Add a test github workflow

Author: thomasZen

.github/workflows/unit-tests.yml

@@ -0,0 +1,33 @@
+name: Unit Tests
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  unit-tests:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.10"
+      
+      - name: Install uv
+        run: |
+          curl -LsSf https://astral.sh/uv/install.sh | sh
+          echo "${HOME}/.local/bin" >> $GITHUB_PATH
+
+      - name: Install openretina with dependencies
+        run: |
+          uv sync --extra dev
+          uv pip install pytest
+
+      - name: Run Unit Tests
+        run: make test-unittests

tests/test_data.py

@@ -1,12 +1,15 @@
+import pytest
 import numpy as np
 
 from gcl_classifier.data import load_data, prepare_baden_data
 
 
 class TestDataLoader:
 
-    def test_model_load(self, force_download=True):
-        """Test that data downloads without errors."""
+
+    @pytest.mark.parametrize("force_download", [True, False])
+    def test_data_load(self, force_download: bool):
+        """Test that data downloads without errors with both force_download options."""
         data = load_data(force_download=force_download)
         assert data is not None
         assert isinstance(data, dict)
@@ -17,9 +20,6 @@ def test_model_load(self, force_download=True):
         assert isinstance(data['bar_feats'], np.ndarray)
         assert isinstance(data['chirp_feats'], np.ndarray)
 
-    def test_model_load_from_cache(self):
-        self.test_model_load(force_download=False)
-
     def test_extract_baden_data(self):
         """Test that data extracts without errors."""
         data = load_data(force_download=False)

tests/test_model.py

@@ -1,4 +1,4 @@
-from gcl_classifier.model import load_model
+from gcl_classifier.model import load_model, get_model
 
 
 class TestModelLoader:
@@ -10,18 +10,18 @@ def test_model_download(self):
 
     def test_model_load(self):
         """Test that model loads without errors."""
-        model, model_dict = load_model(force_download=False)
+        model = get_model()
         assert model is not None
 
     def test_model_type(self):
         """Test that loaded model is correct type."""
         from sklearn.calibration import CalibratedClassifierCV
-        model, model_dict = load_model(force_download=False)
+        model = get_model()
         assert isinstance(model, CalibratedClassifierCV)
 
     def test_model_has_predict_methods(self):
         """Test that model has required methods."""
-        model, model_dict = load_model(force_download=False)
+        model = get_model()
         assert hasattr(model, 'predict')
         assert hasattr(model, 'predict_proba')
         assert callable(model.predict)