CLN: various related to numeric indexes (#41615)

Author: topper-123

pandas/_testing/__init__.py

@@ -30,9 +30,13 @@
 from pandas.core.dtypes.common import (
     is_datetime64_dtype,
     is_datetime64tz_dtype,
+    is_float_dtype,
+    is_integer_dtype,
     is_period_dtype,
     is_sequence,
     is_timedelta64_dtype,
+    is_unsigned_integer_dtype,
+    pandas_dtype,
 )
 
 import pandas as pd
@@ -41,11 +45,14 @@
     CategoricalIndex,
     DataFrame,
     DatetimeIndex,
+    Float64Index,
     Index,
+    Int64Index,
     IntervalIndex,
     MultiIndex,
     RangeIndex,
     Series,
+    UInt64Index,
     bdate_range,
 )
 from pandas._testing._io import (  # noqa:F401
@@ -292,21 +299,41 @@ 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)
+    assert isinstance(dtype, np.dtype)
+
+    if is_integer_dtype(dtype):
+        values = np.arange(k, dtype=dtype)
+        if is_unsigned_integer_dtype(dtype):
+            values += 2 ** (dtype.itemsize * 8 - 1)
+    elif is_float_dtype(dtype):
+        values = np.random.random_sample(k) - np.random.random_sample(1)
+        values.sort()
+        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, name=name, 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

@@ -106,20 +106,22 @@ def _can_hold_na(self) -> bool:
         else:
             return False
 
-    @cache_readonly
+    _engine_types: dict[np.dtype, type[libindex.IndexEngine]] = {
+        np.dtype(np.int8): libindex.Int8Engine,
+        np.dtype(np.int16): libindex.Int16Engine,
+        np.dtype(np.int32): libindex.Int32Engine,
+        np.dtype(np.int64): libindex.Int64Engine,
+        np.dtype(np.uint8): libindex.UInt8Engine,
+        np.dtype(np.uint16): libindex.UInt16Engine,
+        np.dtype(np.uint32): libindex.UInt32Engine,
+        np.dtype(np.uint64): libindex.UInt64Engine,
+        np.dtype(np.float32): libindex.Float32Engine,
+        np.dtype(np.float64): libindex.Float64Engine,
+    }
+
+    @property
     def _engine_type(self):
-        return {
-            np.int8: libindex.Int8Engine,
-            np.int16: libindex.Int16Engine,
-            np.int32: libindex.Int32Engine,
-            np.int64: libindex.Int64Engine,
-            np.uint8: libindex.UInt8Engine,
-            np.uint16: libindex.UInt16Engine,
-            np.uint32: libindex.UInt32Engine,
-            np.uint64: libindex.UInt64Engine,
-            np.float32: libindex.Float32Engine,
-            np.float64: libindex.Float64Engine,
-        }[self.dtype.type]
+        return self._engine_types[self.dtype]
 
     @cache_readonly
     def inferred_type(self) -> 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)