GH1501 Disable creating and converting Index to float16 types

pandas-stubs/core/indexes/base.pyi

@@ -104,6 +104,7 @@ from pandas._typing import (
     MaskType,
     NaPosition,
     NDArrayT,
+    NumpyFloat16DtypeArg,
     NumpyFloatNot16DtypeArg,
     NumpyNotTimeDtypeArg,
     NumpyTimedeltaDtypeArg,
@@ -189,6 +190,16 @@ class Index(IndexOpsMixin[S1], ElementOpsMixin[S1]):
         tupleize_cols: bool = ...,
     ) -> Index[float]: ...
     @overload
+    def __new__(
+        cls,
+        data: AxesData = ...,
+        *,
+        dtype: NumpyFloat16DtypeArg,
+        copy: bool = ...,
+        name: Hashable = ...,
+        tupleize_cols: bool = ...,
+    ) -> Never: ...
+    @overload
     def __new__(
         cls,
         data: AxesData,
@@ -395,6 +406,12 @@ class Index(IndexOpsMixin[S1], ElementOpsMixin[S1]):
         cls: NumpyNotTimeDtypeArg | NumpyTimedeltaDtypeArg | NumpyTimestampDtypeArg,
     ) -> np_1darray: ...
     @overload
+    def astype(
+        self,
+        dtype: NumpyFloat16DtypeArg,
+        copy: bool = True,
+    ) -> Never: ...
+    @overload
     def astype(
         self,
         dtype: FloatNotNumpy16DtypeArg | PandasAstypeFloatDtypeArg,

pandas-stubs/core/indexes/interval.pyi

@@ -243,7 +243,7 @@ class IntervalIndex(ExtensionIndex[IntervalT, np.object_], IntervalMixin):
     def __contains__(self, key: IntervalT) -> bool: ...  # type: ignore[overload-overlap] # pyright: ignore[reportOverlappingOverload]
     @overload
     def __contains__(self, key: object) -> Literal[False]: ...
-    def astype(self, dtype: DtypeArg, copy: bool = True) -> IntervalIndex: ...
+    def astype(self, dtype: DtypeArg, copy: bool = True) -> IntervalIndex: ...  # type: ignore[override]  # pyright: ignore[reportIncompatibleMethodOverride]
     @property
     def inferred_type(self) -> str: ...
     def memory_usage(self, deep: bool = False) -> int: ...

tests/indexes/test_index_float.py

@@ -1,12 +1,18 @@
-from typing import TYPE_CHECKING
+from typing import (
+    TYPE_CHECKING,
+)
 
 import numpy as np
 import pandas as pd
 import pytest
-from typing_extensions import assert_type
+from typing_extensions import (
+    Never,
+    assert_type,
+)
 
 from tests import (
     ASTYPE_FLOAT_NOT_NUMPY16_ARGS,
+    TYPE_CHECKING_INVALID_USAGE,
     TYPE_FLOAT_NOT_NUMPY16_ARGS,
     check,
     exception_on_platform,
@@ -149,10 +155,37 @@ def test_astype_float(
         assert_type(s.astype("float64[pyarrow]"), "pd.Index[float]")
         assert_type(s.astype("double[pyarrow]"), "pd.Index[float]")
 
-    # if TYPE_CHECKING_INVALID_USAGE:
-    #     # numpy float16
-    #     s.astype(np.half)
-    #     s.astype("half")
-    #     s.astype("float16")
-    #     s.astype("e")
-    #     s.astype("f2")
+
+def test_new_astype_float16() -> None:
+    """Test that a series cannot be built or cast to a float16 type."""
+    s = pd.Index([1, 2, 3])
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(s.astype(np.half), Never)
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(s.astype("half"), Never)
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(s.astype("float16"), Never)
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(s.astype("e"), Never)
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(s.astype("f2"), Never)
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(pd.Index([1.0], dtype=np.half), Never)
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(pd.Index([1.0], dtype="half"), Never)
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(pd.Index([1.0], dtype="float16"), Never)
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(pd.Index([1.0], dtype="e"), Never)
+
+    if TYPE_CHECKING_INVALID_USAGE:
+        assert_type(pd.Index([1.0], dtype="f2"), Never)