chore: bump ruff (#521)

* chore: ruff 0.5.2 -> 0.6.5

* chore: update ruff hook

* fix: ruff errors

* chore: ruff 0.6.5 -> 0.6.6

Author: phi-friday

.pre-commit-config.yaml

@@ -2,12 +2,8 @@ repos:
   - hooks:
       - id: ruff
         name: ruff-lint
-    repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.5.2
-
-  - hooks:
       - id: ruff-format
         name: ruff-format
         args: [--check]
     repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.5.2
+    rev: v0.6.6

pyproject.toml

@@ -21,7 +21,7 @@ optional = true
 pytest = "^8.0.0"
 pytest-cov = "^4.1.0"
 coverage = "^7.4.1"
-ruff = "0.5.2"
+ruff = "0.6.6"
 pre-commit = "^3.7.1"
 
 

tests/test_acquisition.py

@@ -12,27 +12,27 @@
 from bayes_opt.target_space import TargetSpace
 
 
-@pytest.fixture()
+@pytest.fixture
 def target_func():
     return lambda x: sum(x)
 
 
-@pytest.fixture()
+@pytest.fixture
 def random_state():
     return np.random.RandomState()
 
 
-@pytest.fixture()
+@pytest.fixture
 def gp(random_state):
     return GaussianProcessRegressor(random_state=random_state)
 
 
-@pytest.fixture()
+@pytest.fixture
 def target_space(target_func):
     return TargetSpace(target_func=target_func, pbounds={"x": (1, 4), "y": (0, 3.0)})
 
 
-@pytest.fixture()
+@pytest.fixture
 def constrained_target_space(target_func):
     constraint_model = ConstraintModel(fun=lambda params: params["x"] + params["y"], lb=0.0, ub=1.0)
     return TargetSpace(

tests/test_constraint.py

@@ -7,12 +7,12 @@
 from bayes_opt import BayesianOptimization, ConstraintModel
 
 
-@pytest.fixture()
+@pytest.fixture
 def target_function():
     return lambda x, y: np.cos(2 * x) * np.cos(y) + np.sin(x)
 
 
-@pytest.fixture()
+@pytest.fixture
 def constraint_function():
     return lambda x, y: np.cos(x) * np.cos(y) - np.sin(x) * np.sin(y)