renaming

image_prediction/estimator/adapter/adapters/mock.py

@@ -1,7 +1,7 @@
 from image_prediction.estimator.adapter.adapter import EstimatorAdapter
 
 
-class DummyEstimator:
+class EstimatorMock:
     @staticmethod
     def predict(batch):
         return [None for _ in batch]

test/unit_tests/conftest.py

@@ -7,12 +7,12 @@ from PIL import Image
 from image_prediction.classifier.classifier import Classifier
 from image_prediction.classifier.image_classifier import ImageClassifier
 from image_prediction.estimator.adapter.adapters.keras import KerasEstimatorAdapter
-from image_prediction.estimator.adapter.adapters.mock import DummyEstimator, EstimatorAdapterMock
+from image_prediction.estimator.adapter.adapters.mock import EstimatorMock, EstimatorAdapterMock
 from image_prediction.exceptions import UnknownEstimatorAdapter
 
 
 @pytest.fixture
-def predictor(classifier, monkeypatch, expected_predictions):
+def image_classifier(classifier, monkeypatch, expected_predictions):
     return ImageClassifier(classifier)
 
 
@@ -25,7 +25,7 @@ def classifier(estimator_adapter, classes):
 @pytest.fixture
 def estimator_adapter(estimator_type, keras_model, output_batch_generator, monkeypatch):
     if estimator_type == "mock":
-        estimator_adapter = EstimatorAdapterMock(DummyEstimator())
+        estimator_adapter = EstimatorAdapterMock(EstimatorMock())
     elif estimator_type == "keras":
         estimator_adapter = KerasEstimatorAdapter(keras_model)
     else:

test/unit_tests/image_classifier_test.py

@@ -5,8 +5,8 @@ from image_prediction.utils import chunk_iterable
 
 @pytest.mark.parametrize("estimator_type", ["mock", "keras"])
 @pytest.mark.parametrize("batch_size", [0, 1, 2, 16, 32, 64])
-def test_predict(predictor, images, expected_predictions):
-    predictions = list(predictor.predict(images))
+def test_predict(image_classifier, images, expected_predictions):
+    predictions = list(image_classifier.predict(images))
     assert predictions == expected_predictions