REF: _try_cast; go through fastpath more often

pandas/core/construction.py

@@ -39,9 +39,9 @@
  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,
@@ -664,30 +664,45 @@ def _try_cast(
  # perf shortcut as this is the most common case
  if (
  isinstance(arr, np.ndarray)
- and maybe_castable(arr.dtype)
+ and arr.dtype != object
  and not copy
  and dtype is None
  ):
- return arr
+ return sanitize_to_nanoseconds(arr)
 
- 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 isinstance(arr, np.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 isinstance(arr, list):
  # 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

@@ -45,7 +45,6 @@
 
 from pandas.core.dtypes.common import (
  DT64NS_DTYPE,
- POSSIBLY_CAST_DTYPES,
  TD64NS_DTYPE,
  ensure_int8,
  ensure_int16,
@@ -58,7 +57,6 @@
  is_complex,
  is_complex_dtype,
  is_datetime64_dtype,
- is_datetime64_ns_dtype,
  is_datetime64tz_dtype,
  is_datetime_or_timedelta_dtype,
  is_dtype_equal,
@@ -73,7 +71,6 @@
  is_sparse,
  is_string_dtype,
  is_timedelta64_dtype,
- is_timedelta64_ns_dtype,
  is_unsigned_integer_dtype,
  pandas_dtype,
 )
@@ -1466,20 +1463,6 @@ 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)