test: Add unit and integration tests with Pytest

pytest.ini

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+[pytest]
+addopts = -v --cov=app --cov-report=term-missing
+testpaths = tests
+python_files = test_*.py

tests/test_api.py

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+import pytest
+from fastapi.testclient import TestClient
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+from sqlalchemy.pool import StaticPool
+
+from app.main import app
+from app.core.database import Base, get_db
+from app.core.config import settings
+
+# Setup in-memory SQLite database for testing
+SQLALCHEMY_DATABASE_URL = "sqlite:///:memory:"
+
+engine = create_engine(
+    SQLALCHEMY_DATABASE_URL,
+    connect_args={"check_same_thread": False},
+    poolclass=StaticPool,
+)
+TestingSessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
+
+def override_get_db():
+    try:
+        db = TestingSessionLocal()
+        yield db
+    finally:
+        db.close()
+
+app.dependency_overrides[get_db] = override_get_db
+
+client = TestClient(app)
+
+@pytest.fixture(scope="module")
+def test_db():
+    # Create tables
+    Base.metadata.create_all(bind=engine)
+    yield
+    # Drop tables
+    Base.metadata.drop_all(bind=engine)
+
+def test_health_check():
+    response = client.get("/health")
+    assert response.status_code == 200
+    assert response.json() == {"status": "healthy"}
+
+def test_predict_unauthorized():
+    response = client.post("/predict", json={})
+    assert response.status_code == 422
+
+def test_predict_invalid_key():
+    response = client.post("/predict", headers={"X-API-KEY": "wrong_key"}, json={})
+    assert response.status_code == 401
+
+def test_predict_success(test_db):
+    # Valid input data based on updated schema
+    payload = {
+        "age": 30,
+        "genre": "M",
+        "revenu_mensuel": 5000,
+        "statut_marital": "Célibataire",
+        "departement": "R&D",
+        "poste": "Ingénieur",
+        "nombre_experiences_precedentes": 2,
+        "nombre_heures_travailless": 40,
+        "annee_experience_totale": 5,
+        "annees_dans_l_entreprise": 2,
+        "annees_dans_le_poste_actuel": 1,
+        "satisfaction_employee_environnement": 3,
+        "note_evaluation_precedente": 3,
+        "niveau_hierarchique_poste": 2,
+        "satisfaction_employee_nature_travail": 3,
+        "satisfaction_employee_equipe": 4,
+        "satisfaction_employee_equilibre_pro_perso": 3,
+        "note_evaluation_actuelle": 3,
+        "heure_supplementaires": "Non",
+        "augementation_salaire_precedente": "10-15%",
+        "nombre_participation_pee": 0,
+        "nb_formations_suivies": 1,
+        "nombre_employee_sous_responsabilite": 0,
+        "distance_domicile_travail": 10,
+        "niveau_education": 3,
+        "domaine_etude": "Sciences",
+        "ayant_enfants": "Non",
+        "frequence_deplacement": "Rare",
+        "annees_depuis_la_derniere_promotion": 1,
+        "annes_sous_responsable_actuel": 1
+    }
+    
+    response = client.post(
+        "/predict", 
+        headers={"X-API-KEY": settings.API_KEY},
+        json=payload
+    )
+    
+    if response.status_code != 200:
+        print(f"Response error: {response.json()}")
+
+    assert response.status_code == 200
+    data = response.json()
+    assert "prediction" in data
+    assert "probability" in data
+    
+    # Verify DB insertion
+    db = TestingSessionLocal()
+    log = db.query(Base.metadata.tables["prediction_logs"]).first()
+    assert log is not None
+    assert log.age == 30
+    assert log.genre == "M"
+    db.close()

tests/test_unit.py

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+import pytest
+from app.models.schemas import InputSchema
+from app.services.ml_service import ml_service
+
+def test_input_schema_validation():
+    # Test valid data
+    valid_data = {
+        "age": 30,
+        "genre": "M",
+        "revenu_mensuel": 5000,
+        "statut_marital": "Célibataire",
+        "departement": "R&D",
+        "poste": "Ingénieur",
+        "nombre_experiences_precedentes": 2,
+        "nombre_heures_travailless": 40,
+        "annee_experience_totale": 5,
+        "annees_dans_l_entreprise": 2,
+        "annees_dans_le_poste_actuel": 1,
+        "satisfaction_employee_environnement": 3,
+        "note_evaluation_precedente": 3,
+        "niveau_hierarchique_poste": 2,
+        "satisfaction_employee_nature_travail": 3,
+        "satisfaction_employee_equipe": 4,
+        "satisfaction_employee_equilibre_pro_perso": 3,
+        "note_evaluation_actuelle": 3,
+        "heure_supplementaires": "Non",
+        "augementation_salaire_precedente": "10-15%",
+        "nombre_participation_pee": 0,
+        "nb_formations_suivies": 1,
+        "nombre_employee_sous_responsabilite": 0,
+        "distance_domicile_travail": 10,
+        "niveau_education": 3,
+        "domaine_etude": "Sciences",
+        "ayant_enfants": "Non",
+        "frequence_deplacement": "Rare",
+        "annees_depuis_la_derniere_promotion": 1,
+        "annes_sous_responsable_actuel": 1
+    }
+    schema = InputSchema(**valid_data)
+    assert schema.age == 30
+    assert schema.genre == "M"
+
+    # Test invalid data (missing field)
+    invalid_data = valid_data.copy()
+    del invalid_data["age"]
+    with pytest.raises(ValueError):
+        InputSchema(**invalid_data)
+
+def test_model_loading():
+    assert ml_service.model is not None
+    assert ml_service.expected_features is not None