针对pulse-transit的工具

dist/client/pandas/tests/indexes/base_class/test_indexing.py

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+import numpy as np
+import pytest
+
+import pandas as pd
+from pandas import (
+    Index,
+    NaT,
+)
+import pandas._testing as tm
+
+
+class TestGetSliceBounds:
+    @pytest.mark.parametrize("kind", ["getitem", "loc", None])
+    @pytest.mark.parametrize("side, expected", [("left", 4), ("right", 5)])
+    def test_get_slice_bounds_within(self, kind, side, expected):
+        index = Index(list("abcdef"))
+        with tm.assert_produces_warning(FutureWarning, match="'kind' argument"):
+            result = index.get_slice_bound("e", kind=kind, side=side)
+        assert result == expected
+
+    @pytest.mark.parametrize("kind", ["getitem", "loc", None])
+    @pytest.mark.parametrize("side", ["left", "right"])
+    @pytest.mark.parametrize(
+        "data, bound, expected", [(list("abcdef"), "x", 6), (list("bcdefg"), "a", 0)]
+    )
+    def test_get_slice_bounds_outside(self, kind, side, expected, data, bound):
+        index = Index(data)
+        with tm.assert_produces_warning(FutureWarning, match="'kind' argument"):
+            result = index.get_slice_bound(bound, kind=kind, side=side)
+        assert result == expected
+
+    def test_get_slice_bounds_invalid_side(self):
+        with pytest.raises(ValueError, match="Invalid value for side kwarg"):
+            Index([]).get_slice_bound("a", side="middle")
+
+
+class TestGetIndexerNonUnique:
+    def test_get_indexer_non_unique_dtype_mismatch(self):
+        # GH#25459
+        indexes, missing = Index(["A", "B"]).get_indexer_non_unique(Index([0]))
+        tm.assert_numpy_array_equal(np.array([-1], dtype=np.intp), indexes)
+        tm.assert_numpy_array_equal(np.array([0], dtype=np.intp), missing)
+
+
+class TestGetLoc:
+    @pytest.mark.slow  # to_flat_index takes a while
+    def test_get_loc_tuple_monotonic_above_size_cutoff(self):
+        # Go through the libindex path for which using
+        # _bin_search vs ndarray.searchsorted makes a difference
+
+        lev = list("ABCDEFGHIJKLMNOPQRSTUVWXYZ")
+        dti = pd.date_range("2016-01-01", periods=100)
+
+        mi = pd.MultiIndex.from_product([lev, range(10**3), dti])
+        oidx = mi.to_flat_index()
+
+        loc = len(oidx) // 2
+        tup = oidx[loc]
+
+        res = oidx.get_loc(tup)
+        assert res == loc
+
+    def test_get_loc_nan_object_dtype_nonmonotonic_nonunique(self):
+        # case that goes through _maybe_get_bool_indexer
+        idx = Index(["foo", np.nan, None, "foo", 1.0, None], dtype=object)
+
+        # we dont raise KeyError on nan
+        res = idx.get_loc(np.nan)
+        assert res == 1
+
+        # we only match on None, not on np.nan
+        res = idx.get_loc(None)
+        expected = np.array([False, False, True, False, False, True])
+        tm.assert_numpy_array_equal(res, expected)
+
+        # we don't match at all on mismatched NA
+        with pytest.raises(KeyError, match="NaT"):
+            idx.get_loc(NaT)