update pre-commit versions (#116)

Author: jameslamb

.github/workflows/github-actions.yml

@@ -86,5 +86,5 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v4
-    - uses: actions/setup-python@v3
-    - uses: pre-commit/[email protected].0
+    - uses: actions/setup-python@v5
+    - uses: pre-commit/[email protected].1

.pre-commit-config.yaml

@@ -1,29 +1,29 @@
 repos:
     - repo: https://github.com/pre-commit/pre-commit-hooks
-      rev: v3.2.0
+      rev: v4.6.0
       hooks:
         -   id: trailing-whitespace
         -   id: end-of-file-fixer
         -   id: check-yaml
         -   id: check-added-large-files
     - repo: https://github.com/PyCQA/isort
-      rev: 5.12.0
+      rev: 5.13.2
       hooks:
             - id: isort
     - repo: https://github.com/psf/black
-      rev: '22.8.0'
+      rev: '24.4.2'
       hooks:
             - id: black
     - repo: https://github.com/PyCQA/flake8
-      rev: '5.0.4'
+      rev: '7.1.0'
       hooks:
             - id: flake8
     - repo: https://github.com/PyCQA/docformatter
-      rev: 'v1.6.5'
+      rev: 'v1.7.5'
       hooks:
             - id: docformatter
     - repo: https://github.com/pre-commit/mirrors-clang-format
-      rev: 'v14.0.6'  # Use the sha / tag you want to point at
+      rev: 'v18.1.8'  # Use the sha / tag you want to point at
       hooks:
         - id: clang-format
           files: \.(cu|cuh|h|cc|inl)$

legateboost/models/base_model.py

@@ -99,5 +99,4 @@ def __eq__(self, other: object) -> bool:
         pass
 
     @abstractmethod
-    def clear(self) -> None:
-        ...
+    def clear(self) -> None: ...  # noqa: E704

legateboost/test/test_estimator.py

@@ -184,14 +184,19 @@ def test_subsample():
         }
         # Overfit the data and check if subsample improves the model
         subsample_eval_result = {}
-        lb.LBRegressor(**params, subsample=0.5,).fit(
+        lb.LBRegressor(
+            **params,
+            subsample=0.5,
+        ).fit(
             X_train,
             y_train,
             eval_result=subsample_eval_result,
             eval_set=[(X_test, y_test)],
         )
         full_eval_result = {}
-        lb.LBRegressor(**params,).fit(
+        lb.LBRegressor(
+            **params,
+        ).fit(
             X_train, y_train, eval_result=full_eval_result, eval_set=[(X_test, y_test)]
         )
         assert (