yesqa

Signed-off-by: jirka <[email protected]>

Author: Borda

.pre-commit-config.yaml

@@ -37,22 +37,22 @@ repos:
               ^monai/_version.py
           )
 
-  - repo: https://github.com/asottile/yesqa
-    rev: v1.5.0
-    hooks:
-      - id: yesqa
-        name: Unused noqa
-        additional_dependencies:
-          - flake8>=3.8.1
-          - flake8-bugbear<=24.2.6
-          - flake8-comprehensions
-          - pep8-naming
-        exclude: |
-          (?x)^(
-              monai/__init__.py|
-              docs/source/conf.py|
-              tests/utils.py
-          )$
+#  - repo: https://github.com/asottile/yesqa
+#    rev: v1.5.0
+#    hooks:
+#      - id: yesqa
+#        name: Unused noqa
+#        additional_dependencies:
+#          - flake8>=3.8.1
+#          - flake8-bugbear<=24.2.6
+#          - flake8-comprehensions
+#          - pep8-naming
+#        exclude: |
+#          (?x)^(
+#              monai/__init__.py|
+#              docs/source/conf.py|
+#              tests/utils.py
+#          )$
 
   - repo: https://github.com/hadialqattan/pycln
     rev: v2.5.0

monai/apps/nnunet/nnunetv2_runner.py

@@ -18,7 +18,7 @@
 from typing import Any
 
 import monai
-from monai.apps.nnunet.utils import NNUNETMode as M  # noqa: N814
+from monai.apps.nnunet.utils import NNUNETMode as M
 from monai.apps.nnunet.utils import analyze_data, create_new_data_copy, create_new_dataset_json
 from monai.bundle import ConfigParser
 from monai.utils import ensure_tuple, optional_import
@@ -34,7 +34,7 @@
 __all__ = ["nnUNetV2Runner"]
 
 
-class nnUNetV2Runner:  # noqa: N801
+class nnUNetV2Runner:
     """
     ``nnUNetV2Runner`` provides an interface in MONAI to use `nnU-Net` V2 library to analyze, train, and evaluate
     neural networks for medical image segmentation tasks.

monai/metrics/utils.py

@@ -13,7 +13,7 @@
 
 import warnings
 from collections.abc import Iterable, Sequence
-from functools import partial
+from functools import partial, lru_cache
 from types import ModuleType
 from typing import Any
 
@@ -465,7 +465,7 @@ def prepare_spacing(
 ENCODING_KERNEL = {2: [[8, 4], [2, 1]], 3: [[[128, 64], [32, 16]], [[8, 4], [2, 1]]]}
 
 
-@lru_cache(maxsize=None)
+@lru_cache(maxsize=None)  # noqa: UP033
 def _get_neighbour_code_to_normals_table(device=None):
     """
     returns a lookup table. For every binary neighbour code (2x2x2 neighbourhood = 8 neighbours = 8 bits = 256 codes)

monai/transforms/compose.py

@@ -29,12 +29,9 @@
 # For backwards compatibility (so this still works: from monai.transforms.compose import MapTransform)
 from monai.transforms.lazy.functional import apply_pending_transforms
 from monai.transforms.traits import ThreadUnsafe
-from monai.transforms.transform import (  # noqa: F401
+from monai.transforms.transform import (
     LazyTransform,
-    MapTransform,
     Randomizable,
-    RandomizableTransform,
-    Transform,
     apply_transform,
 )
 from monai.utils import MAX_SEED, TraceKeys, TraceStatusKeys, ensure_tuple, get_seed

monai/utils/profiling.py

@@ -337,7 +337,7 @@ def profile_iter(self, name, iterable):
 
         class _Iterable:
 
-            def __iter__(_self):  # noqa: B902, N805 pylint: disable=E0213
+            def __iter__(_self):
                 do_iter = True
                 orig_iter = iter(iterable)
                 caller = getframeinfo(stack()[1][0])

pyproject.toml

@@ -47,6 +47,7 @@ select = [
   "E", "F", "W", # flake8
   "NPY",         # NumPy specific rules
   "UP",          # pyupgrade
+  "RUF100",      # aka yesqa
 ]
 extend-ignore = [
   "E741", # ambiguous variable name

tests/integration/test_integration_lazy_samples.py

@@ -137,7 +137,7 @@ def run_training_test(root_dir, device="cuda:0", cachedataset=0, readers=(None,
                 ops = [0]
                 if len(item.applied_operations) > 1:
                     found = False
-                    for idx, n in enumerate(item.applied_operations):  # noqa
+                    for idx, n in enumerate(item.applied_operations):
                         if n["class"] == "RandCropByPosNegLabel":
                             found = True
                             break

tests/integration/test_loader_semaphore.py

@@ -15,7 +15,6 @@
 import multiprocessing as mp
 import unittest
 
-import monai  # noqa
 
 
 def w():

tests/profile_subclass/pyspy_profiling.py

@@ -17,9 +17,7 @@
 import argparse
 
 import torch
-from min_classes import SubTensor, SubWithTorchFunc  # noqa: F401
 
-from monai.data import MetaTensor  # noqa: F401
 
 Tensor = torch.Tensor
 

tests/runner.py

@@ -32,14 +32,14 @@ def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
         self.timed_tests = {}
 
-    def startTest(self, test):  # noqa: N802
+    def startTest(self, test):
         """Start timer, print test name, do normal test."""
         self.start_time = time.time()
         name = self.getDescription(test)
         self.stream.write(f"Starting test: {name}...\n")
         super().startTest(test)
 
-    def stopTest(self, test):  # noqa: N802
+    def stopTest(self, test):
         """On test end, get time, print, store and do normal behaviour."""
         elapsed = time.time() - self.start_time
         name = self.getDescription(test)