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```python # AI Dev Tool: FastAPI Pydantic v2 Micro-SaaS Boilerplate # Description: A production-ready FastAPI boilerplate with Pydantic v2 for building micro-SaaS applications from fastapi import FastAPI, HTTPException from pydantic import BaseModel, Field from typing import List, Optional from sqlalchemy import create_engine, Column, Integer, String from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker # Define the database connection SQLALCHEMY_DATABASE_URL = "postgresql://user:password@localhost/dbname" # Create a database engine engine = create_engine(SQLALCHEMY_DATABASE_URL) # Create a session maker SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine) # Create a base class for models Base = declarative_base() # Define a model for users class User(Base): """User model""" __tablename__ = "users" id = Column(Integer, primary_key=True) name = Column(String) email = Column(String, unique=True) # Create the database tables Base.metadata.create_all(engine) # Define a Pydantic model for user requests class UserRequest(BaseModel): """
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