BUG: Fix for _validate_setitem_value fails to raise for PandasArray

doc/source/whatsnew/v3.0.0.rst

@@ -674,6 +674,7 @@ Sparse
 
 ExtensionArray
 ^^^^^^^^^^^^^^
+- Bug in :class:`NumpyExtensionArray` where error was not raised if value cannot be inserted without changing the dtype (:issue:`51044`)
 - Bug in :meth:`.arrays.ArrowExtensionArray.__setitem__` which caused wrong behavior when using an integer array with repeated values as a key (:issue:`58530`)
 - Bug in :meth:`api.types.is_datetime64_any_dtype` where a custom :class:`ExtensionDtype` would return ``False`` for array-likes (:issue:`57055`)
 - Bug in comparison between object with :class:`ArrowDtype` and incompatible-dtyped (e.g. string vs bool) incorrectly raising instead of returning all-``False`` (for ``==``) or all-``True`` (for ``!=``) (:issue:`59505`)

pandas/core/arrays/numpy_.py

@@ -17,6 +17,7 @@
 from pandas.core.dtypes.dtypes import NumpyEADtype
 from pandas.core.dtypes.missing import isna
 
+import pandas as pd
 from pandas.core import (
     arraylike,
     missing,
@@ -236,6 +237,55 @@ def _values_for_factorize(self) -> tuple[np.ndarray, float | None]:
             fv = np.nan
         return self._ndarray, fv
 
+    def _validate_setitem_value(self, value):
+        """
+        Check if we have a scalar that we can cast losslessly.
+
+        Raises
+        ------
+        TypeError
+        """
+
+        if type(value) == self.dtype.type:
+            return value
+
+        if (
+            isinstance(value, NumpyExtensionArray)
+            or isinstance(value, np.ndarray)
+            or isinstance(value, pd.Series)
+        ) and value.dtype == self.dtype:
+            return value
+
+        if (
+            isinstance(value, list)
+            or isinstance(value, NumpyExtensionArray)
+            or isinstance(value, np.ndarray)
+            or isinstance(value, pd.Series)
+        ):
+            try:
+                _ = pd.array(value, dtype=self.dtype)
+                return value
+            except ValueError:
+                print("Caught the error")
+
+        if (
+            (
+                (lib.is_integer(value) or lib.is_float(value))
+                and self.dtype.kind in "iuf"
+            )
+            or (isinstance(value, str) and self.dtype.kind in "US")
+            or (self.dtype.kind == "O")
+        ) and not isna(value):
+            if self.dtype.type(value) == value:
+                return value
+
+        if isna(value):
+            return value
+
+        raise TypeError(
+            f"Invalid value '{value!s}' with type {type(value)} for dtype {self.dtype}"
+        )
+
     # Base EA class (and all other EA classes) don't have limit_area keyword
     # This can be removed here as well when the interpolate ffill/bfill method
     # deprecation is enforced

pandas/tests/arrays/numpy_/test_numpy.py

@@ -3,6 +3,8 @@
 the interface tests.
 """
 
+from datetime import datetime
+
 import numpy as np
 import pytest
 
@@ -195,6 +197,93 @@ def test_validate_reduction_keyword_args():
         arr.all(keepdims=True)
 
 
+@pytest.mark.parametrize(
+    "value, expectedError",
+    [
+        (True, True),
+        (5, False),
+        (5.0, False),
+        (5.5, True),
+        (1 + 2j, True),
+        ("t", True),
+        (datetime.now(), True),
+    ],
+)
+def test_int_arr_validate_setitem_value(value, expectedError):
+    arr = pd.Series(range(5), dtype="int").array
+    if expectedError:
+        with pytest.raises(TypeError):
+            arr._validate_setitem_value(value)
+    else:
+        arr[0] = value
+        assert arr[0] == value
+
+
+@pytest.mark.parametrize(
+    "value, expectedError",
+    [
+        (True, True),
+        (5, False),
+        (5.0, False),
+        (5.5, True),
+        (1 + 2j, True),
+        ("t", True),
+        (datetime.now(), True),
+    ],
+)
+def test_uint_arr_validate_setitem_value(value, expectedError):
+    arr = pd.Series(range(5), dtype="uint").array
+    if expectedError:
+        with pytest.raises(TypeError):
+            arr._validate_setitem_value(value)
+    else:
+        arr[0] = value
+        assert arr[0] == value
+
+
+@pytest.mark.parametrize(
+    "value, expectedError",
+    [
+        (True, True),
+        (5, False),
+        (5.0, False),
+        (5.5, False),
+        (1 + 2j, True),
+        ("t", True),
+        (datetime.now(), True),
+    ],
+)
+def test_float_arr_validate_setitem_value(value, expectedError):
+    arr = pd.Series(range(5), dtype="float").array
+    if expectedError:
+        with pytest.raises(TypeError):
+            arr._validate_setitem_value(value)
+    else:
+        arr[0] = value
+        assert arr[0] == value
+
+
+@pytest.mark.parametrize(
+    "value, expectedError",
+    [
+        (True, True),
+        (5, True),
+        (5.0, True),
+        (5.5, True),
+        ("t", False),
+        (datetime.now(), True),
+    ],
+)
+def test_str_arr_validate_setitem_value(value, expectedError):
+    arr = NumpyExtensionArray(np.array(["foo", "bar", "test"], dtype="str"))
+    if expectedError:
+        with pytest.raises(TypeError):
+            arr._validate_setitem_value(value)
+    else:
+        arr[0] = value
+        assert arr[0] == str(value)
+
+
 def test_np_max_nested_tuples():
     # case where checking in ufunc.nout works while checking for tuples
     #  does not
@@ -275,12 +364,15 @@ def test_setitem_object_typecode(dtype):
 def test_setitem_no_coercion():
     # https://github.com/pandas-dev/pandas/issues/28150
     arr = NumpyExtensionArray(np.array([1, 2, 3]))
-    with pytest.raises(ValueError, match="int"):
+    with pytest.raises(TypeError):
         arr[0] = "a"
 
     # With a value that we do coerce, check that we coerce the value
     #  and not the underlying array.
-    arr[0] = 2.5
+    with pytest.raises(TypeError):
+        arr[0] = 2.5
+
+    arr[0] = 9
     assert isinstance(arr[0], (int, np.integer)), type(arr[0])
 
 
@@ -296,7 +388,10 @@ def test_setitem_preserves_views():
     assert view2[0] == 9
     assert view3[0] == 9
 
-    arr[-1] = 2.5
+    with pytest.raises(TypeError):
+        arr[-1] = 2.5
+
+    arr[-1] = 4
     view1[-1] = 5
     assert arr[-1] == 5