REF: _try_cast; go through fastpath more often

pandas/core/construction.py

@@ -38,9 +38,9 @@
     construct_1d_object_array_from_listlike,
     maybe_cast_to_datetime,
     maybe_cast_to_integer_array,
-    maybe_castable,
     maybe_convert_platform,
     maybe_upcast,
+    sanitize_to_nanoseconds,
 )
 from pandas.core.dtypes.common import (
     is_datetime64_ns_dtype,
@@ -656,33 +656,53 @@ def _try_cast(
     -------
     np.ndarray or ExtensionArray
     """
+    is_ndarray = isinstance(arr, np.ndarray)
+
     # perf shortcut as this is the most common case
+    # Item "List[Any]" of "Union[List[Any], ndarray]" has no attribute "dtype"
     if (
-        isinstance(arr, np.ndarray)
-        and maybe_castable(arr.dtype)
+        is_ndarray
+        and arr.dtype != object  # type: ignore[union-attr]
         and not copy
         and dtype is None
     ):
-        return arr
+        # Argument 1 to "sanitize_to_nanoseconds" has incompatible type
+        # "Union[List[Any], ndarray]"; expected "ndarray"
+        return sanitize_to_nanoseconds(arr)  # type: ignore[arg-type]
 
-    if isinstance(dtype, ExtensionDtype) and not isinstance(dtype, DatetimeTZDtype):
+    if isinstance(dtype, ExtensionDtype):
         # create an extension array from its dtype
         # DatetimeTZ case needs to go through maybe_cast_to_datetime but
         # SparseDtype does not
+        if isinstance(dtype, DatetimeTZDtype):
+            # We can't go through _from_sequence because it handles dt64naive
+            #  data differently; _from_sequence treats naive as wall times,
+            #  while maybe_cast_to_datetime treats it as UTC
+            #  see test_maybe_promote_any_numpy_dtype_with_datetimetz
+
+            # error: Incompatible return value type (got "Union[ExtensionArray,
+            # ndarray, List[Any]]", expected "Union[ExtensionArray, ndarray]")
+            return maybe_cast_to_datetime(arr, dtype)  # type: ignore[return-value]
+            # TODO: copy?
+
         array_type = dtype.construct_array_type()._from_sequence
         subarr = array_type(arr, dtype=dtype, copy=copy)
         return subarr
 
-    if is_object_dtype(dtype) and not isinstance(arr, np.ndarray):
-        subarr = construct_1d_object_array_from_listlike(arr)
-        return subarr
+    elif is_object_dtype(dtype):
+        if not is_ndarray:
+            subarr = construct_1d_object_array_from_listlike(arr)
+            return subarr
+        return ensure_wrapped_if_datetimelike(arr).astype(dtype, copy=copy)
 
-    if dtype is None and isinstance(arr, list):
+    elif dtype is None and not is_ndarray:
         # filter out cases that we _dont_ want to go through maybe_cast_to_datetime
         varr = np.array(arr, copy=False)
         if varr.dtype != object or varr.size == 0:
             return varr
-        arr = varr
+        # error: Incompatible return value type (got "Union[ExtensionArray,
+        # ndarray, List[Any]]", expected "Union[ExtensionArray, ndarray]")
+        return maybe_cast_to_datetime(varr, None)  # type: ignore[return-value]
 
     try:
         # GH#15832: Check if we are requesting a numeric dtype and

pandas/core/dtypes/cast.py

@@ -46,7 +46,6 @@
 
 from pandas.core.dtypes.common import (
     DT64NS_DTYPE,
-    POSSIBLY_CAST_DTYPES,
     TD64NS_DTYPE,
     ensure_int8,
     ensure_int16,
@@ -59,7 +58,6 @@
     is_complex,
     is_complex_dtype,
     is_datetime64_dtype,
-    is_datetime64_ns_dtype,
     is_datetime64tz_dtype,
     is_datetime_or_timedelta_dtype,
     is_dtype_equal,
@@ -74,7 +72,6 @@
     is_sparse,
     is_string_dtype,
     is_timedelta64_dtype,
-    is_timedelta64_ns_dtype,
     is_unsigned_integer_dtype,
     pandas_dtype,
 )
@@ -1480,20 +1477,6 @@ def convert_dtypes(
     return inferred_dtype
 
 
-def maybe_castable(dtype: np.dtype) -> bool:
-    # return False to force a non-fastpath
-
-    # check datetime64[ns]/timedelta64[ns] are valid
-    # otherwise try to coerce
-    kind = dtype.kind
-    if kind == "M":
-        return is_datetime64_ns_dtype(dtype)
-    elif kind == "m":
-        return is_timedelta64_ns_dtype(dtype)
-
-    return dtype.name not in POSSIBLY_CAST_DTYPES
-
-
 def maybe_infer_to_datetimelike(
     value: np.ndarray,
 ) -> np.ndarray | DatetimeArray | TimedeltaArray:

pandas/core/dtypes/common.py

@@ -58,21 +58,6 @@
     is_sequence,
 )
 
-POSSIBLY_CAST_DTYPES = {
-    np.dtype(t).name
-    for t in [
-        "O",
-        "int8",
-        "uint8",
-        "int16",
-        "uint16",
-        "int32",
-        "uint32",
-        "int64",
-        "uint64",
-    ]
-}
-
 DT64NS_DTYPE = conversion.DT64NS_DTYPE
 TD64NS_DTYPE = conversion.TD64NS_DTYPE
 INT64_DTYPE = np.dtype(np.int64)