Activate the RUF lints

.pre-commit-config.yaml

@@ -20,12 +20,11 @@ repos:
           )$
       - id: check-merge-conflict
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.14
+    rev: v0.2.0
     hooks:
       - id: ruff
-        args: ["--fix", "--show-source"]
+        args: ["--fix", "--output-format=full"]
       - id: ruff-format
-        args: ["--line-length=88"]
   - repo: https://github.com/pre-commit/mirrors-mypy
     rev: v1.8.0
     hooks:

pyproject.toml

@@ -121,23 +121,19 @@ tag_prefix = "rel-"
 addopts = "--durations=50"
 testpaths = "tests/"
 
-[tool.pylint]
-max-line-length = 88
-
-[tool.pylint.messages_control]
-disable = ["C0330", "C0326"]
-
-
 [tool.ruff]
-select = ["C", "E", "F", "I", "UP", "W"]
-ignore = ["C408", "C901", "E501", "E741"]
+line-length = 88
 exclude = ["doc/", "pytensor/_version.py", "bin/pytensor_cache.py"]
 
+[tool.ruff.lint]
+select = ["C", "E", "F", "I", "UP", "W", "RUF"]
+ignore = ["C408", "C901", "E501", "E741", "RUF012"]
+
 
-[tool.ruff.isort]
+[tool.ruff.lint.isort]
 lines-after-imports = 2
 
-[tool.ruff.per-file-ignores]
+[tool.ruff.lint.per-file-ignores]
 # TODO: Get rid of these:
 "**/__init__.py" = ["F401", "E402", "F403"]
 "pytensor/tensor/linalg.py" = ["F403"]

pytensor/breakpoint.py

@@ -92,7 +92,7 @@ def make_node(self, condition, *monitored_vars):
             new_op.inp_types.append(monitored_vars[i].type)
 
         # Build the Apply node
-        inputs = [condition] + list(monitored_vars)
+        inputs = [condition, *monitored_vars]
         outputs = [inp.type() for inp in monitored_vars]
         return Apply(op=new_op, inputs=inputs, outputs=outputs)
 
@@ -142,7 +142,7 @@ def perform(self, node, inputs, output_storage):
                 output_storage[i][0] = inputs[i + 1]
 
     def grad(self, inputs, output_gradients):
-        return [DisconnectedType()()] + output_gradients
+        return [DisconnectedType()(), *output_gradients]
 
     def infer_shape(self, fgraph, inputs, input_shapes):
         # Return the shape of every input but the condition (first input)

pytensor/compile/compilelock.py

@@ -46,7 +46,9 @@ def force_unlock(lock_dir: os.PathLike):
 
 @contextmanager
 def lock_ctx(
-    lock_dir: Union[str, os.PathLike] = None, *, timeout: Optional[float] = None
+    lock_dir: Optional[Union[str, os.PathLike]] = None,
+    *,
+    timeout: Optional[float] = None,
 ):
     """Context manager that wraps around FileLock and SoftFileLock from filelock package.
 

pytensor/compile/debugmode.py

@@ -892,9 +892,9 @@ def _get_preallocated_maps(
 
         # Use the same step on all dimensions before the last check_ndim.
         if all(s == 1 for s in out_shape[:-check_ndim]):
-            step_signs_list = [(1,)] + step_signs_list
+            step_signs_list = [(1,), *step_signs_list]
         else:
-            step_signs_list = [(-1, 1)] + step_signs_list
+            step_signs_list = [(-1, 1), *step_signs_list]
 
         for step_signs in itertools_product(*step_signs_list):
             for step_size in (1, 2):

pytensor/compile/sharedvalue.py

@@ -209,7 +209,7 @@ def shared(value, name=None, strict=False, allow_downcast=None, **kwargs):
         add_tag_trace(var)
         return var
     except MemoryError as e:
-        e.args = e.args + ("Consider using `pytensor.shared(..., borrow=True)`",)
+        e.args = (*e.args, "Consider using `pytensor.shared(..., borrow=True)`")
         raise
 
 

pytensor/configdefaults.py

@@ -1382,7 +1382,8 @@ def add_caching_dir_configvars():
     "fft_tiling",
     "winograd",
     "winograd_non_fused",
-) + SUPPORTED_DNN_CONV_ALGO_RUNTIME
+    *SUPPORTED_DNN_CONV_ALGO_RUNTIME,
+)
 
 SUPPORTED_DNN_CONV_ALGO_BWD_DATA = (
     "none",
@@ -1391,7 +1392,8 @@ def add_caching_dir_configvars():
     "fft_tiling",
     "winograd",
     "winograd_non_fused",
-) + SUPPORTED_DNN_CONV_ALGO_RUNTIME
+    *SUPPORTED_DNN_CONV_ALGO_RUNTIME,
+)
 
 SUPPORTED_DNN_CONV_ALGO_BWD_FILTER = (
     "none",
@@ -1400,7 +1402,8 @@ def add_caching_dir_configvars():
     "small",
     "winograd_non_fused",
     "fft_tiling",
-) + SUPPORTED_DNN_CONV_ALGO_RUNTIME
+    *SUPPORTED_DNN_CONV_ALGO_RUNTIME,
+)
 
 SUPPORTED_DNN_CONV_PRECISION = (
     "as_input_f32",

pytensor/gradient.py

@@ -1972,7 +1972,7 @@ def inner_function(*args):
     jacobs, updates = pytensor.scan(
         inner_function,
         sequences=pytensor.tensor.arange(expression.shape[0]),
-        non_sequences=[expression] + wrt,
+        non_sequences=[expression, *wrt],
     )
     assert not updates, "Scan has returned a list of updates; this should not happen."
     return as_list_or_tuple(using_list, using_tuple, jacobs)

pytensor/graph/basic.py

@@ -728,7 +728,7 @@ def __hash__(self):
         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 @@ def __repr__(self):
         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/destroyhandler.py

@@ -233,10 +233,11 @@ def fast_inplace_check(fgraph, inputs):
 
     """
     Supervisor = pytensor.compile.function.types.Supervisor
-    protected_inputs = [
-        f.protected for f in fgraph._features if isinstance(f, Supervisor)
-    ]
-    protected_inputs = sum(protected_inputs, [])  # flatten the list
+    protected_inputs = list(
+        itertools.chain.from_iterable(
+            f.protected for f in fgraph._features if isinstance(f, Supervisor)
+        )
+    )
     protected_inputs.extend(fgraph.outputs)
 
     inputs = [

pytensor/graph/features.py

@@ -508,11 +508,13 @@ def consistent_(self, fgraph):
 
 
 class ReplaceValidate(History, Validator):
-    pickle_rm_attr = (
-        ["replace_validate", "replace_all_validate", "replace_all_validate_remove"]
-        + History.pickle_rm_attr
-        + Validator.pickle_rm_attr
-    )
+    pickle_rm_attr = [
+        "replace_validate",
+        "replace_all_validate",
+        "replace_all_validate_remove",
+        *History.pickle_rm_attr,
+        *Validator.pickle_rm_attr,
+    ]
 
     def on_attach(self, fgraph):
         for attr in (

pytensor/graph/rewriting/basic.py

@@ -405,7 +405,7 @@ def print_profile(cls, stream, prof, level=0):
             else:
                 name = rewrite.name
             idx = rewrites.index(rewrite)
-            ll.append((name, rewrite.__class__.__name__, idx) + nb_n)
+            ll.append((name, rewrite.__class__.__name__, idx, *nb_n))
         lll = sorted(zip(prof, ll), key=lambda a: a[0])
 
         for t, rewrite in lll[::-1]:
@@ -1091,7 +1091,7 @@ def __str__(self):
         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)
@@ -1138,7 +1138,8 @@ def decorator(f):
         req = requirements
         if inplace:
             dh_handler = dh.DestroyHandler
-            req = tuple(requirements) + (
+            req = (
+                *requirements,
                 lambda fgraph: fgraph.attach_feature(dh_handler()),
             )
         rval = FromFunctionNodeRewriter(f, tracks, req)

pytensor/graph/rewriting/db.py

@@ -73,7 +73,7 @@ def register(
 
         if use_db_name_as_tag:
             if self.name is not None:
-                tags = tags + (self.name,)
+                tags = (*tags, self.name)
 
         rewriter.name = name
         # This restriction is there because in many place we suppose that

pytensor/graph/rewriting/unify.py

@@ -69,7 +69,7 @@ def __str__(self):
         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):
@@ -283,7 +283,7 @@ def _convert(y):
             var_map[pattern] = v
             return v
         elif isinstance(y, tuple):
-            return etuple(*tuple(_convert(e) for e in y))
+            return etuple(*(_convert(e) for e in y))
         elif isinstance(y, (Number, np.ndarray)):
             from pytensor.tensor import as_tensor_variable
 

pytensor/graph/utils.py

@@ -171,7 +171,7 @@ def __init__(self, *args, **kwargs):
             assert list(kwargs.keys()) == ["variable"]
             error_msg = get_variable_trace_string(kwargs["variable"])
             if error_msg:
-                args = args + (error_msg,)
+                args = (*args, error_msg)
         s = "\n".join(args)  # Needed to have the new line print correctly
         super().__init__(s)
 

pytensor/ifelse.py

@@ -227,7 +227,7 @@ def make_node(self, condition: "TensorLike", *true_false_branches: Any):
 
         return Apply(
             self,
-            [condition] + new_inputs_true_branch + new_inputs_false_branch,
+            [condition, *new_inputs_true_branch, *new_inputs_false_branch],
             output_vars,
         )
 
@@ -275,11 +275,11 @@ def grad(self, ins, grads):
         # condition + epsilon always triggers the same branch as condition
         condition_grad = condition.zeros_like().astype(config.floatX)
 
-        return (
-            [condition_grad]
-            + if_true_op(*inputs_true_grad, return_list=True)
-            + if_false_op(*inputs_false_grad, return_list=True)
-        )
+        return [
+            condition_grad,
+            *if_true_op(*inputs_true_grad, return_list=True),
+            *if_false_op(*inputs_false_grad, return_list=True),
+        ]
 
     def make_thunk(self, node, storage_map, compute_map, no_recycling, impl=None):
         cond = node.inputs[0]
@@ -397,7 +397,7 @@ def ifelse(
 
     new_ifelse = IfElse(n_outs=len(then_branch), as_view=False, name=name)
 
-    ins = [condition] + list(then_branch) + list(else_branch)
+    ins = [condition, *then_branch, *else_branch]
     rval = new_ifelse(*ins, return_list=True)
 
     if rval_type is None:
@@ -611,7 +611,7 @@ def apply(self, fgraph):
                 mn_fs = merging_node.inputs[1:][merging_node.op.n_outs :]
                 pl_ts = proposal.inputs[1:][: proposal.op.n_outs]
                 pl_fs = proposal.inputs[1:][proposal.op.n_outs :]
-                new_ins = [merging_node.inputs[0]] + mn_ts + pl_ts + mn_fs + pl_fs
+                new_ins = [merging_node.inputs[0], *mn_ts, *pl_ts, *mn_fs, *pl_fs]
                 mn_name = "?"
                 if merging_node.op.name:
                     mn_name = merging_node.op.name
@@ -673,7 +673,7 @@ def cond_remove_identical(fgraph, node):
 
     new_ifelse = IfElse(n_outs=len(nw_ts), as_view=op.as_view, name=op.name)
 
-    new_ins = [node.inputs[0]] + nw_ts + nw_fs
+    new_ins = [node.inputs[0], *nw_ts, *nw_fs]
     new_outs = new_ifelse(*new_ins, return_list=True)
 
     rval = []
@@ -711,7 +711,7 @@ def cond_merge_random_op(fgraph, main_node):
             mn_fs = merging_node.inputs[1:][merging_node.op.n_outs :]
             pl_ts = proposal.inputs[1:][: proposal.op.n_outs]
             pl_fs = proposal.inputs[1:][proposal.op.n_outs :]
-            new_ins = [merging_node.inputs[0]] + mn_ts + pl_ts + mn_fs + pl_fs
+            new_ins = [merging_node.inputs[0], *mn_ts, *pl_ts, *mn_fs, *pl_fs]
             mn_name = "?"
             if merging_node.op.name:
                 mn_name = merging_node.op.name

pytensor/link/basic.py

@@ -106,7 +106,7 @@ def __set__(self, value: Any) -> None:
                 self.storage[0] = self.type.filter(value, **kwargs)
 
         except Exception as e:
-            e.args = e.args + (f'Container name "{self.name}"',)
+            e.args = (*e.args, f'Container name "{self.name}"')
             raise
 
     data = property(__get__, __set__)

pytensor/link/c/cmodule.py

@@ -1038,7 +1038,7 @@ def unpickle_failure():
                     _logger.info(f"deleting ModuleCache entry {entry}")
                     key_data.delete_keys_from(self.entry_from_key)
                     del self.module_hash_to_key_data[module_hash]
-                    if key_data.keys and list(key_data.keys)[0][0]:
+                    if key_data.keys and next(iter(key_data.keys))[0]:
                         # this is a versioned entry, so should have been on
                         # disk. Something weird happened to cause this, so we
                         # are responding by printing a warning, removing
@@ -1890,7 +1890,7 @@ def _try_compile_tmp(
                 os.close(fd)
                 fd = None
                 out, err, p_ret = output_subprocess_Popen(
-                    [compiler] + args + [path, "-o", exe_path] + flags
+                    [compiler, *args, path, "-o", exe_path, *flags]
                 )
                 if p_ret != 0:
                     compilation_ok = False

pytensor/link/c/params_type.py

@@ -293,7 +293,7 @@ def __hash__(self):
                 .signature()
                 for i in range(self.__params_type__.length)
             )
-        return hash((type(self), self.__params_type__) + self.__signatures__)
+        return hash((type(self), self.__params_type__, *self.__signatures__))
 
     def __eq__(self, other):
         return (
@@ -437,7 +437,7 @@ def __eq__(self, other):
         )
 
     def __hash__(self):
-        return hash((type(self),) + self.fields + self.types)
+        return hash((type(self), *self.fields, *self.types))
 
     def generate_struct_name(self):
         # This method tries to generate an unique name for the current instance.
@@ -807,7 +807,7 @@ def c_support_code(self, **kwargs):
             )
         )
 
-        return sorted(c_support_code_set) + [final_struct_code]
+        return [*sorted(c_support_code_set), final_struct_code]
 
     def c_code_cache_version(self):
         return ((3,), tuple(t.c_code_cache_version() for t in self.types))