Spaces:
Sleeping
Sleeping
File size: 2,717 Bytes
75c7c56 23dfad0 75c7c56 23dfad0 75c7c56 23dfad0 75c7c56 6bd73b3 75c7c56 6bd73b3 75c7c56 6bd73b3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | import pytest
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.db.models import Base, Prediction
from app.db.crud import log_prediction
from app.schemas.prediction import PredictionInput, PredictionOutput
VALID_INPUT = PredictionInput(
age=35, genre="M", statut_marital="Marié(e)", poste="Consultant",
domaine_etude="Infra & Cloud", niveau_education=3,
departement="Ventes", niveau_hierarchique_poste=2,
nombre_experiences_precedentes=2, annee_experience_totale=10,
annees_dans_l_entreprise=5, annees_dans_le_poste_actuel=2,
annees_sous_responsable_actuel=3, annees_depuis_la_derniere_promotion=1,
note_evaluation_actuelle=3, note_evaluation_precedente=3,
augmentation_salaire_precedente=15, nb_formations_suivies=2,
nombre_participation_pee=1, satisfaction_employee_environnement=3,
satisfaction_employee_nature_travail=4, satisfaction_employee_equipe=3,
satisfaction_employee_equilibre_pro_perso=2,
heure_supplementaires="Non", frequence_deplacement="Occasionnel",
distance_domicile_travail=10, revenu_mensuel=5000,
)
VALID_OUTPUT = PredictionOutput(prediction=0, label="Reste", probabilite=0.30)
@pytest.fixture
def db_session():
engine = create_engine("sqlite:///:memory:")
Base.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
session = Session()
yield session
session.close()
Base.metadata.drop_all(engine)
def test_log_prediction_creates_record(db_session):
record = log_prediction(db_session, VALID_INPUT, VALID_OUTPUT)
assert record.id is not None
assert record.prediction == 0
assert record.probabilite == 0.30
def test_log_prediction_is_retrievable(db_session):
log_prediction(db_session, VALID_INPUT, VALID_OUTPUT)
result = db_session.query(Prediction).first()
assert result is not None
assert result.age == 35
assert result.poste == "Consultant"
assert result.prediction == 0
def test_delete_prediction(db_session):
record = log_prediction(db_session, VALID_INPUT, VALID_OUTPUT)
record_id = record.id
db_session.delete(record)
db_session.commit()
result = db_session.get(Prediction, record_id)
assert result is None
def test_missing_required_field_raises_integrity_error(db_session):
from sqlalchemy.exc import IntegrityError
# On crée un Prediction en omettant le champ 'prediction' → NULL interdit
invalid_record = Prediction(
**VALID_INPUT.model_dump(),
probabilite=0.30,
# prediction= intentionnellement absent → None → violation NOT NULL
)
db_session.add(invalid_record)
with pytest.raises(IntegrityError):
db_session.commit()
|