89 lines
2.6 KiB
Python
89 lines
2.6 KiB
Python
"""
|
|
Database connection and session management for the ML service.
|
|
|
|
This module provides SQLAlchemy engine and session setup for PostgreSQL.
|
|
Environment variables control the connection parameters.
|
|
"""
|
|
|
|
import os
|
|
from contextlib import contextmanager
|
|
from typing import Generator
|
|
|
|
from sqlalchemy import create_engine, Column, Integer, String, DateTime, JSON
|
|
from sqlalchemy.ext.declarative import declarative_base
|
|
from sqlalchemy.orm import sessionmaker, Session
|
|
from sqlalchemy.sql import func
|
|
|
|
|
|
# Database connection configuration from environment
|
|
DATABASE_URL = os.getenv("DATABASE_URL")
|
|
if not DATABASE_URL:
|
|
raise RuntimeError(
|
|
"DATABASE_URL environment variable is required. "
|
|
"Please set it to a valid PostgreSQL connection string."
|
|
)
|
|
|
|
# Create SQLAlchemy engine
|
|
engine = create_engine(
|
|
DATABASE_URL,
|
|
pool_pre_ping=True, # Verify connections before using them
|
|
pool_size=5, # Number of connections to maintain
|
|
max_overflow=10, # Max connections beyond pool_size
|
|
)
|
|
|
|
# Create session factory
|
|
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
|
|
|
|
# Base class for declarative models
|
|
Base = declarative_base()
|
|
|
|
|
|
# Training runs model
|
|
class TrainingRun(Base):
|
|
"""Model for tracking ML training runs."""
|
|
|
|
__tablename__ = "training_runs"
|
|
|
|
id = Column(Integer, primary_key=True, index=True)
|
|
run_id = Column(String(255), unique=True, nullable=False, index=True)
|
|
model_type = Column(String(100), nullable=False)
|
|
experiment_name = Column(String(255), nullable=False, index=True)
|
|
pipeline_config_hash = Column(String(64), nullable=False)
|
|
dataset_version = Column(String(100))
|
|
metrics_summary = Column(JSON)
|
|
status = Column(String(50), nullable=False, default="running", index=True)
|
|
created_at = Column(DateTime(timezone=True), server_default=func.now(), index=True)
|
|
completed_at = Column(DateTime(timezone=True))
|
|
|
|
def __repr__(self):
|
|
return f"<TrainingRun(run_id='{self.run_id}', status='{self.status}')>"
|
|
|
|
|
|
def init_db():
|
|
"""
|
|
Initialize the database schema.
|
|
Creates all tables defined by Base.metadata.
|
|
"""
|
|
Base.metadata.create_all(bind=engine)
|
|
|
|
|
|
@contextmanager
|
|
def get_db() -> Generator[Session, None, None]:
|
|
"""
|
|
Context manager for database sessions.
|
|
|
|
Usage:
|
|
with get_db() as db:
|
|
# Use db session here
|
|
training_run = TrainingRun(run_id="123", ...)
|
|
db.add(training_run)
|
|
db.commit()
|
|
|
|
Yields:
|
|
Database session
|
|
"""
|
|
db = SessionLocal()
|
|
try:
|
|
yield db
|
|
finally:
|
|
db.close()
|