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SQLAlchemy's Base Class:

• In SQLAlchemy, the Base class is part of the Declarative Base system, which is used to define database models (tables) as Python classes.
• It is created using sqlalchemy.ext.declarative.declarative_base().
• Example:

  from sqlalchemy.ext.declarative import declarative_base
  
  Base = declarative_base()
  
  class User(Base):
      __tablename__ = 'users'
      id = Column(Integer, primary_key=True)
      name = Column(String)
  

Pydantic's BaseModel Class:

• In Pydantic, the BaseModel class is used to define data models for validation, parsing, and serialization.
• It is part of Pydantic's core functionality and is not related to databases or ORM.
• Example:

  from pydantic import BaseModel
  
  class UserCreate(BaseModel):
      name: str
      email: str
  

Key Differences:

Can They Be Used Together?

Yes, SQLAlchemy's Base and Pydantic's BaseModel can be used together in applications like FastAPI:

• SQLAlchemy handles database interactions.
• Pydantic handles data validation and serialization for APIs.

Example:

from fastapi import FastAPI
from pydantic import BaseModel
from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker

# SQLAlchemy setup
DATABASE_URL = "sqlite:///./test.db"
engine = create_engine(DATABASE_URL)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
Base = declarative_base()  # SQLAlchemy's Base

# SQLAlchemy model
class User(Base):
    __tablename__ = "users"
    id = Column(Integer, primary_key=True, index=True)
    name = Column(String)
    email = Column(String)

# Pydantic model
class UserCreate(BaseModel):  # Pydantic's BaseModel
    name: str
    email: str

class UserResponse(BaseModel):
    id: int
    name: str
    email: str

    class Config:
        orm_mode = True  # Allows Pydantic to work with SQLAlchemy ORM objects

# FastAPI app
app = FastAPI()

@app.post("/users/", response_model=UserResponse)
def create_user(user: UserCreate):
    db_user = User(name=user.name, email=user.email)  # SQLAlchemy model
    db = SessionLocal()
    db.add(db_user)
    db.commit()
    db.refresh(db_user)
    return db_user  # Pydantic serializes the SQLAlchemy object

Key Points:

1. SQLAlchemy's Base is for defining database models.
2. Pydantic's BaseModel is for validating and serializing data.
3. They are independent but can be integrated in applications like FastAPI.

Conclusion:

SQLAlchemy does not use Pydantic's BaseModel under the hood. They are separate tools with distinct roles, but they can be combined effectively in modern Python applications.

Connections:

• SQLAlchemy
• PyDantic

Sources:

• From: SQLAlchemy