iter

.pre-commit-config.yaml

@@ -21,9 +21,3 @@ repos:
      -  id: mypy
         files: imblearn/
         additional_dependencies: [pytest==6.2.4]
--   repo: https://github.com/MarcoGorelli/cython-lint
-    rev: v0.15.0
-    hooks:
-    # TODO: add the double-quote-cython-strings hook when it's usability has improved:
-    # possibility to pass a directory and use it as a check instead of auto-formatter.
-    -   id: cython-lint

imblearn/ensemble/_bagging.py

@@ -21,8 +21,8 @@
     # scikit-learn >= 1.2
     from sklearn.utils.parallel import Parallel, delayed
 except (ImportError, ModuleNotFoundError):
-    from sklearn.utils.fixes import delayed
     from joblib import Parallel
+    from sklearn.utils.fixes import delayed
 
 from ..base import _ParamsValidationMixin
 from ..pipeline import Pipeline

imblearn/ensemble/_easy_ensemble.py

@@ -21,8 +21,8 @@
     # scikit-learn >= 1.2
     from sklearn.utils.parallel import Parallel, delayed
 except (ImportError, ModuleNotFoundError):
-    from sklearn.utils.fixes import delayed
     from joblib import Parallel
+    from sklearn.utils.fixes import delayed
 
 from ..base import _ParamsValidationMixin
 from ..pipeline import Pipeline

imblearn/ensemble/_forest.py

@@ -30,8 +30,8 @@
     # scikit-learn >= 1.2
     from sklearn.utils.parallel import Parallel, delayed
 except (ImportError, ModuleNotFoundError):
-    from sklearn.utils.fixes import delayed
     from joblib import Parallel
+    from sklearn.utils.fixes import delayed
 
 from ..base import _ParamsValidationMixin
 from ..pipeline import make_pipeline

imblearn/keras/tests/test_generator.py

@@ -10,11 +10,15 @@
 from keras.utils.np_utils import to_categorical  # noqa: E402
 
 from imblearn.datasets import make_imbalance  # noqa: E402
-from imblearn.keras import BalancedBatchGenerator  # noqa: E402
-from imblearn.keras import balanced_batch_generator  # noqa: E402
+from imblearn.keras import (
+    BalancedBatchGenerator,  # noqa: E402
+    balanced_batch_generator,  # noqa: E402
+)
 from imblearn.over_sampling import RandomOverSampler  # noqa: E402
-from imblearn.under_sampling import ClusterCentroids  # noqa: E402
-from imblearn.under_sampling import NearMiss  # noqa: E402
+from imblearn.under_sampling import (
+    ClusterCentroids,  # noqa: E402
+    NearMiss,  # noqa: E402
+)
 
 
 @pytest.fixture

imblearn/over_sampling/_smote/base.py

@@ -479,7 +479,8 @@ class SMOTENC(SMOTE):
 
     See
     :ref:`sphx_glr_auto_examples_over-sampling_plot_comparison_over_sampling.py`,
-    and :ref:`sphx_glr_auto_examples_over-sampling_plot_illustration_generation_sample.py`.  # noqa
+    and
+    :ref:`sphx_glr_auto_examples_over-sampling_plot_illustration_generation_sample.py`.
 
     References
     ----------

imblearn/tests/test_pipeline.py

@@ -246,7 +246,7 @@ def test_pipeline_init():
 
     # Test clone
     pipe2 = clone(pipe)
-    assert not pipe.named_steps["svc"] is pipe2.named_steps["svc"]
+    assert pipe.named_steps["svc"] is not pipe2.named_steps["svc"]
 
     # Check that apart from estimators, the parameters are the same
     params = pipe.get_params(deep=True)
@@ -1163,7 +1163,6 @@ def test_predict_with_predict_params():
 
 
 def test_resampler_last_stage_passthrough():
-
     X, y = make_classification(
         n_classes=2,
         class_sep=2,

pyproject.toml

@@ -4,3 +4,22 @@ include = '\.pyi?$'
 
 [tool.isort]
 profile = "black"
+
+[tool.ruff]
+# all rules can be found here: https://beta.ruff.rs/docs/rules/
+select = ["E", "F", "W", "I"]
+
+# max line length for black
+line-length = 88
+target-version = "py38"
+
+ignore=[
+    # space before : (needed for how black formats slicing)
+    "E203",
+    # do not assign a lambda expression, use a def
+    "E731",
+    # do not use variables named 'l', 'O', or 'I'
+    "E741",
+    # Import not on the top of the file
+    "E402",
+]