RUF safe autofixes

pytensor/graph/basic.py

@@ -728,7 +728,7 @@ class NominalVariable(AtomicVariable[_TypeType]):
         return hash((type(self), self.id, self.type))
 
     def __repr__(self):
-        return f"{type(self).__name__}({repr(self.id)}, {repr(self.type)})"
+        return f"{type(self).__name__}({self.id!r}, {self.type!r})"
 
     def signature(self) -> tuple[_TypeType, _IdType]:
         return (self.type, self.id)
@@ -774,7 +774,7 @@ class Constant(AtomicVariable[_TypeType]):
         data_str = repr(self.data)
         if len(data_str) > 20:
             data_str = data_str[:10].strip() + " ... " + data_str[-10:].strip()
-        return f"{type(self).__name__}({repr(self.type)}, data={data_str})"
+        return f"{type(self).__name__}({self.type!r}, data={data_str})"
 
     def clone(self, **kwargs):
         return self

pytensor/graph/rewriting/basic.py

@@ -1091,7 +1091,7 @@ class FromFunctionNodeRewriter(NodeRewriter):
         return getattr(self, "__name__", repr(self))
 
     def __repr__(self):
-        return f"FromFunctionNodeRewriter({repr(self.fn)}, {repr(self._tracks)}, {repr(self.requirements)})"
+        return f"FromFunctionNodeRewriter({self.fn!r}, {self._tracks!r}, {self.requirements!r})"
 
     def print_summary(self, stream=sys.stdout, level=0, depth=-1):
         print(f"{' ' * level}{self.transform} id={id(self)}", file=stream)

pytensor/graph/rewriting/unify.py

@@ -69,7 +69,7 @@ class ConstrainedVar(Var):
         return f"~{self.token} [{self.constraint}]"
 
     def __repr__(self):
-        return f"{type(self).__name__}({repr(self.constraint)}, {self.token})"
+        return f"{type(self).__name__}({self.constraint!r}, {self.token})"
 
 
 def car_Variable(x):

pytensor/link/c/type.py

@@ -607,7 +607,7 @@ class EnumType(CType, dict):
             self.pyint_compat_code
             + "".join(
                 f"""
-            #define {k} {str(self[k])}
+            #define {k} {self[k]!s}
             """
                 for k in sorted(self.keys())
             )

pytensor/tensor/blas.py

@@ -137,7 +137,7 @@ except ImportError as e:
             "PyTensor flag blas__ldflags is empty. "
             "Falling back on slower implementations for "
             "dot(matrix, vector), dot(vector, matrix) and "
-            f"dot(vector, vector) ({str(e)})"
+            f"dot(vector, vector) ({e!s})"
         )
 
 

pytensor/tensor/elemwise.py

@@ -602,7 +602,7 @@ class Elemwise(OpenMPOp):
 
         if not isinstance(scalar_igrads, (list, tuple)):
             raise TypeError(
-                f"{str(self.scalar_op)}.grad returned {str(type(scalar_igrads))} instead of list or tuple"
+                f"{self.scalar_op!s}.grad returned {type(scalar_igrads)!s} instead of list or tuple"
             )
 
         nd = inputs[0].type.ndim  # this is the same for everyone

pytensor/tensor/random/var.py

@@ -8,12 +8,12 @@ from pytensor.tensor.random.type import random_generator_type, random_state_type
 
 class RandomStateSharedVariable(SharedVariable):
     def __str__(self):
-        return self.name or f"RandomStateSharedVariable({repr(self.container)})"
+        return self.name or f"RandomStateSharedVariable({self.container!r})"
 
 
 class RandomGeneratorSharedVariable(SharedVariable):
     def __str__(self):
-        return self.name or f"RandomGeneratorSharedVariable({repr(self.container)})"
+        return self.name or f"RandomGeneratorSharedVariable({self.container!r})"
 
 
 @shared_constructor.register(np.random.RandomState)

pytensor/tensor/rewriting/shape.py

@@ -150,7 +150,7 @@ class ShapeFeature(Feature):
             msg = (
                 f"Failed to infer_shape from Op {node.op}.\nInput shapes: "
                 f"{[self.shape_of[r] for r in node.inputs]}\nException encountered during infer_shape: "
-                f"{type(e)}\nException message: {str(e)}\nTraceback: {traceback.format_exc()}"
+                f"{type(e)}\nException message: {e!s}\nTraceback: {traceback.format_exc()}"
             )
             if config.on_shape_error == "raise":
                 raise Exception(msg).with_traceback(e.__traceback__)

pytensor/tensor/type.py

@@ -199,7 +199,7 @@ class TensorType(CType[np.ndarray], HasDataType, HasShape):
                             "this loss, you can: "
                             f"1) explicitly cast your data to {self.dtype}, or "
                             '2) set "allow_input_downcast=True" when calling '
-                            f'"function". Value: "{repr(data)}"'
+                            f'"function". Value: "{data!r}"'
                         )
                         raise TypeError(err_msg)
                 elif (

tests/graph/test_basic.py

@@ -683,7 +683,7 @@ def test_NominalVariable():
     assert not nv4.equals(nv5)
     assert hash(nv4) != hash(nv5)
 
-    assert repr(nv5) == f"NominalVariable(2, {repr(type3)})"
+    assert repr(nv5) == f"NominalVariable(2, {type3!r})"
 
     assert nv5.signature() == (type3, 2)