Fix tempfile bug for Windows (#83)

* Run CI also for Windows

* Attempt to fix bug

* Skip model tests for windows

* Attempt to fix model tests for Windows

* Print times

* Remove potential fix

* Attempt to fix timestamp issue

* Attempt proper fix

* Clean up fix

Author: wesselb

.github/workflows/ci.yaml

@@ -8,18 +8,19 @@ on:
 
 jobs:
   test:
-    runs-on: ubuntu-latest
     strategy:
       fail-fast: false
       matrix:
         version: ["3.10", "3.11"]
+        os: [ubuntu-latest, windows-latest]
 
-    name: Test with Python ${{ matrix.version }}
+    runs-on: ${{ matrix.os }}
+    name: Test with Python ${{ matrix.version }} (${{ matrix.os }})
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
 
       - name: Set up Python ${{ matrix.version }}
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.version }}
 

aurora/foundry/common/channel.py

@@ -229,22 +229,26 @@ def _download_blob(self, blob_name: str, file_path: str) -> None:
 
     def _send(self, batch: Batch, name: str) -> None:
         with tempfile.NamedTemporaryFile() as tf:
+            tf.close()  # We will only use the name.
             batch.to_netcdf(tf.name)
             self._upload_blob(tf.name, name)
 
     def _receive(self, name: str) -> Batch:
         with tempfile.NamedTemporaryFile() as tf:
+            tf.close()  # We will only use the name.
             self._download_blob(name, tf.name)
             return Batch.from_netcdf(tf.name)
 
     def _write(self, data: bytes, name: str) -> None:
         with tempfile.NamedTemporaryFile() as tf:
+            tf.close()  # We will only use the name.
             with open(tf.name, "wb") as f:
                 f.write(data)
             self._upload_blob(tf.name, name)
 
     def _read(self, name: str) -> bytes:
         with tempfile.NamedTemporaryFile() as tf:
+            tf.close()  # We will only use the name.
             self._download_blob(name, tf.name)
             with open(tf.name, "rb") as f:
                 return f.read()

aurora/foundry/demo/interactive.py

@@ -29,6 +29,8 @@ def variable_to_urldata(variable: xr.DataArray, cmap: str, vmin: float, vmax: fl
     field = np.concatenate((field[:, ~first_half], field[:, first_half]), axis=1)
 
     with tempfile.NamedTemporaryFile(suffix=".png") as tf:
+        tf.close()  # We will only use the name.
+
         # Make the image that will be overlayed.
         fig = plt.figure()
         ax = fig.add_subplot(projection=ccrs.PlateCarree(), frameon=False)
@@ -63,6 +65,8 @@ def interactive_plot(prediction: Batch, width: str = "1000px", height: str = "50
     )
 
     with tempfile.NamedTemporaryFile(suffix=".nc") as tf:
+        tf.close()  # We will only use the name.
+
         prediction.to_netcdf(tf.name)
         ds = xr.load_dataset(tf.name).isel(batch=0, history=0, time=0)
         dt = ds.time.values.astype("datetime64[s]").tolist()

tests/conftest.py

@@ -1,5 +1,6 @@
 """Copyright (c) Microsoft Corporation. Licensed under the MIT license."""
 
+import os
 import pickle
 from datetime import datetime
 from typing import Generator, TypedDict
@@ -49,6 +50,25 @@ def test_input_output() -> Generator[tuple[Batch, SavedBatch], None, None]:
     with open(path, "rb") as f:
         static_vars: dict[str, np.ndarray] = pickle.load(f)
 
+    # Load test output.
+    path = hf_hub_download(
+        repo_id="microsoft/aurora",
+        filename="aurora-0.25-small-pretrained-test-output.pickle",
+    )
+    with open(path, "rb") as f:
+        test_output: SavedBatch = pickle.load(f)
+
+    # We unfortunately used a time in 1950. Windows cannot produce timestamps for `datetime`s before
+    # 1970. We fix this below.
+    if os.name == "nt":
+
+        class PatchedDateTime(datetime):
+            def timestamp(self) -> float:
+                # This is the value of `datetime(1950, 1, 1, 6, 0).timestamp()` on Linux.
+                return -631134000.0
+
+        test_input["metadata"]["time"] = [PatchedDateTime(1950, 1, 1, 6, 0)]
+
     static_vars = {
         k: interpolate_numpy(
             v,
@@ -73,12 +93,4 @@ def test_input_output() -> Generator[tuple[Batch, SavedBatch], None, None]:
         ),
     )
 
-    # Load test output.
-    path = hf_hub_download(
-        repo_id="microsoft/aurora",
-        filename="aurora-0.25-small-pretrained-test-output.pickle",
-    )
-    with open(path, "rb") as f:
-        test_output: SavedBatch = pickle.load(f)
-
     yield batch, test_output