CLN: various related to numeric indexes

Author: topper-123

pandas/_testing/__init__.py

@@ -33,6 +33,7 @@
     is_period_dtype,
     is_sequence,
     is_timedelta64_dtype,
+    pandas_dtype,
 )
 
 import pandas as pd
@@ -41,11 +42,14 @@
     CategoricalIndex,
     DataFrame,
     DatetimeIndex,
+    Float64Index,
     Index,
+    Int64Index,
     IntervalIndex,
     MultiIndex,
     RangeIndex,
     Series,
+    UInt64Index,
     bdate_range,
 )
 from pandas._testing._io import (  # noqa:F401
@@ -292,21 +296,40 @@ def makeBoolIndex(k=10, name=None):
     return Index([False, True] + [False] * (k - 2), name=name)
 
 
+def makeNumericIndex(k=10, name=None, *, dtype):
+    dtype = pandas_dtype(dtype)
+
+    if dtype.kind == "i":
+        values = list(range(k))
+    elif dtype.kind == "u":
+        start_num = 2 ** (dtype.itemsize * 8 - 1)
+        values = [start_num + i for i in range(k)]
+    elif dtype.kind == "f":
+        values = sorted(np.random.random_sample(k)) - np.random.random_sample(1)
+        values = values * (10 ** np.random.randint(0, 9))
+    else:
+        raise NotImplementedError(f"wrong dtype {dtype}")
+
+    return Index(values, dtype=dtype, name=name)
+
+
 def makeIntIndex(k=10, name=None):
-    return Index(list(range(k)), name=name)
+    base_idx = makeNumericIndex(k, dtype="int64")
+    return Int64Index(base_idx)
 
 
 def makeUIntIndex(k=10, name=None):
-    return Index([2 ** 63 + i for i in range(k)], name=name)
+    base_idx = makeNumericIndex(k, name=name, dtype="uint64")
+    return UInt64Index(base_idx)
 
 
 def makeRangeIndex(k=10, name=None, **kwargs):
     return RangeIndex(0, k, 1, name=name, **kwargs)
 
 
 def makeFloatIndex(k=10, name=None):
-    values = sorted(np.random.random_sample(k)) - np.random.random_sample(1)
-    return Index(values * (10 ** np.random.randint(0, 9)), name=name)
+    base_idx = makeNumericIndex(k, name=name, dtype="float64")
+    return Float64Index(base_idx)
 
 
 def makeDateIndex(k: int = 10, freq="B", name=None, **kwargs) -> DatetimeIndex:

pandas/_testing/asserters.py

@@ -308,7 +308,7 @@ def assert_index_equal(
     """
     __tracebackhide__ = True
 
-    def _check_types(left, right, obj="Index"):
+    def _check_types(left, right, obj="Index") -> None:
         if not exact:
             return
 

pandas/core/indexes/numeric.py

@@ -107,7 +107,7 @@ def _can_hold_na(self) -> bool:
         else:
             return False
 
-    @cache_readonly
+    @property
     def _engine_type(self):
         return {
             np.int8: libindex.Int8Engine,
@@ -229,7 +229,10 @@ def astype(self, dtype, copy=True):
 
     @doc(Index._should_fallback_to_positional)
     def _should_fallback_to_positional(self) -> bool:
-        return False
+        if is_float_dtype(self.dtype):
+            return False
+        else:
+            return super()._should_fallback_to_positional()
 
     @doc(Index._convert_slice_indexer)
     def _convert_slice_indexer(self, key: slice, kind: str):

pandas/tests/api/test_api.py

@@ -214,7 +214,7 @@ def test_api(self):
             + self.funcs_to
             + self.private_modules
         )
-        self.check(pd, checkthese, self.ignored)
+        self.check(namespace=pd, expected=checkthese, ignored=self.ignored)
 
     def test_depr(self):
         deprecated_list = (

pandas/tests/base/test_unique.py

@@ -23,12 +23,12 @@ def test_unique(index_or_series_obj):
     if isinstance(obj, pd.MultiIndex):
         expected = pd.MultiIndex.from_tuples(unique_values)
         expected.names = obj.names
-        tm.assert_index_equal(result, expected)
+        tm.assert_index_equal(result, expected, exact=True)
     elif isinstance(obj, pd.Index):
         expected = pd.Index(unique_values, dtype=obj.dtype)
         if is_datetime64tz_dtype(obj.dtype):
             expected = expected.normalize()
-        tm.assert_index_equal(result, expected)
+        tm.assert_index_equal(result, expected, exact=True)
     else:
         expected = np.array(unique_values)
         tm.assert_numpy_array_equal(result, expected)
@@ -67,7 +67,7 @@ def test_unique_null(null_obj, index_or_series_obj):
         if is_datetime64tz_dtype(obj.dtype):
             result = result.normalize()
             expected = expected.normalize()
-        tm.assert_index_equal(result, expected)
+        tm.assert_index_equal(result, expected, exact=True)
     else:
         expected = np.array(unique_values, dtype=obj.dtype)
         tm.assert_numpy_array_equal(result, expected)
@@ -118,7 +118,7 @@ def test_unique_bad_unicode(idx_or_series_w_bad_unicode):
 
     if isinstance(obj, pd.Index):
         expected = pd.Index(["\ud83d"], dtype=object)
-        tm.assert_index_equal(result, expected)
+        tm.assert_index_equal(result, expected, exact=True)
     else:
         expected = np.array(["\ud83d"], dtype=object)
         tm.assert_numpy_array_equal(result, expected)