sqlalchemy restrictions on HF

App/database.py

@@ -17,18 +17,17 @@ IS_PYTEST = "pytest" in os.getenv("PYTHONPATH", "") or os.getenv("PYTEST_CURRENT
 IS_HF = os.getenv("SPACE_ID") is not None # Hugging Face 
 
 SKIP_DB = IS_CI or IS_PYTEST or IS_HF or not SQLALCHEMY_AVAILABLE
-
-DB_USER = os.getenv("DB_USER", "postgres")
-DB_PASSWORD = os.getenv("DB_PASSWORD", "password")
-DB_HOST = os.getenv("DB_HOST", "localhost")
-DB_PORT = os.getenv("DB_PORT", "5432")
-DB_NAME = os.getenv("DB_NAME", "test_db")
-
-DATABASE_URL = (f"postgresql+psycopg2://{DB_USER}:{DB_PASSWORD}"f"@{DB_HOST}:{DB_PORT}/{DB_NAME}")
-
 Base = declarative_base() if SQLALCHEMY_AVAILABLE else None
 
 if not SKIP_DB:
+    DB_USER = os.getenv("DB_USER", "postgres")
+    DB_PASSWORD = os.getenv("DB_PASSWORD", "password")
+    DB_HOST = os.getenv("DB_HOST", "localhost")
+    DB_PORT = os.getenv("DB_PORT", "5432")
+    DB_NAME = os.getenv("DB_NAME", "test_db")
+
+    DATABASE_URL = (f"postgresql+psycopg2://{DB_USER}:{DB_PASSWORD}"f"@{DB_HOST}:{DB_PORT}/{DB_NAME}")
+
     engine = create_engine(DATABASE_URL)
     SessionLocal = sessionmaker(autocommit = False, autoflush = False, bind = engine)
 

App/model.py

@@ -1,51 +1,56 @@
-from sqlalchemy import Column, Integer, String, Float, Boolean, DateTime, ForeignKey
-from sqlalchemy.sql import func
-from App.database import Base
+from App.database import Base, SQLALCHEMY_AVAILABLE
 
-class Input(Base):
-    __tablename__ = "inputs"
+if SQLALCHEMY_AVAILABLE: 
+    from sqlalchemy import Column, Integer, String, Float, Boolean, DateTime, ForeignKey 
+    from sqlalchemy.sql import func
 
-    id = Column(Integer, primary_key=True, index=True)
-    genre = Column(String)
-    statut_marital = Column(String)
-    departement = Column(String)
-    poste = Column(String)
-    domaine_etude = Column(String)
-    frequence_deplacement = Column(String)
-    heure_supplementaires = Column(Boolean)
-    evolution_cat_evol = Column(String)
-    categorie_employe = Column(String)
-    satisfaction_employee_nature_travail = Column(Integer)
-    nombre_participation_pee = Column(Integer)
-    ecart_note_evaluation = Column(Integer)
-    revenu_mensuel = Column(Integer)
-    distance_domicile_travail = Column(Integer)
-    satisfaction_globale = Column(Float)
-    niveau_education = Column(Integer)
-    note_evaluation_actuelle = Column(Integer)
-    satisfaction_employee_equipe = Column(Integer)
-    age = Column(Integer)
-    revenu_par_annee_experience_interne = Column(Integer)
-    satisfaction_employee_equilibre_pro_perso = Column(Integer)
-    nombre_experiences_precedentes = Column(Integer)
-    annees_dans_l_entreprise = Column(Integer)
-    nb_formations_suivies = Column(Integer)
-    revenu_par_annee_experience_totale = Column(Integer)
-    ratio_sans_promotion = Column(Integer)
-    satisfaction_employee_environnement = Column(Integer)
-    exp_hors_entreprise = Column(Integer)
-    mobilite_promotion = Column(Integer)
-    annees_depuis_la_derniere_promotion = Column(Integer)
+    class Input(Base):
+        __tablename__ = "inputs"
 
-    created_at = Column(DateTime(timezone=True), server_default=func.now())
+        id = Column(Integer, primary_key=True, index=True)
+        genre = Column(String)
+        statut_marital = Column(String)
+        departement = Column(String)
+        poste = Column(String)
+        domaine_etude = Column(String)
+        frequence_deplacement = Column(String)
+        heure_supplementaires = Column(Boolean)
+        evolution_cat_evol = Column(String)
+        categorie_employe = Column(String)
+        satisfaction_employee_nature_travail = Column(Integer)
+        nombre_participation_pee = Column(Integer)
+        ecart_note_evaluation = Column(Integer)
+        revenu_mensuel = Column(Integer)
+        distance_domicile_travail = Column(Integer)
+        satisfaction_globale = Column(Float)
+        niveau_education = Column(Integer)
+        note_evaluation_actuelle = Column(Integer)
+        satisfaction_employee_equipe = Column(Integer)
+        age = Column(Integer)
+        revenu_par_annee_experience_interne = Column(Integer)
+        satisfaction_employee_equilibre_pro_perso = Column(Integer)
+        nombre_experiences_precedentes = Column(Integer)
+        annees_dans_l_entreprise = Column(Integer)
+        nb_formations_suivies = Column(Integer)
+        revenu_par_annee_experience_totale = Column(Integer)
+        ratio_sans_promotion = Column(Integer)
+        satisfaction_employee_environnement = Column(Integer)
+        exp_hors_entreprise = Column(Integer)
+        mobilite_promotion = Column(Integer)
+        annees_depuis_la_derniere_promotion = Column(Integer)
 
-class Predictions(Base):
-    __tablename__ = "predictions"
-    id = Column(Integer, primary_key=True, index=True)
-    input_id = Column(Integer, ForeignKey("inputs.id"))
+        created_at = Column(DateTime(timezone=True), server_default=func.now())
 
-    prediction_label = Column(String)
-    prediction_proba = Column(Float)
-    model_version = Column(String)
+    class Predictions(Base):
+        __tablename__ = "predictions"
+        id = Column(Integer, primary_key=True, index=True)
+        input_id = Column(Integer, ForeignKey("inputs.id"))
 
-    created_at = Column(DateTime(timezone=True), server_default=func.now())
+        prediction_label = Column(String)
+        prediction_proba = Column(Float)
+        model_version = Column(String)
+
+        created_at = Column(DateTime(timezone=True), server_default=func.now())
+else: 
+    Input = None 
+    Predictions = None

App/predict.py

@@ -9,12 +9,15 @@ from huggingface_hub import hf_hub_download
 # Import SQLAlchemy uniquement si disponible 
 try: 
     from sqlalchemy.orm import Session 
+    from App.database import SessionLocal 
+    from App.model import Input, Predictions
     SQLALCHEMY_AVAILABLE = True 
 except ModuleNotFoundError: 
     SQLALCHEMY_AVAILABLE = False 
+    essionLocal = None 
+    Input = None 
+    Predictions = None
     
-from App.database import SessionLocal 
-from App.model import Input, Predictions
 
 MODEL_REPO = "Diaure/xgb_model"