This fork is a heavily modified version of strawberry-sqlalchemy-mapper with the following additions/changes:
- Implements relay pagination (using this sqlakeyset fork)
- Fully async
- Uses SQLAlchmy 2.0 style
- Pydantic integration (generated types can also be pydantic models)
Strawberry-sqlalchemy-mapper is the simplest way to implement autogenerated strawberry types for columns and relationships in SQLAlchemy models.
-
Instead of manually listing every column and relationship in a SQLAlchemy model, strawberry-sqlalchemy-mapper lets you decorate a class declaration and it will automatically generate the necessary strawberry fields for all columns and relationships (subject to the limitations below) in the given model.
-
Native support for most of SQLAlchemy's most common types.
-
Extensible to arbitrary custom SQLAlchemy types.
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Automatic batching of queries, avoiding N+1 queries when getting relationships
-
Support for SQLAlchemy >=1.4.x
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Lightweight and fast.
strawberry-sqlalchemy-mapper is available on PyPi
pip install strawberry-sqlalchemy-mapper
First, define your sqlalchemy model:
# models.py
from sqlalchemy import Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base
Base = declarative_base()
class Employee(Base):
__tablename__ = 'employee'
id = Column(UUID, primary_key=True)
name = Column(String, nullable=False)
password_hash = Column(String, nullable=False)
department_id = Column(UUID, ForeignKey('department.id'))
department = relationship('Department', back_populates='employees')
class Department(Base):
__tablename__ = "department"
id = Column(UUID, primary_key=True)
name = Column(String, nullable=False)
employees = relationship('Employee', back_populates='department')
Next, decorate a type with strawberry_sqlalchemy_mapper.type()
to register it as a strawberry type for the given SQLAlchemy model.
This will automatically add fields for the model's columns, relationships, association proxies,
and hybrid properties. For example:
# elsewhere
# ...
from strawberry_sqlalchemy_mapper import StrawberrySQLAlchemyMapper
strawberry_sqlalchemy_mapper = StrawberrySQLAlchemyMapper()
@strawberry_sqlalchemy_mapper.type(models.Employee)
class Employee:
__exclude__ = ["password_hash"]
@strawberry_sqlalchemy_mapper.type(models.Department)
class Department:
pass
@strawberry.type
class Query:
@strawberry.field
def departments(self):
return db.session.scalars(select(models.Department)).all()
# context is expected to have an instance of StrawberrySQLAlchemyLoader
class CustomGraphQLView(GraphQLView):
def get_context(self):
return {
"sqlalchemy_loader": StrawberrySQLAlchemyLoader(bind=YOUR_SESSION),
}
# call finalize() before using the schema:
# (note that models that are related to models that are in the schema
# are automatically mapped at this stage -- e.g., Department is mapped
# because employee.department is a relationshp to Department)
strawberry_sqlalchemy_mapper.finalize()
# only needed if you have polymorphic types
additional_types = list(strawberry_sqlalchemy_mapper.mapped_types.values())
schema = strawberry.Schema(
query=Query,
mutation=Mutation,
extensions=extensions,
types=additional_types,
)
# You can now query, e.g.:
"""
query {
departments {
id
name
employees {
edge {
node {
id
name
department {
# Just an example of nested relationships
id
name
}
}
}
}
}
}
"""
SQLAlchemy Models -> Strawberry Types and Interfaces are expected to have a consistent
(customizable) naming convention. These can be configured by passing model_to_type_name
and model_to_interface_name
when constructing the mapper.
Natively supports the following SQLAlchemy types:
Integer: int,
Float: float,
BigInteger: int,
Numeric: Decimal,
DateTime: datetime,
Date: date,
Time: time,
String: str,
Text: str,
Boolean: bool,
Unicode: str,
UnicodeText: str,
SmallInteger: int,
SQLAlchemyUUID: uuid.UUID,
VARCHAR: str,
ARRAY[T]: List[T] # PostgreSQL array
Enum: (the Python enum it is mapped to, which should be @strawberry.enum-decorated)
Additional types can be supported by passing extra_sqlalchemy_type_to_strawberry_type_map
,
although support for TypeDecorator
types is untested.
Association proxies are expected to be of the form association_proxy('relationship1', 'relationship2')
,
i.e., both properties are expected to be relationships.
Roots of polymorphic hierarchies are supported, but are also expected to be registered via
strawberry_sqlalchemy_mapper.interface()
, and its concrete type and
its descendants are expected to inherit from the interface:
class Book(Model):
id = Column(UUID, primary_key=True)
class Novel(Book):
pass
class ShortStory(Book):
pass
# in another file
strawberry_sqlalchemy_mapper = StrawberrySQLAlchemyMapper()
@strawberry_sqlalchemy_mapper.interface(models.Book)
class BookInterface:
pass
@strawberry_sqlalchemy_mapper.type(models.Book)
class Book:
pass
@strawberry_sqlalchemy_mapper.type(models.Novel)
class Novel:
pass
@strawberry_sqlalchemy_mapper.type(models.ShortStory)
class ShortStory:
pass
We encourage you to contribute to strawberry-sqlalchemy-mapper! Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (git checkout -b feature)
- Commit your Changes (git commit -m 'Add some feature')
- Push to the Branch (git push origin feature)
- Open a Pull Request
This project uses pre-commit
_, please make sure to install it before making any
changes::
pip install pre-commit
cd strawberry-sqlalchemy-mapper
pre-commit install
It is a good idea to update the hooks to the latest version::
pre-commit autoupdate
Don't forget to tell your contributors to also install and use pre-commit.
pip install -r requirements.txt
pytest