4, 6, 7, 8, 10, 12, 14, 16, 18])
- tm.assert_index_equal(outer, outer2)
- tm.assert_index_equal(outer, expected)
- inner = index.join(other, how="inner")
- inner2 = other.join(index, how="inner")
- expected = Index([6, 8, 10])
- tm.assert_index_equal(inner, inner2)
- tm.assert_index_equal(inner, expected)
- left = index.join(other, how="left")
- tm.assert_index_equal(left, index.astype(object))
- left2 = other.join(index, how="left")
- tm.assert_index_equal(left2, other)
- right = index.join(other, how="right")
- tm.assert_index_equal(right, other)
- right2 = other.join(index, how="right")
- tm.assert_index_equal(right2, index.astype(object))
- def test_join_non_unique(self):
- index = self.create_index()
- other = Index([4, 4, 3, 3])
- res, lidx, ridx = index.join(other, return_indexers=True)
- eres = Int64Index([0, 2, 4, 4, 6, 8, 10, 12, 14, 16, 18])
- elidx = np.array([0, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9], dtype=np.intp)
- eridx = np.array([-1, -1, 0, 1, -1, -1, -1, -1, -1, -1, -1], dtype=np.intp)
- tm.assert_index_equal(res, eres)
- tm.assert_numpy_array_equal(lidx, elidx)
- tm.assert_numpy_array_equal(ridx, eridx)
- def test_join_self(self, join_type):
- index = self.create_index()
- joined = index.join(index, how=join_type)
- assert index is joined
- def test_nbytes(self):
- # memory savings vs int index
- i = RangeIndex(0, 1000)
- assert i.nbytes < i._int64index.nbytes / 10
- # constant memory usage
- i2 = RangeIndex(0, 10)
- assert i.nbytes == i2.nbytes
- def test_cant_or_shouldnt_cast(self):
- # can't
- with pytest.raises(TypeError):
- RangeIndex("foo", "bar", "baz")
- # shouldn't
- with pytest.raises(TypeError):
- RangeIndex("0", "1", "2")
- def test_view_index(self):
- index = self.create_index()
- index.view(Index)
- def test_prevent_casting(self):
- index = self.create_index()
- result = index.astype("O")
- assert result.dtype == np.object_
- def test_take_preserve_name(self):
- index = RangeIndex(1, 5, name="foo")
- taken = index.take([3, 0, 1])
- assert index.name == taken.name
- def test_take_fill_value(self):
- # GH 12631
- idx = pd.RangeIndex(1, 4, name="xxx")
- result = idx.take(np.array([1, 0, -1]))
- expected = pd.Int64Index([2, 1, 3], name="xxx")
- tm.assert_index_equal(result, expected)
- # fill_value
- msg = "Unable to fill values because RangeIndex cannot contain NA"
- with pytest.raises(ValueError, match=msg):
- idx.take(np.array([1, 0, -1]), fill_value=True)
- # allow_fill=False
- result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
- expected = pd.Int64Index([2, 1, 3], name="xxx")
- tm.assert_index_equal(result, expected)
- msg = "Unable to fill values because RangeIndex cannot contain NA"
- with pytest.raises(ValueError, match=msg):
- idx.take(np.array([1, 0, -2]), fill_value=True)
- with pytest.raises(ValueError, match=msg):
- idx.take(np.array([1, 0, -5]), fill_value=True)
- with pytest.raises(IndexError):
- idx.take(np.array([1, -5]))
- def test_print_unicode_columns(self):
- df = pd.DataFrame({"\u05d0": [1, 2, 3], "\u05d1": [4, 5, 6], "c": [7, 8, 9]})
- repr(df.columns) # should not raise UnicodeDecodeError
- def test_repr_roundtrip(self):
- index = self.create_index()
- tm.assert_index_equal(eval(repr(index)), index)
- def test_slice_keep_name(self):
- idx = RangeIndex(1, 2, name="asdf")
- assert idx.name == idx[1:].name
- def test_explicit_conversions(self):
- # GH 8608
- # add/sub are overridden explicitly for Float/Int Index
- idx = RangeIndex(5)
- # float conversions
- arr = np.arange(5, dtype="int64") * 3.2
- expected = Float64Index(arr)
- fidx = idx * 3.2
- tm.assert_index_equal(fidx, expected)
- fidx = 3.2 * idx
- tm.assert_index_equal(fidx, expected)
- # interops with numpy arrays
- expected = Float64Index(arr)
- a = np.zeros(5, dtype="float64")
- result = fidx - a
- tm.assert_index_equal(result, expected)
- expected = Float64Index(-arr)
- a = np.zeros(5, dtype="float64")
- result = a - fidx
- tm.assert_index_equal(result, expected)
- def test_has_duplicates(self, indices):
- assert indices.is_unique
- assert not indices.has_duplicates
- def test_extended_gcd(self):
- index = self.create_index()
- result = index._extended_gcd(6, 10)
- assert result[0] == result[1] * 6 + result[2] * 10
- assert 2 == result[0]
- result = index._extended_gcd(10, 6)
- assert 2 == result[1] * 10 + result[2] * 6
- assert 2 == result[0]
- def test_min_fitting_element(self):
- result = RangeIndex(0, 20, 2)._min_fitting_element(1)
- assert 2 == result
- result = RangeIndex(1, 6)._min_fitting_element(1)
- assert 1 == result
- result = RangeIndex(18, -2, -2)._min_fitting_element(1)
- assert 2 == result
- result = RangeIndex(5, 0, -1)._min_fitting_element(1)
- assert 1 == result
- big_num = 500000000000000000000000
- result = RangeIndex(5, big_num * 2, 1)._min_fitting_element(big_num)
- assert big_num == result
- def test_max_fitting_element(self):
- result = RangeIndex(0, 20, 2)._max_fitting_element(17)
- assert 16 == result
- result = RangeIndex(1, 6)._max_fitting_element(4)
- assert 4 == result
- result = RangeIndex(18, -2, -2)._max_fitting_element(17)
- assert 16 == result
- result = RangeIndex(5, 0, -1)._max_fitting_element(4)
- assert 4 == result
- big_num = 500000000000000000000000
- result = RangeIndex(5, big_num * 2, 1)._max_fitting_element(big_num)
- assert big_num == result
- def test_pickle_compat_construction(self):
- # RangeIndex() is a valid constructor
- pass
- def test_slice_specialised(self):
- index = self.create_index()
- index.name = "foo"
- # scalar indexing
- res = index[1]
- expected = 2
- assert res == expected
- res = index[-1]
- expected = 18
- assert res == expected
- # slicing
- # slice value completion
- index_slice = index[:]
- expected = index
- tm.assert_index_equal(index_slice, expected)
- # positive slice values
- index_slice = index[7:10:2]
- expected = Index(np.array([14, 18]), name="foo")
- tm.assert_index_equal(index_slice, expected)
- # negative slice values
- index_slice = index[-1:-5:-2]
- expected = Index(np.array([18, 14]), name="foo")
- tm.assert_index_equal(index_slice, expected)
- # stop overshoot
- index_slice = index[2:100:4]
- expected = Index(np.array([4, 12]), name="foo")
- tm.assert_index_equal(index_slice, expected)
- # reverse
- index_slice = index[::-1]
- expected = Index(index.values[::-1], name="foo")
- tm.assert_index_equal(index_slice, expected)
- index_slice = index[-8::-1]
- expected = Index(np.array([4, 2, 0]), name="foo")
- tm.assert_index_equal(index_slice, expected)
- index_slice = index[-40::-1]
- expected = Index(np.array([], dtype=np.int64), name="foo")
- tm.assert_index_equal(index_slice, expected)
- index_slice = index[40::-1]
- expected = Index(index.values[40::-1], name="foo")
- tm.assert_index_equal(index_slice, expected)
- index_slice = index[10::-1]
- expected = Index(index.values[::-1], name="foo")
- tm.assert_index_equal(index_slice, expected)
- @pytest.mark.parametrize("step", set(range(-5, 6)) - {0})
- def test_len_specialised(self, step):
- # make sure that our len is the same as np.arange calc
- start, stop = (0, 5) if step > 0 else (5, 0)
- arr = np.arange(start, stop, step)
- index = RangeIndex(start, stop, step)
- assert len(index) == len(arr)
- index = RangeIndex(stop, start, step)
- assert len(index) == 0
- @pytest.fixture(
- params=[
- ([RI(1, 12, 5)], RI(1, 12, 5)),
- ([RI(0, 6, 4)], RI(0, 6, 4)),
- ([RI(1, 3), RI(3, 7)], RI(1, 7)),
- ([RI(1, 5, 2), RI(5, 6)], RI(1, 6, 2)),
- ([RI(1, 3, 2), RI(4, 7, 3)], RI(1, 7, 3)),
- ([RI(-4, 3, 2), RI(4, 7, 2)], RI(-4, 7, 2)),
- ([RI(-4, -8), RI(-8, -12)], RI(0, 0)),
- ([RI(-4, -8), RI(3, -4)], RI(0, 0)),
- ([RI(-4, -8), RI(3, 5)], RI(3, 5)),
- ([RI(-4, -2), RI(3, 5)], I64([-4, -3, 3, 4])),
- ([RI(-2), RI(3, 5)], RI(3, 5)),
- ([RI(2), RI(2)], I64([0, 1, 0, 1])),
- ([RI(2), RI(2, 5), RI(5, 8, 4)], RI(0, 6)),
- ([RI(2), RI(3, 5), RI(5, 8, 4)], I64([0, 1, 3, 4, 5])),
- ([RI(-2, 2), RI(2, 5), RI(5, 8, 4)], RI(-2, 6)),
- ([RI(3), I64([-1, 3, 15])], I64([0, 1, 2, -1, 3, 15])),
- ([RI(3), F64([-1, 3.1, 15.0])], F64([0, 1, 2, -1, 3.1, 15.0])),
- ([RI(3), OI(["a", None, 14])], OI([0, 1, 2, "a", None, 14])),
- ([RI(3, 1), OI(["a", None, 14])], OI(["a", None, 14])),
- ]
- )
- def appends(self, request):
- """Inputs and expected outputs for RangeIndex.append test"""
- return request.param
- def test_append(self, appends):
- # GH16212
- indices, expected = appends
- result = indices[0].append(indices[1:])
- tm.assert_index_equal(result, expected, exact=True)
- if len(indices) == 2:
- # Append single item rather than list
- result2 = indices[0].append(indices[1])
- tm.assert_index_equal(result2, expected, exact=True)
- def test_engineless_lookup(self):
- # GH 16685
- # Standard lookup on RangeIndex should not require the engine to be
- # created
- idx = RangeIndex(2, 10, 3)
- assert idx.get_loc(5) == 1
- tm.assert_numpy_array_equal(
- idx.get_indexer([2, 8]), ensure_platform_int(np.array([0, 2]))
- )
- with pytest.raises(KeyError, match="3"):
- idx.get_loc(3)
- assert "_engine" not in idx._cache
- # The engine is still required for lookup of a different dtype scalar:
- with pytest.raises(KeyError, match="'a'"):
- assert idx.get_loc("a") == -1
- assert "_engine" in idx._cache
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