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. (See all supported types here)
- Extensible to arbitrary custom SQLAlchemy types.
- Automatic batching of queries, avoiding N+1 queries when getting relationships
- Support for SQLAlchemy >=1.4.x
- 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, ForeignKey, Integer, String
from sqlalchemy.ext.declarative import
8000
declarative_base
from sqlalchemy.orm import relationship
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:
# In another file
# ...
import strawberry
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):
# This db.session was created with sqlalchemy.orm.sessionmaker(...)
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:
| SQLAlchemy Type | Strawberry Equivalent | Notes |
|---|---|---|
Integer |
int |
|
Float |
float |
|
BigInteger |
BigInt |
|
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 |
JSON |
JSON |
SQLAlchemy JSON |
Enum |
enum.Enum |
The Python enum that the column is mapped to must be decorated with@strawberry.enum (strawberry enum docs) |
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.
If your association_proxy does not follow the expected form, you should add it to __exclude__ to prevent an exception from being raised.
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:
# models.py
from sqlalchemy import Column
Base = declarative_base()
class Book(Base):
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:
passWe 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
For more details on how to contribute, as well as how to setup the project on your local machine, please refer to the contributing docs
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
Don't forget to tell your contributors to also install and use pre-commit.
💡 Tip: You can also use our DevContainer setup for a fully configured development environment, including pre-commit, Python, PostgreSQL, and all required dependencies. This is the fastest way to get started.
pip install -r requirements.txtInstall PostgreSQL 14+
pytest
