Fixup typing of dtypes

spec/API_specification/dataframe_api/typing.py

@@ -17,41 +17,6 @@
 if TYPE_CHECKING:
     from collections.abc import Sequence
 
-    from .dtypes import (
-        Bool,
-        Date,
-        Datetime,
-        Duration,
-        Float32,
-        Float64,
-        Int8,
-        Int16,
-        Int32,
-        Int64,
-        String,
-        UInt8,
-        UInt16,
-        UInt32,
-        UInt64,
-    )
-
-    DType = Union[
-        Bool,
-        Float64,
-        Float32,
-        Int64,
-        Int32,
-        Int16,
-        Int8,
-        UInt64,
-        UInt32,
-        UInt16,
-        UInt8,
-        String,
-        Date,
-        Datetime,
-        Duration,
-    ]
 
 # Type alias: Mypy needs Any, but for readability we need to make clear this
 # is a Python scalar (i.e., an instance of `bool`, `int`, `float`, `str`, etc.)
@@ -104,7 +69,14 @@ class Datetime:
         def __init__(  # noqa: ANN204
             self,
             time_unit: Literal["ms", "us"],
-            time_zone: str | None,
+            time_zone: str | None = None,
+        ):
+            ...
+
+    class Duration:
+        def __init__(  # noqa: ANN204
+            self,
+            time_unit: Literal["ms", "us"],
         ):
             ...
 
@@ -155,6 +127,25 @@ def date(self, year: int, month: int, day: int) -> Scalar:
         ...
 
 
+DType = Union[
+    Namespace.Bool,
+    Namespace.Float64,
+    Namespace.Float32,
+    Namespace.Int64,
+    Namespace.Int32,
+    Namespace.Int16,
+    Namespace.Int8,
+    Namespace.UInt64,
+    Namespace.UInt32,
+    Namespace.UInt16,
+    Namespace.UInt8,
+    Namespace.String,
+    Namespace.Date,
+    Namespace.Datetime,
+    Namespace.Duration,
+]
+
+
 class SupportsDataFrameAPI(Protocol):
     def __dataframe_consortium_standard__(
         self,

spec/API_specification/examples/04_datatypes.py

@@ -0,0 +1,27 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Any, Callable
+
+if TYPE_CHECKING:
+    from dataframe_api.typing import SupportsDataFrameAPI
+
+some_array_function: Callable[[Any], Any]
+
+
+def main(df_raw: SupportsDataFrameAPI) -> SupportsDataFrameAPI:
+    df = df_raw.__dataframe_consortium_standard__(api_version="2023-11.beta").persist()
+    namespace = df.__dataframe_namespace__()
+    df = df.select(
+        *[
+            col_name
+            for col_name in df.column_names
+            if isinstance(df.col(col_name).dtype, namespace.Int64)
+        ],
+    )
+    arr = df.to_array(namespace.Int64())
+    arr = some_array_function(arr)
+    df = namespace.dataframe_from_2d_array(
+        arr,
+        schema={"a": df.col("a").dtype, "b": namespace.Float64()},
+    )
+    return df.dataframe