test

Author: andrewgsavage

pandas/_libs/lib.pyx

@@ -1695,7 +1695,6 @@ def infer_dtype(value: object, skipna: bool = True) -> str:
         if is_interval_array(values):
             return "interval"
 
-    print("infer_dtype")
     reg_dtype = _registry.match_scalar(val)
     if reg_dtype:
         return str(reg_dtype)

pandas/core/dtypes/base.py

@@ -444,12 +444,17 @@ def _can_fast_transpose(self) -> bool:
         """
         return False
 
-    def is_unambiguous_scalar(self):
+    @classmethod
+    def is_unambiguous_scalar(cls, scalar):
         return False
 
     @classmethod
     def construct_from_scalar(cls, scalar):
         return cls()
+    
+    @property
+    def is_external_dtype(self) -> bool:
+        return not self.__module__.split(".")[0] == "pandas"
 
 
 class StorageExtensionDtype(ExtensionDtype):

pandas/core/dtypes/cast.py

@@ -918,6 +918,8 @@ def infer_dtype_from_array(arr) -> tuple[DtypeObj, ArrayLike]:
     inferred = lib.infer_dtype(arr, skipna=False)
     if inferred in ["string", "bytes", "mixed", "mixed-integer"]:
         return (np.dtype(np.object_), arr)
+    elif inferred in ["empty", "integer", "floating", "integer-na", "mixed-integer-float", "datetime", "period", "timedelta", "time", "date"]:
+        pass
     else:
         arr_dtype = pandas_dtype_func(inferred)
         if isinstance(arr_dtype, ExtensionDtype):

pandas/core/series.py

@@ -502,7 +502,10 @@ def __init__(
                 data = data.copy()
         else:
             if dtype is None:
-                dtype = infer_dtype_from(data)[0]
+                inferred_dtype = infer_dtype_from(data)[0]
+                if isinstance(inferred_dtype, ExtensionDtype) and inferred_dtype.is_external_dtype:
+                    dtype = inferred_dtype
+                    # import pdb; pdb.set_trace()
             data = sanitize_array(data, index, dtype, copy)
             data = SingleBlockManager.from_array(data, index, refs=refs)
 

pandas/tests/dtypes/test_inference.py

@@ -81,6 +81,13 @@
 def coerce(request):
     return request.param
 
+class MockScalar:
+    pass
+
+class MockDtype(pd.api.extensions.ExtensionDtype):
+    
+
+
 
 class MockNumpyLikeArray:
     """