Update tests to support python>=3.11

Author: tybulewicz

.pre-commit-config.yaml

@@ -15,7 +15,7 @@ repos:
 
   # Ruff version.
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.15.2"
+    rev: "v0.6.2"
     hooks:
       # Run the linter.
       - id: ruff

pyproject.toml

@@ -188,17 +188,6 @@ lint.ignore = [
 
     # flake8-fixme (`FIX`)
     "FIX002", # Line contains TODO, consider resolving the issue
-
-    # upgraded to most recent ruff, remove the following rules for now
-    "LOG015",
-    "RUF005",
-    "RUF052",
-    "RUF067",
-    "RUF069",
-    "TC001",
-    "TC002",
-    "TC003",
-
 ]
 
 # Allow autofix for all enabled rules (when `--fix`) is provided.
@@ -235,8 +224,8 @@ line-length = 120
 # Allow unused variables when underscore-prefixed.
 lint.dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
 
-# Assume Python 3.14.
-target-version = "py314"
+# Assume Python 3.11.
+target-version = "py311"
 
 # Allow imports relative to the "src" and "tests" directories.
 src = ["src", "tests"]

src/model_api/models/classification.py

@@ -258,7 +258,7 @@ def get_multiclass_predictions(self, outputs: dict) -> list[Label]:
         if not is_softmaxed(logits, axis=axis):
             logits = softmax(logits, axis=axis)
         top_k_result = top_k(logits, self.params.topk, axis=axis)
-        scores = top_k_result.values[0]
+        scores = top_k_result.values[0]  # noqa: PD011 # silencing false positive - it's not pandas code
         indices = top_k_result.indices[0]
 
         labels_list = self.params.labels

src/model_api/models/parameters.py

@@ -45,7 +45,7 @@ def __dir__(self) -> list[str]:
         try:
             parameters = self._model.get_cached_parameters()
             return list(parameters.keys())
-        except AttributeError, TypeError, ValueError:
+        except (AttributeError, TypeError, ValueError):
             return []
 
 

tests/accuracy/test_accuracy.py

@@ -223,9 +223,9 @@ def compare_detection_result(outputs: DetectionResult, reference: dict) -> None:
     if expected_bboxes.size == 0 and outputs.bboxes.size == 0:
         expected_bboxes = expected_bboxes.reshape(0, 4)
 
-    assert outputs.bboxes.shape == expected_bboxes.shape, (
-        f"bboxes shape mismatch: {outputs.bboxes.shape} vs {expected_bboxes.shape}"
-    )
+    assert (
+        outputs.bboxes.shape == expected_bboxes.shape
+    ), f"bboxes shape mismatch: {outputs.bboxes.shape} vs {expected_bboxes.shape}"
 
     # Sort both outputs and expected by bbox coordinates (x1, y1, x2, y2) for deterministic comparison
     output_sort_indices = np.lexsort((