REF: call pandas_dtype up-front in Index.__new__

pandas/core/indexes/base.py

@@ -48,6 +48,7 @@
     is_signed_integer_dtype,
     is_timedelta64_dtype,
     is_unsigned_integer_dtype,
+    pandas_dtype,
 )
 from pandas.core.dtypes.concat import concat_compat
 from pandas.core.dtypes.generic import (
@@ -68,6 +69,7 @@
 from pandas.core.accessor import CachedAccessor
 import pandas.core.algorithms as algos
 from pandas.core.arrays import ExtensionArray
+from pandas.core.arrays.datetimes import tz_to_dtype, validate_tz_from_dtype
 from pandas.core.base import IndexOpsMixin, PandasObject
 import pandas.core.common as com
 from pandas.core.indexers import deprecate_ndim_indexing
@@ -292,54 +294,59 @@ def __new__(
 
         name = maybe_extract_name(name, data, cls)
 
+        if dtype is not None:
+            dtype = pandas_dtype(dtype)
+        if "tz" in kwargs:
+            tz = kwargs.pop("tz")
+            validate_tz_from_dtype(dtype, tz)
+            dtype = tz_to_dtype(tz)
+
         if isinstance(data, ABCPandasArray):
             # ensure users don't accidentally put a PandasArray in an index.
             data = data.to_numpy()
 
+        data_dtype = getattr(data, "dtype", None)
+
         # range
         if isinstance(data, RangeIndex):
             return RangeIndex(start=data, copy=copy, dtype=dtype, name=name)
         elif isinstance(data, range):
             return RangeIndex.from_range(data, dtype=dtype, name=name)
 
         # categorical
-        elif is_categorical_dtype(data) or is_categorical_dtype(dtype):
+        elif is_categorical_dtype(data_dtype) or is_categorical_dtype(dtype):
             # Delay import for perf. https://github.com/pandas-dev/pandas/pull/31423
             from pandas.core.indexes.category import CategoricalIndex
 
             return _maybe_asobject(dtype, CategoricalIndex, data, copy, name, **kwargs)
 
         # interval
-        elif is_interval_dtype(data) or is_interval_dtype(dtype):
+        elif is_interval_dtype(data_dtype) or is_interval_dtype(dtype):
             # Delay import for perf. https://github.com/pandas-dev/pandas/pull/31423
             from pandas.core.indexes.interval import IntervalIndex
 
             return _maybe_asobject(dtype, IntervalIndex, data, copy, name, **kwargs)
 
-        elif (
-            is_datetime64_any_dtype(data)
-            or is_datetime64_any_dtype(dtype)
-            or "tz" in kwargs
-        ):
+        elif is_datetime64_any_dtype(data_dtype) or is_datetime64_any_dtype(dtype):
             # Delay import for perf. https://github.com/pandas-dev/pandas/pull/31423
             from pandas import DatetimeIndex
 
             return _maybe_asobject(dtype, DatetimeIndex, data, copy, name, **kwargs)
 
-        elif is_timedelta64_dtype(data) or is_timedelta64_dtype(dtype):
+        elif is_timedelta64_dtype(data_dtype) or is_timedelta64_dtype(dtype):
             # Delay import for perf. https://github.com/pandas-dev/pandas/pull/31423
             from pandas import TimedeltaIndex
 
             return _maybe_asobject(dtype, TimedeltaIndex, data, copy, name, **kwargs)
 
-        elif is_period_dtype(data) or is_period_dtype(dtype):
+        elif is_period_dtype(data_dtype) or is_period_dtype(dtype):
             # Delay import for perf. https://github.com/pandas-dev/pandas/pull/31423
             from pandas import PeriodIndex
 
             return _maybe_asobject(dtype, PeriodIndex, data, copy, name, **kwargs)
 
         # extension dtype
-        elif is_extension_array_dtype(data) or is_extension_array_dtype(dtype):
+        elif is_extension_array_dtype(data_dtype) or is_extension_array_dtype(dtype):
             if not (dtype is None or is_object_dtype(dtype)):
                 # coerce to the provided dtype
                 ea_cls = dtype.construct_array_type()

pandas/core/internals/blocks.py

@@ -8,7 +8,7 @@
 
 from pandas._libs import NaT, algos as libalgos, lib, writers
 import pandas._libs.internals as libinternals
-from pandas._libs.tslibs import Timedelta, conversion
+from pandas._libs.tslibs import conversion
 from pandas._libs.tslibs.timezones import tz_compare
 from pandas._typing import ArrayLike
 from pandas.util._validators import validate_bool_kwarg

pandas/tests/indexes/ranges/test_constructors.py

@@ -43,7 +43,7 @@ def test_constructor_invalid_args(self):
             r"kind, 0 was passed"
         )
         with pytest.raises(TypeError, match=msg):
-            Index(0, 1000)
+            Index(0)
 
     @pytest.mark.parametrize(
         "args",