ci: test windows

.github/workflows/ci.yml

@@ -23,17 +23,52 @@ jobs:
       - run: pipx run check-manifest
 
   test:
-    uses: pyapp-kit/workflows/.github/workflows/test-pyrepo.yml@v2
-    with:
-      os: ${{ matrix.os }}
-      python-version: ${{ matrix.python-version }}
-      coverage-upload: artifact
-      qt: pyqt6
+    name: ${{ matrix.platform }} (${{ matrix.python-version }})
+    runs-on: ${{ matrix.platform }}
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-latest, macos-latest]
-        python-version: ["3.8", "3.10", "3.11"]
+        python-version: ["3.10", "3.11", "3.12"]
+        platform: [ubuntu-latest, macos-latest, windows-latest]
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: pyvista/setup-headless-display-action@v2
+        with:
+          qt: true
+      # strangely, this lib is in headless-display-action, but doesn't get installed
+      - if: runner.os == 'Linux'
+        run: sudo apt-get install -y libxcb-cursor0
+
+      - uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache-dependency-path: "pyproject.toml"
+          cache: "pip"
+
+      - name: Install Dependencies
+        run: |
+          python -m pip install -U pip
+          python -m pip install .[test,pyqt]
+
+      - name: 🧪 Run Tests
+        run: coverage run -p -m pytest --color=yes
+
+      - name: Generate UUID
+        shell: bash
+        run: |
+          if [[ "$RUNNER_OS" == "Windows" ]]; then
+            echo "UUID=$(powershell -Command "[guid]::NewGuid().ToString()")" >> $GITHUB_ENV
+          else
+            echo "UUID=$(uuidgen)" >> $GITHUB_ENV
+          fi
+
+      - name: Upload coverage data
+        uses: actions/upload-artifact@v4
+        with:
+          name: covreport-${{ matrix.platform }}-py${{ matrix.python-version }}-${{ env.UUID }}
+          path: ./.coverage*
 
   test-array-libs:
     uses: pyapp-kit/workflows/.github/workflows/test-pyrepo.yml@v2

src/ndv/viewer/_data_wrapper.py

@@ -2,8 +2,10 @@
 
 from __future__ import annotations
 
+import atexit
 import logging
 import sys
+import threading
 from abc import abstractmethod
 from concurrent.futures import Future, ThreadPoolExecutor
 from contextlib import suppress
@@ -61,6 +63,11 @@
 _EXECUTOR = ThreadPoolExecutor(max_workers=2)
 
 
+@atexit.register
+def _cleanup_executor() -> None:
+    _EXECUTOR.shutdown(wait=False)
+
+
 def _recurse_subclasses(cls: _T) -> Iterator[_T]:
     for subclass in cls.__subclasses__():
         yield subclass
@@ -104,6 +111,7 @@
 
     def __init__(self, data: ArrayT) -> None:
         self._data = data
+        self._lock = threading.Lock()
 
     @property
     def data(self) -> ArrayT:
@@ -197,7 +205,8 @@
     """Wrapper for xarray DataArray objects."""
 
     def isel(self, indexers: Indices) -> np.ndarray:
-        return np.asarray(self._data.isel(indexers))
+        with self._lock:
+            return np.asarray(self._data.isel(indexers))
 
     def sizes(self) -> Mapping[Hashable, int]:
         return {k: int(v) for k, v in self._data.sizes.items()}
@@ -252,8 +261,9 @@
             labels, values = zip(*indexers.items())
             origins = (0,) * len(labels)
             slc = self._ts.d[labels].translate_to[origins][values]
-        result = self._data[slc].read().result()
-        return np.asarray(result)
+        with self._lock:
+            result = self._data[slc].read().result()
+            return np.asarray(result)
 
     @classmethod
     def supports(cls, obj: Any) -> TypeGuard[ts.TensorStore]:
@@ -268,8 +278,11 @@
     PRIORITY = 100
 
     def isel(self, indexers: Indices) -> np.ndarray:
-        idx = tuple(indexers.get(k, slice(None)) for k in range(len(self._data.shape)))
-        return self._asarray(self._data[idx])
+        with self._lock:
+            idx = tuple(
+                indexers.get(k, slice(None)) for k in range(len(self._data.shape))
+            )
+            return self._asarray(self._data[idx])
 
     def _asarray(self, data: npt.ArrayLike) -> np.ndarray:
         return np.asarray(data)
@@ -305,8 +318,11 @@
     """Wrapper for dask array objects."""
 
     def isel(self, indexers: Indices) -> np.ndarray:
-        idx = tuple(indexers.get(k, slice(None)) for k in range(len(self._data.shape)))
-        return np.asarray(self._data[idx].compute())
+        with self._lock:
+            idx = tuple(
+                indexers.get(k, slice(None)) for k in range(len(self._data.shape))
+            )
+            return np.asarray(self._data[idx].compute())
 
     @classmethod
     def supports(cls, obj: Any) -> TypeGuard[da.Array]:
@@ -374,8 +390,9 @@
 
     def isel(self, indexers: Indices) -> np.ndarray:
         # convert possibly named indices to integer indices
-        real_indexers = {self._name2index.get(k, k): v for k, v in indexers.items()}
-        return super().isel(real_indexers)
+        with self._lock:
+            real_indexers = {self._name2index.get(k, k): v for k, v in indexers.items()}
+            return super().isel(real_indexers)
 
 
 class TorchTensorWrapper(DataWrapper["torch.Tensor"]):
@@ -397,10 +414,13 @@
 
     def isel(self, indexers: Indices) -> np.ndarray:
         # convert possibly named indices to integer indices
-        real_indexers = {self._name2index.get(k, k): v for k, v in indexers.items()}
-        # convert to tuple of slices
-        idx = tuple(real_indexers.get(i, slice(None)) for i in range(self.data.ndim))
-        return self.data[idx].numpy(force=True)  # type: ignore [no-any-return]
+        with self._lock:
+            real_indexers = {self._name2index.get(k, k): v for k, v in indexers.items()}
+            # convert to tuple of slices
+            idx = tuple(
+                real_indexers.get(i, slice(None)) for i in range(self.data.ndim)
+            )
+            return self.data[idx].numpy(force=True)  # type: ignore [no-any-return]
 
     @classmethod
     def supports(cls, obj: Any) -> TypeGuard[torch.Tensor]: