820 lines
28 KiB
Python
820 lines
28 KiB
Python
import gc
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from typing import Type
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import numpy as np
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import pytest
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from pandas._libs import iNaT
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from pandas.errors import InvalidIndexError
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from pandas.core.dtypes.common import is_datetime64tz_dtype
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from pandas.core.dtypes.dtypes import CategoricalDtype
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import pandas as pd
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from pandas import (
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CategoricalIndex,
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DatetimeIndex,
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Index,
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Int64Index,
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IntervalIndex,
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MultiIndex,
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PeriodIndex,
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RangeIndex,
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Series,
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TimedeltaIndex,
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UInt64Index,
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isna,
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)
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import pandas._testing as tm
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from pandas.core.indexes.datetimelike import DatetimeIndexOpsMixin
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class Base:
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""" base class for index sub-class tests """
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_holder: Type[Index]
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_compat_props = ["shape", "ndim", "size", "nbytes"]
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def create_index(self) -> Index:
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raise NotImplementedError("Method not implemented")
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def test_pickle_compat_construction(self):
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# need an object to create with
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msg = (
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r"Index\(\.\.\.\) must be called with a collection of some "
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r"kind, None was passed|"
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r"__new__\(\) missing 1 required positional argument: 'data'|"
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r"__new__\(\) takes at least 2 arguments \(1 given\)"
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)
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with pytest.raises(TypeError, match=msg):
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self._holder()
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@pytest.mark.parametrize("name", [None, "new_name"])
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def test_to_frame(self, name):
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# see GH-15230, GH-22580
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idx = self.create_index()
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if name:
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idx_name = name
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else:
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idx_name = idx.name or 0
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df = idx.to_frame(name=idx_name)
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assert df.index is idx
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assert len(df.columns) == 1
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assert df.columns[0] == idx_name
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assert df[idx_name].values is not idx.values
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df = idx.to_frame(index=False, name=idx_name)
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assert df.index is not idx
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def test_shift(self):
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# GH8083 test the base class for shift
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idx = self.create_index()
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msg = (
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f"This method is only implemented for DatetimeIndex, PeriodIndex and "
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f"TimedeltaIndex; Got type {type(idx).__name__}"
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)
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with pytest.raises(NotImplementedError, match=msg):
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idx.shift(1)
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with pytest.raises(NotImplementedError, match=msg):
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idx.shift(1, 2)
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def test_constructor_name_unhashable(self):
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# GH#29069 check that name is hashable
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# See also same-named test in tests.series.test_constructors
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idx = self.create_index()
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with pytest.raises(TypeError, match="Index.name must be a hashable type"):
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type(idx)(idx, name=[])
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def test_create_index_existing_name(self):
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# GH11193, when an existing index is passed, and a new name is not
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# specified, the new index should inherit the previous object name
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expected = self.create_index()
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if not isinstance(expected, MultiIndex):
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expected.name = "foo"
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result = Index(expected)
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tm.assert_index_equal(result, expected)
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result = Index(expected, name="bar")
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expected.name = "bar"
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tm.assert_index_equal(result, expected)
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else:
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expected.names = ["foo", "bar"]
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result = Index(expected)
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tm.assert_index_equal(
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result,
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Index(
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Index(
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[
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("foo", "one"),
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("foo", "two"),
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("bar", "one"),
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("baz", "two"),
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("qux", "one"),
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("qux", "two"),
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],
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dtype="object",
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),
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names=["foo", "bar"],
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),
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)
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result = Index(expected, names=["A", "B"])
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tm.assert_index_equal(
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result,
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Index(
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Index(
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[
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("foo", "one"),
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("foo", "two"),
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("bar", "one"),
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("baz", "two"),
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("qux", "one"),
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("qux", "two"),
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],
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dtype="object",
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),
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names=["A", "B"],
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),
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)
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def test_numeric_compat(self):
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idx = self.create_index()
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# Check that this doesn't cover MultiIndex case, if/when it does,
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# we can remove multi.test_compat.test_numeric_compat
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assert not isinstance(idx, MultiIndex)
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if type(idx) is Index:
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return
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typ = type(idx._data).__name__
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lmsg = "|".join(
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[
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rf"unsupported operand type\(s\) for \*: '{typ}' and 'int'",
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"cannot perform (__mul__|__truediv__|__floordiv__) with "
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f"this index type: {typ}",
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]
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)
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with pytest.raises(TypeError, match=lmsg):
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idx * 1
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rmsg = "|".join(
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[
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rf"unsupported operand type\(s\) for \*: 'int' and '{typ}'",
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"cannot perform (__rmul__|__rtruediv__|__rfloordiv__) with "
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f"this index type: {typ}",
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]
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)
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with pytest.raises(TypeError, match=rmsg):
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1 * idx
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div_err = lmsg.replace("*", "/")
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with pytest.raises(TypeError, match=div_err):
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idx / 1
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div_err = rmsg.replace("*", "/")
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with pytest.raises(TypeError, match=div_err):
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1 / idx
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floordiv_err = lmsg.replace("*", "//")
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with pytest.raises(TypeError, match=floordiv_err):
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idx // 1
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floordiv_err = rmsg.replace("*", "//")
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with pytest.raises(TypeError, match=floordiv_err):
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1 // idx
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def test_logical_compat(self):
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idx = self.create_index()
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with pytest.raises(TypeError, match="cannot perform all"):
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idx.all()
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with pytest.raises(TypeError, match="cannot perform any"):
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idx.any()
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def test_reindex_base(self):
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idx = self.create_index()
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expected = np.arange(idx.size, dtype=np.intp)
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actual = idx.get_indexer(idx)
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tm.assert_numpy_array_equal(expected, actual)
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with pytest.raises(ValueError, match="Invalid fill method"):
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idx.get_indexer(idx, method="invalid")
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def test_get_indexer_consistency(self, index):
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# See GH 16819
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if isinstance(index, IntervalIndex):
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return
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if index.is_unique or isinstance(index, CategoricalIndex):
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indexer = index.get_indexer(index[0:2])
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assert isinstance(indexer, np.ndarray)
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assert indexer.dtype == np.intp
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else:
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e = "Reindexing only valid with uniquely valued Index objects"
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with pytest.raises(InvalidIndexError, match=e):
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index.get_indexer(index[0:2])
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indexer, _ = index.get_indexer_non_unique(index[0:2])
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assert isinstance(indexer, np.ndarray)
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assert indexer.dtype == np.intp
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def test_ndarray_compat_properties(self):
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idx = self.create_index()
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assert idx.T.equals(idx)
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assert idx.transpose().equals(idx)
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values = idx.values
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for prop in self._compat_props:
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assert getattr(idx, prop) == getattr(values, prop)
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# test for validity
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idx.nbytes
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idx.values.nbytes
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def test_repr_roundtrip(self):
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idx = self.create_index()
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tm.assert_index_equal(eval(repr(idx)), idx)
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def test_repr_max_seq_item_setting(self):
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# GH10182
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idx = self.create_index()
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idx = idx.repeat(50)
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with pd.option_context("display.max_seq_items", None):
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repr(idx)
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assert "..." not in str(idx)
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def test_copy_name(self, index):
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# gh-12309: Check that the "name" argument
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# passed at initialization is honored.
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if isinstance(index, MultiIndex):
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return
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first = type(index)(index, copy=True, name="mario")
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second = type(first)(first, copy=False)
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# Even though "copy=False", we want a new object.
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assert first is not second
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# Not using tm.assert_index_equal() since names differ.
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assert index.equals(first)
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assert first.name == "mario"
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assert second.name == "mario"
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s1 = Series(2, index=first)
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s2 = Series(3, index=second[:-1])
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if not isinstance(index, CategoricalIndex):
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# See gh-13365
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s3 = s1 * s2
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assert s3.index.name == "mario"
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def test_copy_name2(self, index):
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# gh-35592
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if isinstance(index, MultiIndex):
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return
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assert index.copy(name="mario").name == "mario"
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with pytest.raises(ValueError, match="Length of new names must be 1, got 2"):
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index.copy(name=["mario", "luigi"])
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msg = f"{type(index).__name__}.name must be a hashable type"
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with pytest.raises(TypeError, match=msg):
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index.copy(name=[["mario"]])
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def test_copy_dtype_deprecated(self, index):
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# GH35853
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with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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index.copy(dtype=object)
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def test_ensure_copied_data(self, index):
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# Check the "copy" argument of each Index.__new__ is honoured
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# GH12309
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init_kwargs = {}
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if isinstance(index, PeriodIndex):
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# Needs "freq" specification:
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init_kwargs["freq"] = index.freq
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elif isinstance(index, (RangeIndex, MultiIndex, CategoricalIndex)):
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# RangeIndex cannot be initialized from data
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# MultiIndex and CategoricalIndex are tested separately
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return
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index_type = type(index)
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result = index_type(index.values, copy=True, **init_kwargs)
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if is_datetime64tz_dtype(index.dtype):
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result = result.tz_localize("UTC").tz_convert(index.tz)
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if isinstance(index, (DatetimeIndex, TimedeltaIndex)):
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index = index._with_freq(None)
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tm.assert_index_equal(index, result)
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if isinstance(index, PeriodIndex):
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# .values an object array of Period, thus copied
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result = index_type(ordinal=index.asi8, copy=False, **init_kwargs)
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tm.assert_numpy_array_equal(index.asi8, result.asi8, check_same="same")
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elif isinstance(index, IntervalIndex):
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# checked in test_interval.py
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pass
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else:
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result = index_type(index.values, copy=False, **init_kwargs)
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tm.assert_numpy_array_equal(index.values, result.values, check_same="same")
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def test_memory_usage(self, index):
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index._engine.clear_mapping()
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result = index.memory_usage()
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if index.empty:
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# we report 0 for no-length
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assert result == 0
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return
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# non-zero length
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index.get_loc(index[0])
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result2 = index.memory_usage()
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result3 = index.memory_usage(deep=True)
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# RangeIndex, IntervalIndex
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# don't have engines
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if not isinstance(index, (RangeIndex, IntervalIndex)):
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assert result2 > result
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if index.inferred_type == "object":
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assert result3 > result2
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def test_argsort(self, request, index):
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# separately tested
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if isinstance(index, CategoricalIndex):
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return
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result = index.argsort()
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expected = np.array(index).argsort()
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tm.assert_numpy_array_equal(result, expected, check_dtype=False)
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def test_numpy_argsort(self, index):
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result = np.argsort(index)
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expected = index.argsort()
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tm.assert_numpy_array_equal(result, expected)
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# these are the only two types that perform
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# pandas compatibility input validation - the
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# rest already perform separate (or no) such
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# validation via their 'values' attribute as
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# defined in pandas.core.indexes/base.py - they
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# cannot be changed at the moment due to
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# backwards compatibility concerns
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if isinstance(type(index), (CategoricalIndex, RangeIndex)):
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# TODO: why type(index)?
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msg = "the 'axis' parameter is not supported"
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with pytest.raises(ValueError, match=msg):
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np.argsort(index, axis=1)
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msg = "the 'kind' parameter is not supported"
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with pytest.raises(ValueError, match=msg):
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np.argsort(index, kind="mergesort")
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msg = "the 'order' parameter is not supported"
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with pytest.raises(ValueError, match=msg):
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np.argsort(index, order=("a", "b"))
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def test_repeat(self):
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rep = 2
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i = self.create_index()
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expected = Index(i.values.repeat(rep), name=i.name)
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tm.assert_index_equal(i.repeat(rep), expected)
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i = self.create_index()
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rep = np.arange(len(i))
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expected = Index(i.values.repeat(rep), name=i.name)
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tm.assert_index_equal(i.repeat(rep), expected)
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def test_numpy_repeat(self):
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rep = 2
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i = self.create_index()
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expected = i.repeat(rep)
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tm.assert_index_equal(np.repeat(i, rep), expected)
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msg = "the 'axis' parameter is not supported"
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with pytest.raises(ValueError, match=msg):
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np.repeat(i, rep, axis=0)
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@pytest.mark.parametrize("klass", [list, tuple, np.array, Series])
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def test_where(self, klass):
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i = self.create_index()
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if isinstance(i, (pd.DatetimeIndex, pd.TimedeltaIndex)):
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# where does not preserve freq
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i = i._with_freq(None)
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cond = [True] * len(i)
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result = i.where(klass(cond))
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expected = i
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tm.assert_index_equal(result, expected)
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cond = [False] + [True] * len(i[1:])
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expected = Index([i._na_value] + i[1:].tolist(), dtype=i.dtype)
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result = i.where(klass(cond))
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tm.assert_index_equal(result, expected)
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def test_insert_base(self, index):
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result = index[1:4]
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if not len(index):
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return
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# test 0th element
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assert index[0:4].equals(result.insert(0, index[0]))
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def test_delete_base(self, index):
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if not len(index):
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return
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if isinstance(index, RangeIndex):
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# tested in class
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return
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expected = index[1:]
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result = index.delete(0)
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assert result.equals(expected)
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assert result.name == expected.name
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expected = index[:-1]
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result = index.delete(-1)
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assert result.equals(expected)
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assert result.name == expected.name
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length = len(index)
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msg = f"index {length} is out of bounds for axis 0 with size {length}"
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with pytest.raises(IndexError, match=msg):
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index.delete(length)
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def test_equals(self, index):
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if isinstance(index, IntervalIndex):
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# IntervalIndex tested separately, the index.equals(index.astype(object))
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# fails for IntervalIndex
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return
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assert index.equals(index)
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assert index.equals(index.copy())
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assert index.equals(index.astype(object))
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assert not index.equals(list(index))
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assert not index.equals(np.array(index))
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# Cannot pass in non-int64 dtype to RangeIndex
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if not isinstance(index, RangeIndex):
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same_values = Index(index, dtype=object)
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assert index.equals(same_values)
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assert same_values.equals(index)
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if index.nlevels == 1:
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# do not test MultiIndex
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assert not index.equals(Series(index))
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def test_equals_op(self):
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# GH9947, GH10637
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index_a = self.create_index()
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n = len(index_a)
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index_b = index_a[0:-1]
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index_c = index_a[0:-1].append(index_a[-2:-1])
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index_d = index_a[0:1]
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msg = "Lengths must match|could not be broadcast"
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with pytest.raises(ValueError, match=msg):
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index_a == index_b
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expected1 = np.array([True] * n)
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expected2 = np.array([True] * (n - 1) + [False])
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tm.assert_numpy_array_equal(index_a == index_a, expected1)
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tm.assert_numpy_array_equal(index_a == index_c, expected2)
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# test comparisons with numpy arrays
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array_a = np.array(index_a)
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array_b = np.array(index_a[0:-1])
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array_c = np.array(index_a[0:-1].append(index_a[-2:-1]))
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array_d = np.array(index_a[0:1])
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with pytest.raises(ValueError, match=msg):
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index_a == array_b
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tm.assert_numpy_array_equal(index_a == array_a, expected1)
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tm.assert_numpy_array_equal(index_a == array_c, expected2)
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# test comparisons with Series
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series_a = Series(array_a)
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series_b = Series(array_b)
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series_c = Series(array_c)
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series_d = Series(array_d)
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with pytest.raises(ValueError, match=msg):
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index_a == series_b
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tm.assert_numpy_array_equal(index_a == series_a, expected1)
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tm.assert_numpy_array_equal(index_a == series_c, expected2)
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# cases where length is 1 for one of them
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with pytest.raises(ValueError, match="Lengths must match"):
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index_a == index_d
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with pytest.raises(ValueError, match="Lengths must match"):
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index_a == series_d
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with pytest.raises(ValueError, match="Lengths must match"):
|
|
index_a == array_d
|
|
msg = "Can only compare identically-labeled Series objects"
|
|
with pytest.raises(ValueError, match=msg):
|
|
series_a == series_d
|
|
with pytest.raises(ValueError, match="Lengths must match"):
|
|
series_a == array_d
|
|
|
|
# comparing with a scalar should broadcast; note that we are excluding
|
|
# MultiIndex because in this case each item in the index is a tuple of
|
|
# length 2, and therefore is considered an array of length 2 in the
|
|
# comparison instead of a scalar
|
|
if not isinstance(index_a, MultiIndex):
|
|
expected3 = np.array([False] * (len(index_a) - 2) + [True, False])
|
|
# assuming the 2nd to last item is unique in the data
|
|
item = index_a[-2]
|
|
tm.assert_numpy_array_equal(index_a == item, expected3)
|
|
# For RangeIndex we can convert to Int64Index
|
|
tm.assert_series_equal(series_a == item, Series(expected3))
|
|
|
|
def test_format(self):
|
|
# GH35439
|
|
idx = self.create_index()
|
|
expected = [str(x) for x in idx]
|
|
assert idx.format() == expected
|
|
|
|
def test_format_empty(self):
|
|
# GH35712
|
|
empty_idx = self._holder([])
|
|
assert empty_idx.format() == []
|
|
assert empty_idx.format(name=True) == [""]
|
|
|
|
def test_hasnans_isnans(self, index):
|
|
# GH 11343, added tests for hasnans / isnans
|
|
if isinstance(index, MultiIndex):
|
|
return
|
|
|
|
# cases in indices doesn't include NaN
|
|
idx = index.copy(deep=True)
|
|
expected = np.array([False] * len(idx), dtype=bool)
|
|
tm.assert_numpy_array_equal(idx._isnan, expected)
|
|
assert idx.hasnans is False
|
|
|
|
idx = index.copy(deep=True)
|
|
values = np.asarray(idx.values)
|
|
|
|
if len(index) == 0:
|
|
return
|
|
elif isinstance(index, DatetimeIndexOpsMixin):
|
|
values[1] = iNaT
|
|
elif isinstance(index, (Int64Index, UInt64Index)):
|
|
return
|
|
else:
|
|
values[1] = np.nan
|
|
|
|
if isinstance(index, PeriodIndex):
|
|
idx = type(index)(values, freq=index.freq)
|
|
else:
|
|
idx = type(index)(values)
|
|
|
|
expected = np.array([False] * len(idx), dtype=bool)
|
|
expected[1] = True
|
|
tm.assert_numpy_array_equal(idx._isnan, expected)
|
|
assert idx.hasnans is True
|
|
|
|
def test_fillna(self, index):
|
|
# GH 11343
|
|
if len(index) == 0:
|
|
pass
|
|
elif isinstance(index, MultiIndex):
|
|
idx = index.copy(deep=True)
|
|
msg = "isna is not defined for MultiIndex"
|
|
with pytest.raises(NotImplementedError, match=msg):
|
|
idx.fillna(idx[0])
|
|
else:
|
|
idx = index.copy(deep=True)
|
|
result = idx.fillna(idx[0])
|
|
tm.assert_index_equal(result, idx)
|
|
assert result is not idx
|
|
|
|
msg = "'value' must be a scalar, passed: "
|
|
with pytest.raises(TypeError, match=msg):
|
|
idx.fillna([idx[0]])
|
|
|
|
idx = index.copy(deep=True)
|
|
values = np.asarray(idx.values)
|
|
|
|
if isinstance(index, DatetimeIndexOpsMixin):
|
|
values[1] = iNaT
|
|
elif isinstance(index, (Int64Index, UInt64Index)):
|
|
return
|
|
else:
|
|
values[1] = np.nan
|
|
|
|
if isinstance(index, PeriodIndex):
|
|
idx = type(index)(values, freq=index.freq)
|
|
else:
|
|
idx = type(index)(values)
|
|
|
|
expected = np.array([False] * len(idx), dtype=bool)
|
|
expected[1] = True
|
|
tm.assert_numpy_array_equal(idx._isnan, expected)
|
|
assert idx.hasnans is True
|
|
|
|
def test_nulls(self, index):
|
|
# this is really a smoke test for the methods
|
|
# as these are adequately tested for function elsewhere
|
|
if len(index) == 0:
|
|
tm.assert_numpy_array_equal(index.isna(), np.array([], dtype=bool))
|
|
elif isinstance(index, MultiIndex):
|
|
idx = index.copy()
|
|
msg = "isna is not defined for MultiIndex"
|
|
with pytest.raises(NotImplementedError, match=msg):
|
|
idx.isna()
|
|
elif not index.hasnans:
|
|
tm.assert_numpy_array_equal(index.isna(), np.zeros(len(index), dtype=bool))
|
|
tm.assert_numpy_array_equal(index.notna(), np.ones(len(index), dtype=bool))
|
|
else:
|
|
result = isna(index)
|
|
tm.assert_numpy_array_equal(index.isna(), result)
|
|
tm.assert_numpy_array_equal(index.notna(), ~result)
|
|
|
|
def test_empty(self):
|
|
# GH 15270
|
|
index = self.create_index()
|
|
assert not index.empty
|
|
assert index[:0].empty
|
|
|
|
def test_join_self_unique(self, join_type):
|
|
index = self.create_index()
|
|
if index.is_unique:
|
|
joined = index.join(index, how=join_type)
|
|
assert (index == joined).all()
|
|
|
|
def test_map(self):
|
|
# callable
|
|
index = self.create_index()
|
|
|
|
# we don't infer UInt64
|
|
if isinstance(index, pd.UInt64Index):
|
|
expected = index.astype("int64")
|
|
else:
|
|
expected = index
|
|
|
|
result = index.map(lambda x: x)
|
|
# For RangeIndex we convert to Int64Index
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize(
|
|
"mapper",
|
|
[
|
|
lambda values, index: {i: e for e, i in zip(values, index)},
|
|
lambda values, index: Series(values, index),
|
|
],
|
|
)
|
|
def test_map_dictlike(self, mapper):
|
|
|
|
index = self.create_index()
|
|
if isinstance(index, (pd.CategoricalIndex, pd.IntervalIndex)):
|
|
pytest.skip(f"skipping tests for {type(index)}")
|
|
|
|
identity = mapper(index.values, index)
|
|
|
|
# we don't infer to UInt64 for a dict
|
|
if isinstance(index, pd.UInt64Index) and isinstance(identity, dict):
|
|
expected = index.astype("int64")
|
|
else:
|
|
expected = index
|
|
|
|
result = index.map(identity)
|
|
# For RangeIndex we convert to Int64Index
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
# empty mappable
|
|
expected = Index([np.nan] * len(index))
|
|
result = index.map(mapper(expected, index))
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
def test_map_str(self):
|
|
# GH 31202
|
|
index = self.create_index()
|
|
result = index.map(str)
|
|
expected = Index([str(x) for x in index], dtype=object)
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
def test_putmask_with_wrong_mask(self):
|
|
# GH18368
|
|
index = self.create_index()
|
|
fill = index[0]
|
|
|
|
msg = "putmask: mask and data must be the same size"
|
|
with pytest.raises(ValueError, match=msg):
|
|
index.putmask(np.ones(len(index) + 1, np.bool_), fill)
|
|
|
|
with pytest.raises(ValueError, match=msg):
|
|
index.putmask(np.ones(len(index) - 1, np.bool_), fill)
|
|
|
|
with pytest.raises(ValueError, match=msg):
|
|
index.putmask("foo", fill)
|
|
|
|
@pytest.mark.parametrize("copy", [True, False])
|
|
@pytest.mark.parametrize("name", [None, "foo"])
|
|
@pytest.mark.parametrize("ordered", [True, False])
|
|
def test_astype_category(self, copy, name, ordered):
|
|
# GH 18630
|
|
index = self.create_index()
|
|
if name:
|
|
index = index.rename(name)
|
|
|
|
# standard categories
|
|
dtype = CategoricalDtype(ordered=ordered)
|
|
result = index.astype(dtype, copy=copy)
|
|
expected = CategoricalIndex(index.values, name=name, ordered=ordered)
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
# non-standard categories
|
|
dtype = CategoricalDtype(index.unique().tolist()[:-1], ordered)
|
|
result = index.astype(dtype, copy=copy)
|
|
expected = CategoricalIndex(index.values, name=name, dtype=dtype)
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
if ordered is False:
|
|
# dtype='category' defaults to ordered=False, so only test once
|
|
result = index.astype("category", copy=copy)
|
|
expected = CategoricalIndex(index.values, name=name)
|
|
tm.assert_index_equal(result, expected)
|
|
|
|
def test_is_unique(self):
|
|
# initialize a unique index
|
|
index = self.create_index().drop_duplicates()
|
|
assert index.is_unique is True
|
|
|
|
# empty index should be unique
|
|
index_empty = index[:0]
|
|
assert index_empty.is_unique is True
|
|
|
|
# test basic dupes
|
|
index_dup = index.insert(0, index[0])
|
|
assert index_dup.is_unique is False
|
|
|
|
# single NA should be unique
|
|
index_na = index.insert(0, np.nan)
|
|
assert index_na.is_unique is True
|
|
|
|
# multiple NA should not be unique
|
|
index_na_dup = index_na.insert(0, np.nan)
|
|
assert index_na_dup.is_unique is False
|
|
|
|
@pytest.mark.arm_slow
|
|
def test_engine_reference_cycle(self):
|
|
# GH27585
|
|
index = self.create_index()
|
|
nrefs_pre = len(gc.get_referrers(index))
|
|
index._engine
|
|
assert len(gc.get_referrers(index)) == nrefs_pre
|
|
|
|
def test_getitem_2d_deprecated(self):
|
|
# GH#30588
|
|
idx = self.create_index()
|
|
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
|
|
res = idx[:, None]
|
|
|
|
assert isinstance(res, np.ndarray), type(res)
|
|
|
|
def test_contains_requires_hashable_raises(self):
|
|
idx = self.create_index()
|
|
|
|
msg = "unhashable type: 'list'"
|
|
with pytest.raises(TypeError, match=msg):
|
|
[] in idx
|
|
|
|
msg = "|".join(
|
|
[
|
|
r"unhashable type: 'dict'",
|
|
r"must be real number, not dict",
|
|
r"an integer is required",
|
|
r"\{\}",
|
|
r"pandas\._libs\.interval\.IntervalTree' is not iterable",
|
|
]
|
|
)
|
|
with pytest.raises(TypeError, match=msg):
|
|
{} in idx._engine
|
|
|
|
def test_copy_shares_cache(self):
|
|
# GH32898, GH36840
|
|
idx = self.create_index()
|
|
idx.get_loc(idx[0]) # populates the _cache.
|
|
copy = idx.copy()
|
|
|
|
assert copy._cache is idx._cache
|
|
|
|
def test_shallow_copy_shares_cache(self):
|
|
# GH32669, GH36840
|
|
idx = self.create_index()
|
|
idx.get_loc(idx[0]) # populates the _cache.
|
|
shallow_copy = idx._shallow_copy()
|
|
|
|
assert shallow_copy._cache is idx._cache
|
|
|
|
shallow_copy = idx._shallow_copy(idx._data)
|
|
assert shallow_copy._cache is not idx._cache
|
|
assert shallow_copy._cache == {}
|