diff --git a/spec/API_specification/dataframe_api/__init__.py b/spec/API_specification/dataframe_api/__init__.py
index 1e7d57b4..0c34c2f3 100644
--- a/spec/API_specification/dataframe_api/__init__.py
+++ b/spec/API_specification/dataframe_api/__init__.py
@@ -3,12 +3,15 @@
 """
 from __future__ import annotations
 
-from typing import Mapping, Sequence, Any
+from typing import Mapping, Sequence, Any, TYPE_CHECKING
 
 from .column_object import *
 from .dataframe_object import DataFrame
 from .groupby_object import *
-from ._types import DType
+from .dtypes import *
+
+if TYPE_CHECKING:
+    from ._types import DType
 
 __all__ = [
     "__dataframe_api_version__",
@@ -63,7 +66,7 @@ def concat(dataframes: Sequence[DataFrame]) -> DataFrame:
     """
     ...
 
-def column_from_sequence(sequence: Sequence[Any], *, dtype: Any, name: str = '', api_version: str | None = None) -> Column[Any]:
+def column_from_sequence(sequence: Sequence[Any], *, dtype: DType, name: str = '', api_version: str | None = None) -> Column:
     """
     Construct Column from sequence of elements.
 
@@ -91,7 +94,7 @@ def column_from_sequence(sequence: Sequence[Any], *, dtype: Any, name: str = '',
     """
     ...
 
-def dataframe_from_dict(data: Mapping[str, Column[Any]], *, api_version: str | None = None) -> DataFrame:
+def dataframe_from_dict(data: Mapping[str, Column], *, api_version: str | None = None) -> DataFrame:
     """
     Construct DataFrame from map of column names to Columns.
 
@@ -123,7 +126,7 @@ def dataframe_from_dict(data: Mapping[str, Column[Any]], *, api_version: str | N
     ...
 
 
-def column_from_1d_array(array: Any, *, dtype: Any, name: str = '', api_version: str | None = None) -> Column[Any]:
+def column_from_1d_array(array: Any, *, dtype: DType, name: str = '', api_version: str | None = None) -> Column:
     """
     Construct Column from 1D array.
 
@@ -232,51 +235,13 @@ def is_null(value: object, /) -> bool:
 
     """
 
-##########
-# Dtypes #
-##########
-
-class Int64:
-    """Integer type with 64 bits of precision."""
-
-class Int32:
-    """Integer type with 32 bits of precision."""
-
-class Int16:
-    """Integer type with 16 bits of precision."""
-
-class Int8:
-    """Integer type with 8 bits of precision."""
-
-class UInt64:
-    """Unsigned integer type with 64 bits of precision."""
-
-class UInt32:
-    """Unsigned integer type with 32 bits of precision."""
-
-class UInt16:
-    """Unsigned integer type with 16 bits of precision."""
-
-class UInt8:
-    """Unsigned integer type with 8 bits of precision."""
-
-class Float64:
-    """Floating point type with 64 bits of precision."""
-
-class Float32:
-    """Floating point type with 32 bits of precision."""
-
-class Bool:
-    """Boolean type with 8 bits of precision."""
-
-
-def is_dtype(dtype: Any, kind: str | tuple[str, ...]) -> bool:
+def is_dtype(dtype: DType, kind: str | tuple[str, ...]) -> bool:
     """
     Returns a boolean indicating whether a provided dtype is of a specified data type “kind”.
 
     Parameters
     ----------
-        dtype: Any
+        dtype: DType
             The input dtype.
         kind: str
             data type kind.
diff --git a/spec/API_specification/dataframe_api/_types.py b/spec/API_specification/dataframe_api/_types.py
index 2b6d7d08..2b43e115 100644
--- a/spec/API_specification/dataframe_api/_types.py
+++ b/spec/API_specification/dataframe_api/_types.py
@@ -1,8 +1,5 @@
 """
 Types for type annotations used in the dataframe API standard.
-
-The type variables should be replaced with the actual types for a given
-library, e.g., for Pandas TypeVar('DataFrame') would be replaced with pd.DataFrame.
 """
 from __future__ import annotations
 
@@ -14,12 +11,28 @@
     Optional,
     Sequence,
     Tuple,
-    TypeVar,
     Union,
-    Protocol,
+    TYPE_CHECKING,
 )
 from enum import Enum
 
+if TYPE_CHECKING:
+    from .dtypes import (
+        Bool,
+        Float64,
+        Float32,
+        Int64,
+        Int32,
+        Int16,
+        Int8,
+        UInt64,
+        UInt32,
+        UInt16,
+        UInt8,
+    )
+
+    DType = Union[Bool, Float64, Float32, Int64, Int32, Int16, Int8, UInt64, UInt32, UInt16, UInt8]
+
 # 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.)
 Scalar = Any
@@ -27,26 +40,6 @@
 # It is not valid as a type.
 NullType = Any
 
-array = TypeVar("array")
-device = TypeVar("device")
-DType = TypeVar("DType")
-SupportsDLPack = TypeVar("SupportsDLPack")
-SupportsBufferProtocol = TypeVar("SupportsBufferProtocol")
-PyCapsule = TypeVar("PyCapsule")
-# ellipsis cannot actually be imported from anywhere, so include a dummy here
-# to keep pyflakes happy. https://github.com/python/typeshed/issues/3556
-ellipsis = TypeVar("ellipsis")
-
-_T_co = TypeVar("_T_co", covariant=True)
-
-
-class NestedSequence(Protocol[_T_co]):
-    def __getitem__(self, key: int, /) -> Union[_T_co, NestedSequence[_T_co]]:
-        ...
-
-    def __len__(self, /) -> int:
-        ...
-
 
 __all__ = [
     "Any",
diff --git a/spec/API_specification/dataframe_api/column_object.py b/spec/API_specification/dataframe_api/column_object.py
index 960462ff..7b0f552a 100644
--- a/spec/API_specification/dataframe_api/column_object.py
+++ b/spec/API_specification/dataframe_api/column_object.py
@@ -2,17 +2,14 @@
 
 from typing import Any,NoReturn, TYPE_CHECKING, Literal, Generic
 
-from ._types import DType
-
 if TYPE_CHECKING:
-    from . import Bool
-    from ._types import NullType, Scalar
+    from ._types import NullType, Scalar, DType
 
 
 __all__ = ['Column']
 
 
-class Column(Generic[DType]):
+class Column:
     """
     Column object
 
@@ -73,21 +70,21 @@ def dtype(self) -> Any:
         Return data type of column.
         """
 
-    def get_rows(self: Column[DType], indices: Column[Any]) -> Column[DType]:
+    def get_rows(self: Column, indices: Column) -> Column:
         """
         Select a subset of rows, similar to `ndarray.take`.
 
         Parameters
         ----------
-        indices : Column[int]
+        indices : Column
             Positions of rows to select.
         """
         ...
 
 
     def slice_rows(
-        self: Column[DType], start: int | None, stop: int | None, step: int | None
-    ) -> Column[DType]:
+        self: Column, start: int | None, stop: int | None, step: int | None
+    ) -> Column:
         """
         Select a subset of rows corresponding to a slice.
 
@@ -104,13 +101,13 @@ def slice_rows(
         ...
 
 
-    def filter(self: Column[DType], mask: Column[Bool]) -> Column[DType]:
+    def filter(self: Column, mask: Column) -> Column:
         """
         Select a subset of rows corresponding to a mask.
 
         Parameters
         ----------
-        mask : Column[bool]
+        mask : Column
 
         Returns
         -------
@@ -146,7 +143,7 @@ def sort(
         *,
         ascending: bool = True,
         nulls_position: Literal['first', 'last'] = 'last',
-    ) -> Column[DType]:
+    ) -> Column:
         """
         Sort column.
 
@@ -175,7 +172,7 @@ def sorted_indices(
         *,
         ascending: bool = True,
         nulls_position: Literal['first', 'last'] = 'last',
-    ) -> Column[Any]:
+    ) -> Column:
         """
         Return row numbers which would sort column.
 
@@ -194,11 +191,11 @@ def sorted_indices(
 
         Returns
         -------
-        Column[int]
+        Column
         """
         ...
 
-    def __eq__(self, other: Column[Any] | Scalar) -> Column[Bool]:  # type: ignore[override]
+    def __eq__(self, other: Column | Scalar) -> Column:  # type: ignore[override]
         """
         Compare for equality.
 
@@ -216,7 +213,7 @@ def __eq__(self, other: Column[Any] | Scalar) -> Column[Bool]:  # type: ignore[o
         Column
         """
 
-    def __ne__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:  # type: ignore[override]
+    def __ne__(self: Column, other: Column | Scalar) -> Column:  # type: ignore[override]
         """
         Compare for non-equality.
 
@@ -234,7 +231,7 @@ def __ne__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:
         Column
         """
 
-    def __ge__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:
+    def __ge__(self: Column, other: Column | Scalar) -> Column:
         """
         Compare for "greater than or equal to" `other`.
 
@@ -250,7 +247,7 @@ def __ge__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:
         Column
         """
 
-    def __gt__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:
+    def __gt__(self: Column, other: Column | Scalar) -> Column:
         """
         Compare for "greater than" `other`.
 
@@ -266,7 +263,7 @@ def __gt__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:
         Column
         """
 
-    def __le__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:
+    def __le__(self: Column, other: Column | Scalar) -> Column:
         """
         Compare for "less than or equal to" `other`.
 
@@ -282,7 +279,7 @@ def __le__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:
         Column
         """
 
-    def __lt__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:
+    def __lt__(self: Column, other: Column | Scalar) -> Column:
         """
         Compare for "less than" `other`.
 
@@ -298,7 +295,7 @@ def __lt__(self: Column[DType], other: Column[DType] | Scalar) -> Column[Bool]:
         Column
         """
 
-    def __and__(self: Column[Bool], other: Column[Bool] | bool) -> Column[Bool]:
+    def __and__(self: Column, other: Column | bool) -> Column:
         """
         Apply logical 'and' to `other` Column (or scalar) and this Column.
 
@@ -306,7 +303,7 @@ def __and__(self: Column[Bool], other: Column[Bool] | bool) -> Column[Bool]:
 
         Parameters
         ----------
-        other : Column[bool] or bool
+        other : Column or bool
             If Column, must have same length.
 
         Returns
@@ -319,7 +316,7 @@ def __and__(self: Column[Bool], other: Column[Bool] | bool) -> Column[Bool]:
             If `self` or `other` is not boolean.
         """
 
-    def __or__(self: Column[Bool], other: Column[Bool] | bool) -> Column[Bool]:
+    def __or__(self: Column, other: Column | bool) -> Column:
         """
         Apply logical 'or' to `other` Column (or scalar) and this column.
 
@@ -327,12 +324,12 @@ def __or__(self: Column[Bool], other: Column[Bool] | bool) -> Column[Bool]:
 
         Parameters
         ----------
-        other : Column[bool] or Scalar
+        other : Column or Scalar
             If Column, must have same length.
 
         Returns
         -------
-        Column[bool]
+        Column
 
         Raises
         ------
@@ -340,7 +337,7 @@ def __or__(self: Column[Bool], other: Column[Bool] | bool) -> Column[Bool]:
             If `self` or `other` is not boolean.
         """
 
-    def __add__(self: Column[Any], other: Column[Any] | Scalar) -> Column[Any]:
+    def __add__(self: Column, other: Column | Scalar) -> Column:
         """
         Add `other` column or scalar to this column.
 
@@ -356,7 +353,7 @@ def __add__(self: Column[Any], other: Column[Any] | Scalar) -> Column[Any]:
         Column
         """
 
-    def __sub__(self: Column[Any], other: Column[Any] | Scalar) -> Column[Any]:
+    def __sub__(self: Column, other: Column | Scalar) -> Column:
         """
         Subtract `other` column or scalar from this column.
 
@@ -372,7 +369,7 @@ def __sub__(self: Column[Any], other: Column[Any] | Scalar) -> Column[Any]:
         Column
         """
 
-    def __mul__(self, other: Column[Any] | Scalar) -> Column[Any]:
+    def __mul__(self, other: Column | Scalar) -> Column:
         """
         Multiply `other` column or scalar with this column.
 
@@ -388,7 +385,7 @@ def __mul__(self, other: Column[Any] | Scalar) -> Column[Any]:
         Column
         """
 
-    def __truediv__(self, other: Column[Any] | Scalar) -> Column[Any]:
+    def __truediv__(self, other: Column | Scalar) -> Column:
         """
         Divide this column by `other` column or scalar. True division, returns floats.
 
@@ -404,7 +401,7 @@ def __truediv__(self, other: Column[Any] | Scalar) -> Column[Any]:
         Column
         """
 
-    def __floordiv__(self, other: Column[Any] | Scalar) -> Column[Any]:
+    def __floordiv__(self, other: Column | Scalar) -> Column:
         """
         Floor-divide `other` column or scalar to this column.
 
@@ -420,7 +417,7 @@ def __floordiv__(self, other: Column[Any] | Scalar) -> Column[Any]:
         Column
         """
 
-    def __pow__(self, other: Column[Any] | Scalar) -> Column[Any]:
+    def __pow__(self, other: Column | Scalar) -> Column:
         """
         Raise this column to the power of `other`.
 
@@ -440,7 +437,7 @@ def __pow__(self, other: Column[Any] | Scalar) -> Column[Any]:
         Column
         """
 
-    def __mod__(self, other: Column[Any] | Scalar) -> Column[Any]:
+    def __mod__(self, other: Column | Scalar) -> Column:
         """
         Returns modulus of this column by `other` (`%` operator).
 
@@ -456,7 +453,7 @@ def __mod__(self, other: Column[Any] | Scalar) -> Column[Any]:
         Column
         """
 
-    def __divmod__(self, other: Column[Any] | Scalar) -> tuple[Column[Any], Column[Any]]:
+    def __divmod__(self, other: Column | Scalar) -> tuple[Column, Column]:
         """
         Return quotient and remainder of integer division. See `divmod` builtin function.
 
@@ -472,7 +469,7 @@ def __divmod__(self, other: Column[Any] | Scalar) -> tuple[Column[Any], Column[A
         Column
         """
 
-    def __invert__(self: Column[Bool]) -> Column[Bool]:
+    def __invert__(self: Column) -> Column:
         """
         Invert truthiness of (boolean) elements.
 
@@ -482,7 +479,7 @@ def __invert__(self: Column[Bool]) -> Column[Bool]:
             If any of the Column's columns is not boolean.
         """
 
-    def any(self: Column[Bool], *, skip_nulls: bool = True) -> bool | NullType:
+    def any(self: Column, *, skip_nulls: bool = True) -> bool | NullType:
         """
         Reduction returns a bool.
 
@@ -492,7 +489,7 @@ def any(self: Column[Bool], *, skip_nulls: bool = True) -> bool | NullType:
             If column is not boolean.
         """
 
-    def all(self: Column[Bool], *, skip_nulls: bool = True) -> bool | NullType:
+    def all(self: Column, *, skip_nulls: bool = True) -> bool | NullType:
         """
         Reduction returns a bool.
 
@@ -586,33 +583,33 @@ def var(self, *, correction: int | float = 1, skip_nulls: bool = True) -> Scalar
             Whether to skip null values.
         """
 
-    def cumulative_max(self: Column[DType]) -> Column[DType]:
+    def cumulative_max(self: Column) -> Column:
         """
         Reduction returns a Column. Any data type that supports comparisons
         must be supported. The returned value has the same dtype as the column.
         """
 
-    def cumulative_min(self: Column[DType]) -> Column[DType]:
+    def cumulative_min(self: Column) -> Column:
         """
         Reduction returns a Column. Any data type that supports comparisons
         must be supported. The returned value has the same dtype as the column.
         """
 
-    def cumulative_sum(self: Column[DType]) -> Column[DType]:
+    def cumulative_sum(self: Column) -> Column:
         """
         Reduction returns a Column. Must be supported for numerical and
         datetime data types. The returned value has the same dtype as the
         column.
         """
 
-    def cumulative_prod(self: Column[DType]) -> Column[DType]:
+    def cumulative_prod(self: Column) -> Column:
         """
         Reduction returns a Column. Must be supported for numerical and
         datetime data types. The returned value has the same dtype as the
         column.
         """
 
-    def is_null(self) -> Column[Bool]:
+    def is_null(self) -> Column:
         """
         Check for 'missing' or 'null' entries.
 
@@ -631,7 +628,7 @@ def is_null(self) -> Column[Bool]:
         but note that the Standard makes no guarantees about them.
         """
 
-    def is_nan(self) -> Column[Bool]:
+    def is_nan(self) -> Column:
         """
         Check for nan entries.
 
@@ -650,7 +647,7 @@ def is_nan(self) -> Column[Bool]:
         In particular, does not check for `np.timedelta64('NaT')`.
         """
 
-    def is_in(self: Column[DType], values: Column[DType]) -> Column[Bool]:
+    def is_in(self: Column, values: Column) -> Column:
         """
         Indicate whether the value at each row matches any value in `values`.
 
@@ -665,16 +662,16 @@ def is_in(self: Column[DType], values: Column[DType]) -> Column[Bool]:
 
         Returns
         -------
-        Column[bool]
+        Column
         """
 
-    def unique_indices(self, *, skip_nulls: bool = True) -> Column[Any]:
+    def unique_indices(self, *, skip_nulls: bool = True) -> Column:
         """
         Return indices corresponding to unique values in Column.
 
         Returns
         -------
-        Column[int]
+        Column
             Indices corresponding to unique values.
 
         Notes
@@ -689,7 +686,7 @@ def unique_indices(self, *, skip_nulls: bool = True) -> Column[Any]:
         """
         ...
 
-    def fill_nan(self: Column[DType], value: float | NullType, /) -> Column[DType]:
+    def fill_nan(self: Column, value: float | NullType, /) -> Column:
         """
         Fill floating point ``nan`` values with the given fill value.
 
@@ -703,7 +700,7 @@ def fill_nan(self: Column[DType], value: float | NullType, /) -> Column[DType]:
         """
         ...
 
-    def fill_null(self: Column[DType], value: Scalar, /) -> Column[DType]:
+    def fill_null(self: Column, value: Scalar, /) -> Column:
         """
         Fill null values with the given fill value.
 
@@ -716,7 +713,7 @@ def fill_null(self: Column[DType], value: Scalar, /) -> Column[DType]:
         """
         ...
 
-    def to_array_object(self, dtype: Any) -> Any:
+    def to_array_object(self, dtype: DType) -> Any:
         """
         Convert to array-API-compliant object.
 
@@ -751,7 +748,7 @@ def to_array_object(self, dtype: Any) -> Any:
         ``array-api-compat`` package to convert it to a Standard-compliant array.
         """
 
-    def rename(self, name: str) -> Column[DType]:
+    def rename(self, name: str) -> Column:
         """
         Rename column.
 
diff --git a/spec/API_specification/dataframe_api/dataframe_object.py b/spec/API_specification/dataframe_api/dataframe_object.py
index 9a727cf3..1994c674 100644
--- a/spec/API_specification/dataframe_api/dataframe_object.py
+++ b/spec/API_specification/dataframe_api/dataframe_object.py
@@ -6,8 +6,7 @@
 if TYPE_CHECKING:
     from .column_object import Column
     from .groupby_object import GroupBy
-    from . import Bool
-    from ._types import NullType, Scalar
+    from ._types import NullType, Scalar, DType
 
 
 __all__ = ["DataFrame"]
@@ -90,7 +89,7 @@ def group_by(self, keys: str | list[str], /) -> GroupBy:
         """
         ...
 
-    def get_column_by_name(self, name: str, /) -> Column[Any]:
+    def get_column_by_name(self, name: str, /) -> Column:
         """
         Select a column by name.
 
@@ -128,13 +127,13 @@ def select(self, names: Sequence[str], /) -> DataFrame:
         """
         ...
 
-    def get_rows(self, indices: Column[Any]) -> DataFrame:
+    def get_rows(self, indices: Column) -> DataFrame:
         """
         Select a subset of rows, similar to `ndarray.take`.
 
         Parameters
         ----------
-        indices : Column[int]
+        indices : Column
             Positions of rows to select.
 
         Returns
@@ -161,13 +160,13 @@ def slice_rows(
         """
         ...
 
-    def filter(self, mask: Column[Bool]) -> DataFrame:
+    def filter(self, mask: Column) -> DataFrame:
         """
         Select a subset of rows corresponding to a mask.
 
         Parameters
         ----------
-        mask : Column[bool]
+        mask : Column
 
         Returns
         -------
@@ -180,7 +179,7 @@ def filter(self, mask: Column[Bool]) -> DataFrame:
         """
         ...
 
-    def insert_column(self, column: Column[Any]) -> DataFrame:
+    def insert_column(self, column: Column) -> DataFrame:
         """
         Insert column into DataFrame at rightmost location.
 
@@ -209,7 +208,7 @@ def insert_column(self, column: Column[Any]) -> DataFrame:
         """
         ...
 
-    def update_columns(self, columns: Column[Any] | Sequence[Column[Any]], /) -> DataFrame:
+    def update_columns(self, columns: Column | Sequence[Column], /) -> DataFrame:
         """
         Update values in existing column(s) from Dataframe.
 
@@ -336,7 +335,7 @@ def sorted_indices(
         *,
         ascending: Sequence[bool] | bool = True,
         nulls_position: Literal['first', 'last'] = 'last',
-    ) -> Column[Any]:
+    ) -> Column:
         """
         Return row numbers which would sort according to given columns.
 
@@ -361,7 +360,7 @@ def sorted_indices(
 
         Returns
         -------
-        Column[int]
+        Column
     
         Raises
         ------
@@ -687,7 +686,7 @@ def all(self, *, skip_nulls: bool = True) -> DataFrame:
         """
         ...
     
-    def any_rowwise(self, *, skip_nulls: bool = True) -> Column[Bool]:
+    def any_rowwise(self, *, skip_nulls: bool = True) -> Column:
         """
         Reduction returns a Column.
 
@@ -701,7 +700,7 @@ def any_rowwise(self, *, skip_nulls: bool = True) -> Column[Bool]:
         """
         ...
 
-    def all_rowwise(self, *, skip_nulls: bool = True) -> Column[Bool]:
+    def all_rowwise(self, *, skip_nulls: bool = True) -> Column:
         """
         Reduction returns a Column.
 
@@ -821,7 +820,7 @@ def is_nan(self) -> DataFrame:
         """
         ...
 
-    def unique_indices(self, keys: str | list[str] | None = None, *, skip_nulls: bool = True) -> Column[int]:
+    def unique_indices(self, keys: str | list[str] | None = None, *, skip_nulls: bool = True) -> Column:
         """
         Return indices corresponding to unique values across selected columns.
 
@@ -833,7 +832,7 @@ def unique_indices(self, keys: str | list[str] | None = None, *, skip_nulls: boo
 
         Returns
         -------
-        Column[int]
+        Column
             Indices corresponding to unique values.
 
         Notes
@@ -897,7 +896,7 @@ def fill_null(
         """
         ...
     
-    def to_array_object(self, dtype: Any) -> Any:
+    def to_array_object(self, dtype: DType) -> Any:
         """
         Convert to array-API-compliant object.
 
diff --git a/spec/API_specification/dataframe_api/dtypes.py b/spec/API_specification/dataframe_api/dtypes.py
new file mode 100644
index 00000000..c984542f
--- /dev/null
+++ b/spec/API_specification/dataframe_api/dtypes.py
@@ -0,0 +1,33 @@
+class Int64:
+    """Integer type with 64 bits of precision."""
+
+class Int32:
+    """Integer type with 32 bits of precision."""
+
+class Int16:
+    """Integer type with 16 bits of precision."""
+
+class Int8:
+    """Integer type with 8 bits of precision."""
+
+class UInt64:
+    """Unsigned integer type with 64 bits of precision."""
+
+class UInt32:
+    """Unsigned integer type with 32 bits of precision."""
+
+class UInt16:
+    """Unsigned integer type with 16 bits of precision."""
+
+class UInt8:
+    """Unsigned integer type with 8 bits of precision."""
+
+class Float64:
+    """Floating point type with 64 bits of precision."""
+
+class Float32:
+    """Floating point type with 32 bits of precision."""
+
+class Bool:
+    """Boolean type with 8 bits of precision."""
+