Compat for latest libraries

hypothesis-python/RELEASE.rst

@@ -0,0 +1,3 @@
+RELEASE_TYPE: patch
+
+This patch silences a false alarm from :pypi:`mypy==1.2.0 <mypy>`.

hypothesis-python/src/hypothesis/internal/compat.py

@@ -52,7 +52,7 @@ def get_args(
     # remove at Python 3.7 end-of-life
     from collections.abc import Callable as _Callable
 
-    def get_origin(tp: Any) -> typing.Optional[Any]:  # pragma: no cover
+    def get_origin(tp: Any) -> typing.Optional[Any]:  # pragma: no cover  # type: ignore
         """Get the unsubscripted version of a type.
         This supports generic types, Callable, Tuple, Union, Literal, Final and ClassVar.
         Return None for unsupported types. Examples::

hypothesis-python/tests/pandas/test_indexes.py

@@ -8,6 +8,8 @@
 # v. 2.0. If a copy of the MPL was not distributed with this file, You can
 # obtain one at https://mozilla.org/MPL/2.0/.
 
+import warnings
+
 import numpy as np
 import pandas
 import pytest
@@ -82,7 +84,7 @@ def test_generate_arbitrary_indices(data):
         st.one_of(
             npst.boolean_dtypes(),
             npst.integer_dtypes(endianness="="),
-            npst.floating_dtypes(endianness="="),
+            npst.floating_dtypes(endianness="=", sizes=(32, 64)),
             npst.complex_number_dtypes(endianness="="),
             npst.datetime64_dtypes(endianness="="),
             npst.timedelta64_dtypes(endianness="="),
@@ -94,23 +96,30 @@ def test_generate_arbitrary_indices(data):
     converted_dtype = pandas.Index([], dtype=dtype).dtype
 
     try:
-        inferred_dtype = pandas.Index([data.draw(npst.from_dtype(dtype))]).dtype
-
-        if pass_elements:
-            elements = npst.from_dtype(dtype)
-            dtype = None
-        else:
-            elements = None
-
-        index = data.draw(
-            pdst.indexes(
-                elements=elements,
-                dtype=dtype,
-                min_size=min_size,
-                max_size=max_size,
-                unique=unique,
+        elem = data.draw(npst.from_dtype(dtype))
+
+        with warnings.catch_warnings():
+            warnings.simplefilter("error")
+            if np.dtype.kind == "c":
+                warnings.simplefilter("ignore", np.ComplexWarning)
+
+            inferred_dtype = pandas.Index([elem]).dtype
+
+            if pass_elements:
+                elements = npst.from_dtype(dtype)
+                dtype = None
+            else:
+                elements = None
+
+            index = data.draw(
+                pdst.indexes(
+                    elements=elements,
+                    dtype=dtype,
+                    min_size=min_size,
+                    max_size=max_size,
+                    unique=unique,
+                )
             )
-        )
 
     except Exception as e:
         if type(e).__name__ == "OutOfBoundsDatetime":