Merge pull request #541 from alan-turing-institute/540-add-target-version-to-ruff

Add target-version to ruff config to extend lints (#540)

Author: sgreenbury

autoemulate/experimental/data/utils.py

@@ -29,11 +29,11 @@ def _convert_to_dataset(
         if isinstance(y, np.ndarray):
             y = torch.tensor(y, dtype=torch.float32)
 
-        if isinstance(x, (torch.Tensor, np.ndarray)) and isinstance(
-            y, (torch.Tensor, np.ndarray)
+        if isinstance(x, torch.Tensor | np.ndarray) and isinstance(
+            y, torch.Tensor | np.ndarray
         ):
             dataset = TensorDataset(x, y)
-        elif isinstance(x, (torch.Tensor, np.ndarray)) and y is None:
+        elif isinstance(x, torch.Tensor | np.ndarray) and y is None:
             dataset = TensorDataset(x)
         elif isinstance(x, Dataset) and y is None:
             dataset = x

autoemulate/experimental/emulators/lightgbm.py

@@ -104,7 +104,7 @@ def _fit(self, x: TensorLike, y: TensorLike):
     def _predict(self, x: TensorLike) -> OutputLike:
         """Predicts the output of the emulator for a given input."""
         y_pred = self.model_.predict(x)
-        assert not isinstance(y_pred, (spmatrix, list))
+        assert not isinstance(y_pred, spmatrix | list)
         _, y = self._convert_to_tensors(x, y_pred)
         return y
 

autoemulate/experimental/emulators/neural_processes/conditional_neural_process.py

@@ -105,7 +105,7 @@ def cnp_collate_fn(batch, device: DeviceLike | None = None):
     as we don't do layernorm or attention, but we should modify cnp etc. to handle this
     better.
     """
-    X, y = zip(*batch)
+    X, y = zip(*batch, strict=False)
     device = get_torch_device(device)
 
     # Get the maximum number of context and target points in the batch
@@ -123,7 +123,7 @@ def cnp_collate_fn(batch, device: DeviceLike | None = None):
     target_mask = torch.zeros(len(batch), max_target, dtype=torch.bool)
 
     # Fill in the batched tensors
-    for i, (x, yi) in enumerate(zip(X, y)):
+    for i, (x, yi) in enumerate(zip(X, y, strict=False)):
         n_context = x["x_context"].shape[0]
         n_target = x["x_target"].shape[0]
 

pyproject.toml

@@ -68,6 +68,7 @@ include = ["autoemulate/experimental/*", "tests/experimental/*"]
 src = ["autoemulate/"]
 line-length = 88
 include = ["autoemulate/experimental/**/*.py", "tests/experimental/**/*.py"]
+target-version = "py310"
 
 [tool.ruff.format]
 docstring-code-format = true