iris_classification_lambda / tests /test_classifier.py
Clement Vachet
Use list of features as direct input
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import pytest
from classification.classifier import Classifier
@pytest.fixture
def setup_pipeline():
pipeline = Classifier()
pipeline.train_and_save()
return pipeline
@pytest.fixture
def requests():
return {
"features": [
[6.5, 3.0, 5.8, 2.2],
[6.1, 2.8, 4.7, 1.2]
]
}
@pytest.fixture
def response():
return ["virginica", "versicolor"]
def test_response(setup_pipeline, requests, response):
assert response == setup_pipeline.load_and_test(requests["features"])["predictions"]