Use less idx fixture in multi

Author: mroeschke

pandas/tests/indexes/multi/test_analytics.py

@@ -11,13 +11,15 @@
 import pandas._testing as tm
 
 
-def test_infer_objects(idx):
+def test_infer_objects():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     with pytest.raises(NotImplementedError, match="to_frame"):
         idx.infer_objects()
 
 
-def test_shift(idx):
+def test_shift():
     # GH8083 test the base class for shift
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     msg = (
         "This method is only implemented for DatetimeIndex, PeriodIndex and "
         "TimedeltaIndex; Got type MultiIndex"
@@ -76,8 +78,9 @@ def test_truncate_multiindex():
 # TODO: reshape
 
 
-def test_reorder_levels(idx):
+def test_reorder_levels():
     # this blows up
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     with pytest.raises(IndexError, match="^Too many levels"):
         idx.reorder_levels([2, 1, 0])
 
@@ -174,9 +177,9 @@ def test_sub(idx):
         first.tolist() - idx[-3:]
 
 
-def test_map(idx):
+def test_map():
     # callable
-    index = idx
+    index = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
 
     result = index.map(lambda x: x)
     tm.assert_index_equal(result, index)
@@ -235,10 +238,11 @@ def test_map_dictlike(idx, mapper):
     ],
     ids=lambda func: func.__name__,
 )
-def test_numpy_ufuncs(idx, func):
+def test_numpy_ufuncs(func):
     # test ufuncs of numpy. see:
     # https://numpy.org/doc/stable/reference/ufuncs.html
 
+    idx = MultiIndex(levels=[["A", "B"]], codes=[[0, 1]])
     expected_exception = TypeError
     msg = (
         "loop of ufunc does not support argument 0 of type tuple which "
@@ -254,6 +258,7 @@ def test_numpy_ufuncs(idx, func):
     ids=lambda func: func.__name__,
 )
 def test_numpy_type_funcs(idx, func):
+    idx = MultiIndex(levels=[["A", "B"]], codes=[[0, 1]])
     msg = (
         f"ufunc '{func.__name__}' not supported for the input types, and the inputs "
         "could not be safely coerced to any supported types according to "

pandas/tests/indexes/multi/test_astype.py

@@ -3,10 +3,12 @@
 
 from pandas.core.dtypes.dtypes import CategoricalDtype
 
+from pandas import MultiIndex
 import pandas._testing as tm
 
 
-def test_astype(idx):
+def test_astype():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]], names=["foo"])
     expected = idx.copy()
     actual = idx.astype("O")
     tm.assert_copy(actual.levels, expected.levels)
@@ -18,7 +20,8 @@ def test_astype(idx):
 
 
 @pytest.mark.parametrize("ordered", [True, False])
-def test_astype_category(idx, ordered):
+def test_astype_category(ordered):
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     # GH 18630
     msg = "> 1 ndim Categorical are not supported at this time"
     with pytest.raises(NotImplementedError, match=msg):

pandas/tests/indexes/multi/test_compat.py

@@ -6,7 +6,8 @@
 import pandas._testing as tm
 
 
-def test_numeric_compat(idx):
+def test_numeric_compat():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     with pytest.raises(TypeError, match="cannot perform __mul__"):
         idx * 1
 
@@ -29,7 +30,8 @@ def test_numeric_compat(idx):
 
 
 @pytest.mark.parametrize("method", ["all", "any", "__invert__"])
-def test_logical_compat(idx, method):
+def test_logical_compat(method):
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     msg = f"cannot perform {method}"
 
     with pytest.raises(TypeError, match=msg):

pandas/tests/indexes/multi/test_constructors.py

@@ -385,7 +385,8 @@ def test_from_tuples_empty():
     tm.assert_index_equal(result, expected)
 
 
-def test_from_tuples_index_values(idx):
+def test_from_tuples_index_values():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     result = MultiIndex.from_tuples(idx)
     assert (result.values == idx.values).all()
 

pandas/tests/indexes/multi/test_conversion.py

@@ -9,7 +9,8 @@
 import pandas._testing as tm
 
 
-def test_to_numpy(idx):
+def test_to_numpy():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     result = idx.to_numpy()
     exp = idx.values
     tm.assert_numpy_array_equal(result, exp)

pandas/tests/indexes/multi/test_copy.py

@@ -26,19 +26,22 @@ def assert_multiindex_copied(copy, original):
     assert copy.sortorder == original.sortorder
 
 
-def test_copy(idx):
+def test_copy():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     i_copy = idx.copy()
 
     assert_multiindex_copied(i_copy, idx)
 
 
-def test_shallow_copy(idx):
+def test_shallow_copy():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     i_copy = idx._view()
 
     assert_multiindex_copied(i_copy, idx)
 
 
-def test_view(idx):
+def test_view():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     i_view = idx.view()
     assert_multiindex_copied(i_view, idx)
 

pandas/tests/indexes/multi/test_duplicates.py

@@ -145,13 +145,19 @@ def test_duplicate_meta_data():
         assert idx.drop_duplicates().names == idx.names
 
 
-def test_has_duplicates(idx, idx_dup):
-    # see fixtures
+def test_has_duplicates():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     assert idx.is_unique is True
     assert idx.has_duplicates is False
+
+
+def test_has_duplicates_with_dups(idx_dup):
+    # see fixtures
     assert idx_dup.is_unique is False
     assert idx_dup.has_duplicates is True
 
+
+def test_has_duplicates_other():
     mi = MultiIndex(
         levels=[[0, 1], [0, 1, 2]], codes=[[0, 0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 0, 1, 2]]
     )

pandas/tests/indexes/multi/test_equivalence.py

@@ -12,7 +12,8 @@
 import pandas._testing as tm
 
 
-def test_equals(idx):
+def test_equals():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     assert idx.equals(idx)
     assert idx.equals(idx.copy())
     assert idx.equals(idx.astype(object))
@@ -26,10 +27,6 @@ def test_equals(idx):
     assert idx.equals(same_values)
     assert same_values.equals(idx)
 
-    if idx.nlevels == 1:
-        # do not test MultiIndex
-        assert not idx.equals(Series(idx))
-
 
 def test_equals_op(idx):
     # GH9947, GH10637
@@ -132,7 +129,8 @@ def test_compare_tuple_strs():
     tm.assert_numpy_array_equal(result, expected)
 
 
-def test_equals_multi(idx):
+def test_equals_multi():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     assert idx.equals(idx)
     assert not idx.equals(idx.values)
     assert idx.equals(Index(idx.values))
@@ -141,6 +139,8 @@ def test_equals_multi(idx):
     assert not idx.equals(idx[:-1])
     assert not idx.equals(idx[-1])
 
+
+def test_equals_multi_different_levels(idx):
     # different number of levels
     index = MultiIndex(
         levels=[Index(list(range(4))), Index(list(range(4))), Index(list(range(4)))],
@@ -181,7 +181,8 @@ def test_equals_multi(idx):
     assert not idx.equals(index)
 
 
-def test_identical(idx):
+def test_identical():
+    idx = MultiIndex(levels=[[0, 1], [2, 3]], codes=[[0, 1], [0, 1]])
     mi = idx.copy()
     mi2 = idx.copy()
     assert mi.identical(mi2)
@@ -249,12 +250,14 @@ def test_is_():
     assert not mi5.is_(mi)
 
 
-def test_is_all_dates(idx):
+def test_is_all_dates():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     assert not idx._is_all_dates
 
 
-def test_is_numeric(idx):
+def test_is_numeric():
     # MultiIndex is never numeric
+    idx = MultiIndex(levels=[["A", "B"]], codes=[[0, 1]])
     assert not is_any_real_numeric_dtype(idx)
 
 

pandas/tests/indexes/multi/test_formats.py

@@ -9,8 +9,9 @@
 import pandas._testing as tm
 
 
-def test_format(idx):
+def test_format():
     msg = "MultiIndex.format is deprecated"
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     with tm.assert_produces_warning(FutureWarning, match=msg):
         idx.format()
         idx[:0].format()
@@ -70,8 +71,9 @@ def test_unicode_string_with_unicode():
     str(idx)
 
 
-def test_repr_max_seq_item_setting(idx):
+def test_repr_max_seq_item_setting():
     # GH10182
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     idx = idx.repeat(50)
     with pd.option_context("display.max_seq_items", None):
         repr(idx)

pandas/tests/indexes/multi/test_get_set.py

@@ -242,7 +242,8 @@ def test_set_codes(idx):
     assert result.equals(expected)
 
 
-def test_set_levels_codes_names_bad_input(idx):
+def test_set_levels_codes_names_bad_input():
+    idx = MultiIndex(levels=[["A", "B"], ["B", "C"]], codes=[[0, 1], [0, 1]])
     levels, codes = idx.levels, idx.codes
     names = idx.names
 

pandas/tests/indexes/multi/test_integrity.py

@@ -163,10 +163,11 @@ def test_take_invalid_kwargs():
         idx.take(indices, mode="clip")
 
 
-def test_isna_behavior(idx):
+def test_isna_behavior():
     # should not segfault GH5123
     # NOTE: if MI representation changes, may make sense to allow
     # isna(MI)
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     msg = "isna is not defined for MultiIndex"
     with pytest.raises(NotImplementedError, match=msg):
         pd.isna(idx)
@@ -208,12 +209,14 @@ def test_mi_hashtable_populated_attribute_error(monkeypatch):
         df["a"].foo()
 
 
-def test_can_hold_identifiers(idx):
+def test_can_hold_identifiers():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     key = idx[0]
     assert idx._can_hold_identifiers_and_holds_name(key) is True
 
 
-def test_metadata_immutable(idx):
+def test_metadata_immutable():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     levels, codes = idx.levels, idx.codes
     # shouldn't be able to set at either the top level or base level
     mutable_regex = re.compile("does not support mutable operations")
@@ -265,7 +268,8 @@ def test_rangeindex_fallback_coercion_bug():
     tm.assert_index_equal(result, expected)
 
 
-def test_memory_usage(idx):
+def test_memory_usage():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     result = idx.memory_usage()
     if len(idx):
         idx.get_loc(idx[0])
@@ -285,5 +289,6 @@ def test_memory_usage(idx):
         assert result == 0
 
 
-def test_nlevels(idx):
-    assert idx.nlevels == 2
+def test_nlevels():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
+    assert idx.nlevels == 1

pandas/tests/indexes/multi/test_join.py

@@ -50,7 +50,8 @@ def test_join_level_corner_case(idx):
         idx.join(idx, level=1)
 
 
-def test_join_self(idx, join_type):
+def test_join_self(join_type):
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     result = idx.join(idx, how=join_type)
     expected = idx
     if join_type == "outer":

pandas/tests/indexes/multi/test_missing.py

@@ -6,8 +6,9 @@
 import pandas._testing as tm
 
 
-def test_fillna(idx):
+def test_fillna():
     # GH 11343
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     msg = "isna is not defined for MultiIndex"
     with pytest.raises(NotImplementedError, match=msg):
         idx.fillna(idx[0])
@@ -53,18 +54,19 @@ def test_dropna():
     tm.assert_index_equal(idx.dropna(how="all"), expected)
 
 
-def test_nulls(idx):
+def test_nulls():
     # this is really a smoke test for the methods
     # as these are adequately tested for function elsewhere
-
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     msg = "isna is not defined for MultiIndex"
     with pytest.raises(NotImplementedError, match=msg):
         idx.isna()
 
 
 @pytest.mark.xfail(reason="isna is not defined for MultiIndex")
-def test_hasnans_isnans(idx):
+def test_hasnans_isnans():
     # GH 11343, added tests for hasnans / isnans
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     index = idx.copy()
 
     # cases in indices doesn't include NaN

pandas/tests/indexes/multi/test_reindex.py

@@ -9,7 +9,12 @@
 import pandas._testing as tm
 
 
-def test_reindex(idx):
+def test_reindex():
+    idx = MultiIndex(
+        levels=[list(range(5)), list(range(1, 6))],
+        codes=[list(range(5)), list(range(5))],
+        names=["first", "second"],
+    )
     result, indexer = idx.reindex(list(idx[:4]))
     assert isinstance(result, MultiIndex)
     assert result.names == ["first", "second"]
@@ -92,7 +97,8 @@ def test_reindex_lvl_preserves_type_if_target_is_empty_list_or_array(
     assert mi.reindex([], level=1)[0].levels[1].dtype == dti.dtype
 
 
-def test_reindex_base(idx):
+def test_reindex_base():
+    idx = MultiIndex(levels=[[0, 1]], codes=[[0, 1]])
     expected = np.arange(idx.size, dtype=np.intp)
 
     actual = idx.get_indexer(idx)