[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -5,7 +5,7 @@ ci:
 
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.6
+    rev: v0.11.4
     hooks:
       - id: ruff
         args: [--fix]
@@ -23,14 +23,14 @@ repos:
       - id: trailing-whitespace
 
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.3.0
+    rev: v2.4.1
     hooks:
       - id: codespell
         exclude_types: [json]
         args: [--check-filenames]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.14.1
+    rev: v1.15.0
     hooks:
       - id: mypy
         exclude: (tests|examples)/

aviary/predict.py

@@ -214,9 +214,9 @@ def predict_from_wandb_checkpoints(
     print(f"Using checkpoints from {len(runs)} run(s):")
 
     run_target = runs[0].config["target"]
-    assert all(
-        run_target == run.config["target"] for run in runs
-    ), f"Runs have differing targets, first {run_target=}"
+    assert all(run_target == run.config["target"] for run in runs), (
+        f"Runs have differing targets, first {run_target=}"
+    )
 
     target_col = kwargs.get("target_col")
     if target_col and target_col != run_target:

aviary/train.py

@@ -433,9 +433,9 @@ def checkpoint_model(
         torch.save(checkpoint_dict, checkpoint_path)
 
     if checkpoint_endpoint == "wandb":
-        assert (
-            wandb.run is not None
-        ), "can't save model checkpoint to Weights and Biases, wandb.run is None"
+        assert wandb.run is not None, (
+            "can't save model checkpoint to Weights and Biases, wandb.run is None"
+        )
         torch.save(
             checkpoint_dict,
             f"{wandb.run.dir}/{timestamp + '-' if timestamp else ''}{run_name}-{epochs}.pth",
@@ -584,9 +584,9 @@ def df_train_test_split(
     if folds:
         n_folds, test_fold_idx = folds
         assert 1 < n_folds <= 10, f"{n_folds = } must be between 2 and 10"
-        assert (
-            0 <= test_fold_idx < n_folds
-        ), f"{test_fold_idx = } must be between 0 and {n_folds - 1}"
+        assert 0 <= test_fold_idx < n_folds, (
+            f"{test_fold_idx = } must be between 0 and {n_folds - 1}"
+        )
 
         df_splits: list[pd.DataFrame] = np.array_split(df, n_folds)
         test_df = df_splits.pop(test_fold_idx)

aviary/wren/data.py

@@ -276,8 +276,7 @@ def parse_protostructure_label(
 
     if len(elems) != len(wyckoff_letters):
         raise ValueError(
-            f"Chemical system {chemsys} does not match Wyckoff letters "
-            f"{wyckoff_letters}"
+            f"Chemical system {chemsys} does not match Wyckoff letters {wyckoff_letters}"
         )
 
     wyckoff_site_multiplicities = []

tests/test_wyckoff_ops.py

@@ -349,9 +349,9 @@ def test_get_protostructure_label_from_aflow(structure, expected):
 @pytest.mark.parametrize("structure, expected", zip(TEST_STRUCTS, TEST_PROTOSTRUCTURES))
 def test_get_protostructure_label_from_moyopy(structure, expected):
     """Check that moyopy gives correct protostructure label simple cases."""
-    assert (
-        get_protostructure_label_from_moyopy(structure) == expected
-    ), f"unexpected moyopy protostructure for {structure=}"
+    assert get_protostructure_label_from_moyopy(structure) == expected, (
+        f"unexpected moyopy protostructure for {structure=}"
+    )
 
 
 @pytest.mark.parametrize(
@@ -365,9 +365,9 @@ def test_moyopy_spglib_consistency(protostructure):
     moyopy_label = get_protostructure_label_from_moyopy(struct)
     spglib_label = get_protostructure_label_from_spglib(struct)
 
-    assert (
-        moyopy_label == spglib_label
-    ), f"spglib moyopy protostructure mismatch for {protostructure}"
+    assert moyopy_label == spglib_label, (
+        f"spglib moyopy protostructure mismatch for {protostructure}"
+    )
 
 
 @pytest.mark.skipif(pyxtal is None, reason="pyxtal not installed")