SQL Types

Custom type decorators for SQLModel/SQLAlchemy with Pydantic validation

Installation

pip install sqltypes

Quick Start

from typing import Sequence
from pydantic import BaseModel
from sqlmodel import Field, SQLModel
from sqltypes import ValidatedJSON, SpaceDelimitedList

class User(BaseModel):
    name: str
    age: int

class Article(SQLModel, table=True):
    id: int | None = Field(default=None, primary_key=True)
    tags: Sequence[str] = Field(sa_type=SpaceDelimitedList)
    author: User = Field(sa_type=ValidatedJSON(User))

Available Types

ValidatedJSON(T, name?)

Stores any Pydantic model or complex type as JSON with automatic validation.

config: Config = Field(sa_type=ValidatedJSON(Config))

SpaceDelimitedList

Stores sequences as space-delimited strings.

tags: Sequence[str] = Field(sa_type=SpaceDelimitedList)
# Database: "python sql database"
# Python: ["python", "sql", "database"]

ValidatedStr(LiteralType)

Validates strings against Pydantic literal types.

from typing import Literal
Status = Literal["pending", "active", "completed"]
status: Status = Field(sa_type=ValidatedStr(Status))

Custom Types

Use CustomTypeMeta to create your own types:

from sqltypes import CustomTypeMeta
from sqlalchemy.types import String

CommaSeparatedList = CustomTypeMeta(
    'CommaSeparatedList',
    (), {},
    Impl=String,
    dump=lambda lst: ','.join(lst),
    parse=lambda s: s.split(',')
)

Or use CustomStringMeta for string-based types:

from sqltypes import CustomStringMeta

class CommaSeparatedList(metaclass=CustomStringMeta,
                          dump=lambda lst: ','.join(lst),
                          parse=lambda s: s.split(',')):
    ...

Links

• PyPI: https://pypi.org/project/sqltypes/
• Repository: https://github.com/marciclabas/sqltypes