Fix UP007 (Typealias Unions and Optionals)

Author: Armavica

pymc/backends/__init__.py

@@ -81,7 +81,7 @@
 
     from pymc.backends.mcbackend import init_chain_adapters
 
-    TraceOrBackend = Union[BaseTrace, Backend]
+    TraceOrBackend = BaseTrace | Backend
     RunType: TypeAlias = Run
     HAS_MCB = True
 except ImportError:

pymc/gp/cov.py

@@ -19,7 +19,7 @@
 from collections.abc import Callable, Sequence
 from functools import reduce
 from operator import add, mul
-from typing import Any, Union
+from typing import Any
 
 import numpy as np
 import pytensor.tensor as pt
@@ -51,8 +51,8 @@
 
 from pymc.pytensorf import constant_fold
 
-TensorLike = Union[np.ndarray, TensorVariable]
-IntSequence = Union[np.ndarray, Sequence[int]]
+TensorLike = np.ndarray | TensorVariable
+IntSequence = np.ndarray | Sequence[int]
 
 
 class BaseCovariance:

pymc/gp/hsgp_approx.py

@@ -17,7 +17,6 @@
 
 from collections.abc import Sequence
 from types import ModuleType
-from typing import Union
 
 import numpy as np
 import pytensor.tensor as pt
@@ -28,7 +27,7 @@
 from pymc.gp.gp import Base
 from pymc.gp.mean import Mean, Zero
 
-TensorLike = Union[np.ndarray, pt.TensorVariable]
+TensorLike = np.ndarray | pt.TensorVariable
 
 
 def set_boundary(Xs: TensorLike, c: numbers.Real | TensorLike) -> TensorLike:

pymc/model/transform/basic.py

@@ -12,7 +12,6 @@
 #   See the License for the specific language governing permissions and
 #   limitations under the License.
 from collections.abc import Sequence
-from typing import Union
 
 from pytensor import Variable
 from pytensor.graph import ancestors
@@ -25,7 +24,7 @@
     model_from_fgraph,
 )
 
-ModelVariable = Union[Variable, str]
+ModelVariable = Variable | str
 
 
 def prune_vars_detached_from_observed(model: Model) -> Model:

pymc/pytensorf.py

@@ -14,10 +14,6 @@
 import warnings
 
 from collections.abc import Callable, Generator, Iterable, Sequence
-from typing import (
-    Optional,
-    Union,
-)
 
 import numpy as np
 import pandas as pd
@@ -58,7 +54,7 @@
 from pymc.util import makeiter
 from pymc.vartypes import continuous_types, isgenerator, typefilter
 
-PotentialShapeType = Union[int, np.ndarray, Sequence[int | Variable], TensorVariable]
+PotentialShapeType = int | np.ndarray | Sequence[int | Variable] | TensorVariable
 
 
 __all__ = [
@@ -765,7 +761,7 @@ def replace_rng_nodes(outputs: Sequence[TensorVariable]) -> Sequence[TensorVaria
     return graph.outputs
 
 
-SeedSequenceSeed = Optional[int | Sequence[int] | np.ndarray | np.random.SeedSequence]
+SeedSequenceSeed = None | int | Sequence[int] | np.ndarray | np.random.SeedSequence
 
 
 def reseed_rngs(

pymc/util.py

@@ -16,7 +16,7 @@
 import warnings
 
 from collections.abc import Sequence
-from typing import Any, NewType, Optional, Union, cast
+from typing import Any, NewType, cast
 
 import arviz
 import cloudpickle
@@ -405,8 +405,8 @@ def wrapped(**kwargs):
     return wrapped
 
 
-RandomSeed = Optional[int | Sequence[int] | np.ndarray]
-RandomState = Union[RandomSeed, np.random.RandomState, np.random.Generator]
+RandomSeed = None | int | Sequence[int] | np.ndarray
+RandomState = RandomSeed | np.random.RandomState | np.random.Generator
 
 
 def _get_seeds_per_chain(