DEPS: Update reprs with numpy NEP51 scalar repr (#54268)

* DEPS: Update reprs with numpy NEP51 scalar repr

* Just return str

Author: mroeschke

pandas/_libs/interval.pyx

@@ -492,8 +492,9 @@ cdef class Interval(IntervalMixin):
     def __repr__(self) -> str:
 
         left, right = self._repr_base()
+        disp = str if isinstance(left, np.generic) else repr
         name = type(self).__name__
-        repr_str = f"{name}({repr(left)}, {repr(right)}, closed={repr(self.closed)})"
+        repr_str = f"{name}({disp(left)}, {disp(right)}, closed={repr(self.closed)})"
         return repr_str
 
     def __str__(self) -> str:

pandas/core/arrays/masked.py

@@ -3,6 +3,7 @@
 from typing import (
     TYPE_CHECKING,
     Any,
+    Callable,
     Literal,
     overload,
 )
@@ -160,6 +161,10 @@ def _empty(cls, shape: Shape, dtype: ExtensionDtype):
             )
         return result
 
+    def _formatter(self, boxed: bool = False) -> Callable[[Any], str | None]:
+        # NEP 51: https://github.com/numpy/numpy/pull/22449
+        return str
+
     @property
     def dtype(self) -> BaseMaskedDtype:
         raise AbstractMethodError(self)

pandas/core/indexes/base.py

@@ -5250,7 +5250,8 @@ def _raise_scalar_data_error(cls, data):
         #  in order to keep mypy happy
         raise TypeError(
             f"{cls.__name__}(...) must be called with a collection of some "
-            f"kind, {repr(data)} was passed"
+            f"kind, {repr(data) if not isinstance(data, np.generic) else str(data)} "
+            "was passed"
         )
 
     def _validate_fill_value(self, value):
@@ -6974,7 +6975,7 @@ def drop(
         mask = indexer == -1
         if mask.any():
             if errors != "ignore":
-                raise KeyError(f"{list(labels[mask])} not found in axis")
+                raise KeyError(f"{labels[mask].tolist()} not found in axis")
             indexer = indexer[~mask]
         return self.delete(indexer)
 

pandas/tests/arrays/floating/test_construction.py

@@ -125,6 +125,7 @@ def test_to_array_error(values):
             "Cannot pass scalar",
             r"float\(\) argument must be a string or a (real )?number, not 'dict'",
             "could not convert string to float: 'foo'",
+            r"could not convert string to float: np\.str_\('foo'\)",
         ]
     )
     with pytest.raises((TypeError, ValueError), match=msg):

pandas/tests/arrays/sparse/test_dtype.py

@@ -197,7 +197,7 @@ def test_update_dtype(original, dtype, expected):
         (
             SparseDtype(str, "abc"),
             int,
-            re.escape("invalid literal for int() with base 10: 'abc'"),
+            r"invalid literal for int\(\) with base 10: ('abc'|np\.str_\('abc'\))",
         ),
     ],
 )