CRUD operations on nested SQLAlchemy ORM-models using Pydantic
Project description
sqlalchemy-pydantic-orm
This library makes it a lot easier to do nested database operation with SQLAlchemy. With this library it is for example possible to validate, convert, and upload a 100-level deep nested JSON (dict) to its corresponding tables in a given database, within 3 lines of code.
Pydantic is used for creating the
dataclass and validating it. Pydantic already has a function called
.from_orm()
that can do a nested get operation, but it only supports ORM -> Pydantic and
not Pydantic -> ORM. That's exactly where this library fills in, with 2
specific functions .orm_create()
and .orm_update()
, and one general
function .to_orm()
that combines the functionality of the first 2, calling
one or the other, depending on if there is an id provided.
Requirements
- Python 3.8+
- SQLAlchemy 1.4+
- Pydantic 1.8+
Installation
$ pip install sqlalchemy-pydantic-orm
To tinker with the code yourself, install the full dependencies with:
$ pip install sqlalchemy-pydantic-orm[dev]
Useful references
- https://pydantic-docs.helpmanual.io/usage/models/
- https://fastapi.tiangolo.com/tutorial/sql-databases/
Examples
Below 1 example is provided (more coming).
For a bigger and more detailed example you can look at the /examples/ folder.
Example 1 - Using manual created schemas
Create your own Pydantic schemas and link them to the SQLAlchemy ORM-models.
Create your SQLAlchemy ORM-models (one-to-one or one-to-many)
class Parent(Base):
id = Column(Integer, primary_key=True, index=True, nullable=False)
name = Column(String, nullable=False)
car = relationship("Car", cascade="all, delete", uselist=False, back_populates="owner")
children = relationship("Child", cascade="all, delete")
class Car(Base):
id = Column(Integer, primary_key=True, index=True, nullable=False)
color = Column(String, nullable=False)
owner_id = Column(Integer, ForeignKey("parents.id"), nullable=False)
owner = relationship("Parent", back_populates="car")
class Child(Base):
id = Column(Integer, primary_key=True, index=True, nullable=False)
name = Column(String, nullable=False)
parent_id = Column(Integer, ForeignKey("parents.id"), nullable=False)
Create your Pydantic base and CRUD schemas using these ORM models, and the imported ORMBaseSchema
Base schemas
from sqlalchemy_pydantic_orm import ORMBaseSchema
from .models import Parent, Car, Child
class ParentBase(ORMBaseSchema):
name: str
_orm_model = PrivateAttr(Parent)
class CarBase(ORMBaseSchema):
color: str
_orm_model = PrivateAttr(models.Car)
class ChildBase(ORMBaseSchema):
name: str
_orm_model = PrivateAttr(models.Child)
GET schemas
class Parent(ParentBase):
id: int
children: List[Child]
car: Car
class Car(CarBase):
id: int
class Child(ChildBase):
id: int
CREATE/UPDATE schemas
class ParentCreate(ParentBase):
id: Optional[int]
children: List[ChildCreate]
car: CarCreate
class CarCreate(CarBase):
id: Optional[int]
class ChildCreate(ChildBase):
id: Optional[int]
Use your schemas to do nested CRUD operations.
with ConnectionDatabase() as db:
create_schema = schemas.ParentCreate.parse_obj(create_dict)
parent_db = create_schema.orm_create()
db.add(parent_db)
db.commit()
db_create_schema = schemas.Parent.from_orm(parent_db)
print(db_create_schema.dict())
update_schema = schemas.ParentUpdate.parse_obj(update_dict)
update_schema.to_orm(db)
db.commit()
db_update_schema = schemas.Parent.orm_update(parent_db)
print(db_update_schema.dict())
Note: with .orm_create()
you have to call db.add()
before calling db.commit()
.
With orm_update you give the db session as parameter,
and you only have to call db.commit()
.
Example 2 - Using generated schemas
TODO: Integrate with https://github.com/tiangolo/pydantic-sqlalchemy
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