sqlalchemy-pydantic-mapper library for mapping SQLAlchemy models to Pydantic
Project description
sqlalchemy-pydantic-mapper
sqlalchemy-pydantic-mapper simplifies converting SQLAlchemy instances (subclasses of sqlalchemy.orm.DeclarativeBase) into Pydantic models (pydantic.BaseModel).
It supports:
- registering custom synchronous and asynchronous mappers;
- registration via decorator or by passing
func=directly; - automatic mapping via Pydantic if the model has
model_config = ConfigDict(from_attributes=True); map(...)— an async method returning the target Pydantic model instance (mustawaitit);map_each(...)— an async method returning the sequence of target Pydantic model instances, calls target func for every ORM model (mustawaitit);map_bulk(...)— an async method returning a list of mapped Pydantic model instances from a sequence of SQLAlchemy objects(mustawaitit).
Usage Examples (Full Code Snippets)
- Simple registration via
func=and checking_mappers:
from sqlalchemy_pydantic_mapper import ObjectMapper
def mapper(db: UserDB) -> UserSchema:
return UserSchema(id=db.id, name=db.name)
ObjectMapper.register(UserDB, UserSchema, func=mapper)
assert ObjectMapper._mappers_single[UserDB][UserSchema] is mapper
- Registration via decorator:
@ObjectMapper.register(UserDB, UserSchema)
def mapper2(db: UserDB) -> UserSchema:
return UserSchema(id=db.id, name=db.name)
- Async mapper (registration + usage):
@ObjectMapper.register(UserDB, UserSchema)
async def async_mapper(db: UserDB) -> UserSchema:
# e.g., async call or await something
return UserSchema(id=db.id, name=db.name.upper())
import asyncio
async def main():
user = UserDB()
user.id = 1
user.name = "alice"
res = await ObjectMapper.map(user, UserSchema)
print(res) # UserSchema(id=1, name='ALICE')
asyncio.run(main())
- Auto-mapping via Pydantic (
from_attributes=True):
class UserSchema(BaseModel):
model_config = ConfigDict(from_attributes=True)
id: int
name: str
If no custom mapper is registered for the from_class -> to_class pair, ObjectMapper.map(instance, UserSchema) automatically calls:
UserSchema.model_validate(instance, from_attributes=True)
- Example in a test (synthetic):
async def test_auto_mapping():
stud = StudentDB()
stud.id = 2
stud.name = "Bob"
result = await ObjectMapper.map(stud, UserSchema)
assert result.id == 2
assert result.name == "Bob"
- Example for manual mapping (different names / logic):
def stud_to_studschema(db: StudentDB) -> StudSchema:
return StudSchema(id=db.id, name=db.name)
ObjectMapper.register(StudentDB, StudSchema, func=stud_to_studschema)
- Mapping multiple objects with
map_many
users = [UserDB(id=1, name="Alice"), UserDB(id=2, name="Bob")]
# Synchronous mapper
def mapper(db: UserDB) -> UserSchema:
return UserSchema(id=db.id, name=db.name)
ObjectMapper.register(UserDB, UserSchema, func=mapper)
import asyncio
async def main():
results = await ObjectMapper.map_each(users, UserSchema)
print(results)
# [UserSchema(id=1, name='Alice'), UserSchema(id=2, name='Bob')]
asyncio.run(main())
- Passing additional arguments to a mapper function
def mapper_with_prefix(db: UserDB, prefix: str) -> UserSchema:
return UserSchema(id=db.id, name=f"{prefix}{db.name}")
# Register mapper with a closure to pass extra arguments
ObjectMapper.register(UserDB, UserSchema, func=lambda db: mapper_with_prefix(db, prefix="Mr. "))
user = UserDB(id=1, name="Alice")
import asyncio
async def main():
result = await ObjectMapper.map(user, UserSchema)
print(result) # UserSchema(id=1, name='Mr. Alice')
asyncio.run(main())
- Re-registering a mapper (overwriting)
# Original mapper
ObjectMapper.register(UserDB, UserSchema, func=lambda db: UserSchema(id=db.id, name=db.name))
# Re-register with a new logic
ObjectMapper.register(UserDB, UserSchema,
func=lambda db: UserSchema(id=db.id, name=db.name.upper()),
override_existing=True)
user = UserDB(id=2, name="Bob")
import asyncio
async def main():
result = await ObjectMapper.map(user, UserSchema)
print(result) # UserSchema(id=2, name='BOB')
asyncio.run(main())
- Async mapper with
map_each
async def async_mapper(db: UserDB) -> UserSchema:
import asyncio
await asyncio.sleep(0.01)
return UserSchema(id=db.id, name=db.name.upper())
ObjectMapper.register(UserDB, UserSchema, func=async_mapper)
users = [UserDB(id=1, name="Alice"), UserDB(id=2, name="Bob")]
async def main():
results = await ObjectMapper.map_each(users, UserSchema)
print(results)
# [UserSchema(id=1, name='ALICE'), UserSchema(id=2, name='BOB')]
asyncio.run(main())
- Async mapper with
map_bulk- True bulk operation under all the sequence at once
async def async_mapper(dbs: Sequence[UserDB]) -> Sequence[UserSchema]:
import asyncio
await asyncio.sleep(0.01)
return [UserSchema(id=db.id, name=db.name.upper()) for db in dbs]
ObjectMapper.register_bulk(UserDB, UserSchema, func=async_mapper)
users = [UserDB(id=1, name="Alice"), UserDB(id=2, name="Bob")]
async def main():
results = await ObjectMapper.map_bulk(users, UserSchema)
print(results)
# [UserSchema(id=1, name='ALICE'), UserSchema(id=2, name='BOB')]
asyncio.run(main())
Errors and Behavior on Incorrect Usage
TypeErroriffrom_does not inheritDeclarativeBase:
class NotABase: pass
ObjectMapper.register(NotABase, UserSchema) # -> TypeError
TypeErrorifto_does not inheritBaseModel:
class NotABaseModel: pass
ObjectMapper.register(UserDB, NotABaseModel) # -> TypeError
ValueErroriffuncis missing andto_does not havemodel_config = ConfigDict(from_attributes=True):
class BadSchema(BaseModel):
id: int
name: str
ObjectMapper.register(UserDB, BadSchema) # -> ValueError
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