Tools to convert SQLAlchemy models to Pydantic models
MIT License
Tools to generate Pydantic models from SQLAlchemy models.
Still experimental.
SQLModel is a library that solves the same problem as this one, but in a much better way, also solving several other problems at the same time.
This project was to solve some simple use cases, to generate dynamic Pydantic models from SQLAlchemy models. But the result cannot be used very well in code as it doesn't have all the autocompletion and inline errors that a Pydantic model would have.
This was a very simple implementation, SQLModel is a much better solution, much better design and work behind it.
For most of the cases where you would use pydantic-sqlalchemy
, you should use SQLModel instead.
Quick example:
from typing import List
from pydantic_sqlalchemy import sqlalchemy_to_pydantic
from sqlalchemy import Column, ForeignKey, Integer, String, create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import Session, relationship, sessionmaker
Base = declarative_base()
engine = create_engine("sqlite://", echo=True)
class User(Base):
__tablename__ = "users"
id = Column(Integer, primary_key=True)
name = Column(String)
fullname = Column(String)
nickname = Column(String)
addresses = relationship(
"Address", back_populates="user", cascade="all, delete, delete-orphan"
)
class Address(Base):
__tablename__ = "addresses"
id = Column(Integer, primary_key=True)
email_address = Column(String, nullable=False)
user_id = Column(Integer, ForeignKey("users.id"))
user = relationship("User", back_populates="addresses")
PydanticUser = sqlalchemy_to_pydantic(User)
PydanticAddress = sqlalchemy_to_pydantic(Address)
class PydanticUserWithAddresses(PydanticUser):
addresses: List[PydanticAddress] = []
Base.metadata.create_all(engine)
LocalSession = sessionmaker(bind=engine)
db: Session = LocalSession()
ed_user = User(name="ed", fullname="Ed Jones", nickname="edsnickname")
address = Address(email_address="[email protected]")
address2 = Address(email_address="[email protected]")
ed_user.addresses = [address, address2]
db.add(ed_user)
db.commit()
def test_pydantic_sqlalchemy():
user = db.query(User).first()
pydantic_user = PydanticUser.from_orm(user)
data = pydantic_user.dict()
assert data == {
"fullname": "Ed Jones",
"id": 1,
"name": "ed",
"nickname": "edsnickname",
}
pydantic_user_with_addresses = PydanticUserWithAddresses.from_orm(user)
data = pydantic_user_with_addresses.dict()
assert data == {
"fullname": "Ed Jones",
"id": 1,
"name": "ed",
"nickname": "edsnickname",
"addresses": [
{"email_address": "[email protected]", "id": 1, "user_id": 1},
{"email_address": "[email protected]", "id": 2, "user_id": 1},
],
}
importlib-metadata
to 3.0.0. PR #22 by @tiangolo.importlib-metadata
to support the latest version 2.0.0
. PR #11.exclude
to exclude columns from Pydantic model. PR #3.config
. PR #1 by @pyropy.This project is licensed under the terms of the MIT license.