Complete replace flake8 with ruff and update rules

.github/workflows/pythonapp.yml

@@ -22,7 +22,7 @@ jobs:
   #   - docker-py3-pip- (shared)
   #   - ubuntu py37 pip-
   #   - os-latest-pip- (shared)
-  flake8-py3:
+  lint-py3:
     runs-on: ubuntu-latest
     strategy:
       matrix:

.github/workflows/weekly-preview.yml

@@ -5,7 +5,7 @@ on:
   - cron: "0 2 * * 0"  # 02:00 of every Sunday
 
 jobs:
-  flake8-py3:
+  lint-py3:
     runs-on: ubuntu-latest
     strategy:
       matrix:

CONTRIBUTING.md

@@ -37,7 +37,7 @@ Please note that, as per PyTorch, MONAI uses American English spelling. This mea
 
 ### Preparing pull requests
 
-To ensure the code quality, MONAI relies on several linting tools ([flake8 and its plugins](https://gitlab.com/pycqa/flake8), [black](https://github.com/psf/black), [isort](https://github.com/timothycrosley/isort), [ruff](https://github.com/astral-sh/ruff)),
+To ensure the code quality, MONAI relies on several linting tools ([black](https://github.com/psf/black), [isort](https://github.com/timothycrosley/isort), [ruff](https://github.com/astral-sh/ruff)),
 static type analysis tools ([mypy](https://github.com/python/mypy), [pytype](https://github.com/google/pytype)), as well as a set of unit/integration tests.
 
 This section highlights all the necessary preparation steps required before sending a pull request.
@@ -51,7 +51,7 @@ To collaborate efficiently, please read through this section and follow them.
 
 #### Checking the coding style
 
-Coding style is checked and enforced by flake8, black, isort, and ruff, using [a flake8 configuration](./setup.cfg) similar to [PyTorch's](https://github.com/pytorch/pytorch/blob/master/.flake8).
+Coding style is checked and enforced by black, isort, and ruff.
 Before submitting a pull request, we recommend that all linting should pass, by running the following command locally:
 
 ```bash

monai/apps/auto3dseg/bundle_gen.py

@@ -208,7 +208,7 @@ def _create_cmd(self, train_params: None | dict = None) -> tuple[str, str]:
         config_files = []
         if os.path.isdir(config_dir):
             for file in sorted(os.listdir(config_dir)):
-                if file.endswith("yaml") or file.endswith("json"):
+                if file.endswith(("yaml", "json")):
                     # Python Fire may be confused by single-quoted WindowsPath
                     config_files.append(Path(os.path.join(config_dir, file)).as_posix())
 

monai/apps/deepedit/transforms.py

@@ -164,7 +164,6 @@ class NormalizeLabelsInDatasetd(RemapLabelsToSequentiald):
     which better describes the transform's functionality.
     """
 
-    pass
 
 
 class SingleLabelSelectiond(MapTransform):

monai/apps/detection/transforms/box_ops.py

@@ -179,7 +179,7 @@ def flip_boxes(
     spatial_dims: int = get_spatial_dims(boxes=boxes)
     spatial_size = ensure_tuple_rep(spatial_size, spatial_dims)
     if flip_axes is None:
-        flip_axes = tuple(range(0, spatial_dims))
+        flip_axes = tuple(range(spatial_dims))
     flip_axes = ensure_tuple(flip_axes)
 
     # flip box

monai/auto3dseg/algo_gen.py

@@ -25,23 +25,18 @@ class Algo:
 
     def set_data_stats(self, *args, **kwargs):
         """Provide dataset (and summaries) so that the model creation can depend on the input datasets."""
-        pass
 
     def train(self, *args, **kwargs):
         """Read training/validation data and output a model."""
-        pass
 
     def predict(self, *args, **kwargs):
         """Read test data and output model predictions."""
-        pass
 
     def get_score(self, *args, **kwargs):
         """Returns the model quality measurement based on training and validation datasets."""
-        pass
 
     def get_output_path(self, *args, **kwargs):
         """Returns the algo output paths for scripts location"""
-        pass
 
 
 class AlgoGen(Randomizable):
@@ -70,31 +65,24 @@ class AlgoGen(Randomizable):
 
     def set_data_stats(self, *args, **kwargs):  # type ignore
         """Provide dataset summaries/properties so that the generator can be conditioned on the input datasets."""
-        pass
 
     def set_budget(self, *args, **kwargs):
         """Provide computational budget so that the generator outputs algorithms that requires reasonable resources."""
-        pass
 
     def set_score(self, *args, **kwargs):
         """Feedback from the previously generated algo, the score can be used for new Algo generations."""
-        pass
 
     def get_data_stats(self, *args, **kwargs):
         """Get current dataset summaries."""
-        pass
 
     def get_budget(self, *args, **kwargs):
         """Get the current computational budget."""
-        pass
 
     def get_history(self, *args, **kwargs):
         """Get the previously generated algo."""
-        pass
 
     def generate(self):
         """Generate new Algo -- based on data_stats, budget, and history of previous algo generations."""
-        pass
 
     def run_algo(self, *args, **kwargs):
         """
@@ -104,4 +92,3 @@ def run_algo(self, *args, **kwargs):
         implemented separately is preferred to run them. In this case the controller should also report back the
         scores and the algo history, so that the future ``AlgoGen.generate`` can leverage the information.
         """
-        pass

monai/data/box_utils.py

@@ -591,7 +591,7 @@ def convert_box_mode(
 
     # check validity of corners
     spatial_dims = get_spatial_dims(boxes=boxes_t)
-    for axis in range(0, spatial_dims):
+    for axis in range(spatial_dims):
         if (corners[spatial_dims + axis] < corners[axis]).sum() > 0:
             warnings.warn("Given boxes has invalid values. The box size must be non-negative.")
 
@@ -731,7 +731,7 @@ def is_valid_box_values(boxes: NdarrayOrTensor) -> bool:
         whether ``boxes`` is valid
     """
     spatial_dims = get_spatial_dims(boxes=boxes)
-    for axis in range(0, spatial_dims):
+    for axis in range(spatial_dims):
         if (boxes[:, spatial_dims + axis] < boxes[:, axis]).sum() > 0:
             return False
     return True
@@ -1041,7 +1041,7 @@ def spatial_crop_boxes(
 
     # makes sure the bounding boxes are within the patch
     spatial_dims = get_spatial_dims(boxes=boxes, spatial_size=roi_end)
-    for axis in range(0, spatial_dims):
+    for axis in range(spatial_dims):
         boxes_t[:, axis] = boxes_t[:, axis].clamp(min=roi_start_t[axis], max=roi_end_t[axis] - TO_REMOVE)
         boxes_t[:, axis + spatial_dims] = boxes_t[:, axis + spatial_dims].clamp(
             min=roi_start_t[axis], max=roi_end_t[axis] - TO_REMOVE
@@ -1133,7 +1133,7 @@ def non_max_suppression(
 
     # initialize the list of picked indexes
     pick = []
-    idxs = torch.Tensor(list(range(0, boxes_sort.shape[0]))).to(device=boxes_t.device, dtype=torch.long)
+    idxs = torch.Tensor(list(range(boxes_sort.shape[0]))).to(device=boxes_t.device, dtype=torch.long)
 
     # keep looping while some indexes still remain in the indexes list
     while len(idxs) > 0:

monai/fl/client/client_algo.py

@@ -34,7 +34,6 @@ def initialize(self, extra: dict | None = None) -> None:
         Args:
             extra: optional extra information, e.g. dict of `ExtraItems.CLIENT_NAME` and/or `ExtraItems.APP_ROOT`.
         """
-        pass
 
     def finalize(self, extra: dict | None = None) -> None:
         """
@@ -43,7 +42,6 @@ def finalize(self, extra: dict | None = None) -> None:
         Args:
             extra: Dict with additional information that can be provided by the FL system.
         """
-        pass
 
     def abort(self, extra: dict | None = None) -> None:
         """
@@ -53,8 +51,6 @@ def abort(self, extra: dict | None = None) -> None:
             extra: Dict with additional information that can be provided by the FL system.
         """
 
-        pass
-
 
 class ClientAlgoStats(BaseClient):
 

monai/metrics/loss_metric.py

@@ -16,10 +16,10 @@
 import torch
 from torch.nn.modules.loss import _Loss
 
+from monai.config import TensorOrList
 from monai.metrics.utils import do_metric_reduction
 from monai.utils import MetricReduction
 
-from ..config import TensorOrList
 from .metric import CumulativeIterationMetric
 
 

monai/networks/blocks/feature_pyramid_network.py

@@ -85,7 +85,6 @@ def forward(self, results: list[Tensor], x: list[Tensor], names: list[str]):
             - the extended set of results of the FPN
             - the extended set of names for the results
         """
-        pass
 
 
 class LastLevelMaxPool(ExtraFPNBlock):

monai/networks/nets/dints.py

@@ -627,7 +627,6 @@ def __init__(
 
     def forward(self, x):
         """This function to be implemented by the architecture instances or search spaces."""
-        pass
 
 
 class TopologyInstance(TopologyConstruction):

monai/networks/trt_compiler.py

@@ -98,8 +98,6 @@ class ShapeError(Exception):
     Exception class to report errors from setting TRT plan input shapes
     """
 
-    pass
-
 
 class TRTEngine:
     """

monai/transforms/regularization/array.py

@@ -17,10 +17,9 @@
 import torch
 
 from monai.data.meta_obj import get_track_meta
+from monai.transforms.transform import RandomizableTransform
 from monai.utils.type_conversion import convert_to_dst_type, convert_to_tensor
 
-from ..transform import RandomizableTransform
-
 __all__ = ["MixUp", "CutMix", "CutOut", "Mixer"]
 
 

monai/transforms/regularization/dictionary.py

@@ -18,10 +18,10 @@
 from monai.config import KeysCollection
 from monai.config.type_definitions import NdarrayOrTensor
 from monai.data.meta_obj import get_track_meta
+from monai.transforms.transform import MapTransform, RandomizableTransform
 from monai.utils import convert_to_tensor
 from monai.utils.misc import ensure_tuple
 
-from ..transform import MapTransform, RandomizableTransform
 from .array import CutMix, CutOut, MixUp
 
 __all__ = ["MixUpd", "MixUpD", "MixUpDict", "CutMixd", "CutMixD", "CutMixDict", "CutOutd", "CutOutD", "CutOutDict"]

monai/transforms/traits.py

@@ -74,8 +74,6 @@ class RandomizableTrait:
     implementors of MONAI transforms.
     """
 
-    pass
-
 
 class MultiSampleTrait:
     """
@@ -85,8 +83,6 @@ class MultiSampleTrait:
     of MONAI transforms.
     """
 
-    pass
-
 
 class ThreadUnsafe:
     """
@@ -98,8 +94,6 @@ class ThreadUnsafe:
     its extensions, where the transform cache is built with multiple threads.
     """
 
-    pass
-
 
 class ReduceTrait:
     """
@@ -108,5 +102,3 @@ class ReduceTrait:
     This interface can be extended from by people adapting transforms to the MONAI framework as well
     as by implementors of MONAI transforms.
     """
-
-    pass

monai/utils/deprecate_utils.py

@@ -19,10 +19,9 @@
 from types import FunctionType
 from typing import Any, TypeVar
 
+from monai import __version__
 from monai.utils.module import version_leq
 
-from .. import __version__
-
 __all__ = ["deprecated", "deprecated_arg", "DeprecatedError", "deprecated_arg_default"]
 T = TypeVar("T", type, Callable)
 
@@ -201,7 +200,7 @@ def _wrapper(*args, **kwargs):
                 # if name is specified and new_name is not specified
                 kwargs[new_name] = kwargs[name]
                 try:
-                    sig.bind(*args, **kwargs).arguments
+                    _ = sig.bind(*args, **kwargs).arguments
                 except TypeError:
                     # multiple values for new_name using both args and kwargs
                     kwargs.pop(new_name, None)

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):  # noqa: N805 pylint: disable=E0213
                 do_iter = True
                 orig_iter = iter(iterable)
                 caller = getframeinfo(stack()[1][0])

pyproject.toml

@@ -39,12 +39,19 @@ all = true
 exclude = "monai/bundle/__main__.py"
 
 [tool.ruff]
-line-length = 133
+line-length = 120
 target-version = "py39"
 
 [tool.ruff.lint]
 select = [
-  "E", "F", "W", # flake8
+  "B",  # flake8-bugbear - https://docs.astral.sh/ruff/rules/#flake8-bugbear-b
+  "C90",  # mccabe (complexity) - https://docs.astral.sh/ruff/rules/#mccabe-c90
+  "E",  # pycodestyle errors - https://docs.astral.sh/ruff/rules/#error-e
+  "F",  # pyflakes - https://docs.astral.sh/ruff/rules/#pyflakes-f
+  "N",  # pep8-naming - https://docs.astral.sh/ruff/rules/#pep8-naming-n
+  "PIE",  # flake8-pie - https://docs.astral.sh/ruff/rules/#flake8-pie-pie
+  "TID", # flake8-tidy-imports - https://docs.astral.sh/ruff/rules/#flake8-tidy-imports-tid
+  "W",  # pycodestyle warnings - https://docs.astral.sh/ruff/rules/#warning-w
   "NPY",         # NumPy specific rules
   "UP",          # pyupgrade
   # "RUF100",      # aka yesqa
@@ -53,7 +60,28 @@ extend-ignore = [
   "E741", # ambiguous variable name
   "F401", # unused import
   "NPY002", # numpy-legacy-random
+  "E203", # whitespace before ':' (pycodestyle)
+  "E501", # line too long (pycodestyle)
+  "C408", # unnecessary collection call (flake8-comprehensions)
+  "N812", # lowercase imported as non lowercase (pep8-naming)
+  "B023", # function uses loop variable (flake8-bugbear)
+  "B905", # zip() without an explicit strict= parameter (flake8-bugbear)
+  "B028", # no explicit stacklevel keyword argument found (flake8-bugbear)
+]
+
+[tool.ruff.lint.per-file-ignores]
+"tests/**" = [
+  "B018",
+  "C901",
+  "N999",
+  "N801"
 ]
+"monai/apps/detection/utils/ATSS_matcher.py" = [
+  "N999"
+]
+
+[tool.ruff.lint.mccabe]
+max-complexity = 50  # todo lower this treshold when yesqa id replaced with Ruff's RUF100
 
 [tool.pytype]
 # Space-separated list of files or directories to exclude.

requirements-dev.txt

@@ -10,9 +10,6 @@ tensorboard>=2.12.0  # https://github.com/Project-MONAI/MONAI/issues/7434
 scikit-image>=0.19.0
 tqdm>=4.47.0
 lmdb
-flake8>=3.8.1
-flake8-bugbear<=24.2.6  # https://github.com/Project-MONAI/MONAI/issues/7690
-flake8-comprehensions
 mccabe
 pep8-naming
 pycodestyle