
* ✨ Add UUID support from sqlalchemy 2.0 update * ⚰️ Remove dead code for GUID old support * 📝 Add documentation for UUIDs * 🧪 Add test for UUIDs field definition and support * 🎨 [pre-commit.ci] Auto format from pre-commit.com hooks * ✏️ Fix prerequisites docs for uuid * ♻️ Update UUID source examples for consistency Keep consistency with other examples, functions without parameters, and printing info that shows and explains the UUID results (and can also be tested later) * 📝 Add source examples for selecting UUIDs with session.get() * 📝 Re-structure UUID docs * Explain the concepts at the beggining before using them. * Explain how UUIDs can be used and trusted. * Explain why UUIDs could be generated on the code, and how they can be used for distributed systems. * Explain how UUIDs can prevent information leakage. * Warn about UUIDs storage size. * Explain that uuid is part of the standard library. * Explain how default_factory works. * Explain that creating an instance would generate a new UUID, before it is sent to the DB. This is included and shown in the example, the UUID is printed before saving to the DB. * Remove sections about other operations that would behave the same as other fields and don't need additional info from what was explained in previous chapters. * Add two examples to select using UUIDs, similar to the previous ones, mainly to be able to use them in the tests and ensure that it all works, even when SQLite stores the values as strings but the where() or the session.get() receive UUID values (ensure SQLAlchemy does the conversion correctly for SQLite). * Add an example terminal run of the code, with comments. * Simplify the ending to keep only the information that wasn't there before, just the "Learn More" with links. * ✅ Refactor tests with new printed code, extract and check that UUIDs are used in the right places. * ✅ Add tests for the new extra UUID examples, for session.get() * 🎨 [pre-commit.ci] Auto format from pre-commit.com hooks * 📝 Rename variable in example for Python 3.7+ for consistency with 3.10+ (I missed that change before) --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Sebastián Ramírez <tiangolo@gmail.com>
SQLModel, SQL databases in Python, designed for simplicity, compatibility, and robustness.
Documentation: https://sqlmodel.tiangolo.com
Source Code: https://github.com/tiangolo/sqlmodel
SQLModel is a library for interacting with SQL databases from Python code, with Python objects. It is designed to be intuitive, easy to use, highly compatible, and robust.
SQLModel is based on Python type annotations, and powered by Pydantic and SQLAlchemy.
The key features are:
- Intuitive to write: Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs.
- Easy to use: It has sensible defaults and does a lot of work underneath to simplify the code you write.
- Compatible: It is designed to be compatible with FastAPI, Pydantic, and SQLAlchemy.
- Extensible: You have all the power of SQLAlchemy and Pydantic underneath.
- Short: Minimize code duplication. A single type annotation does a lot of work. No need to duplicate models in SQLAlchemy and Pydantic.
Sponsors
SQL Databases in FastAPI
SQLModel is designed to simplify interacting with SQL databases in FastAPI applications, it was created by the same author. 😁
It combines SQLAlchemy and Pydantic and tries to simplify the code you write as much as possible, allowing you to reduce the code duplication to a minimum, but while getting the best developer experience possible.
SQLModel is, in fact, a thin layer on top of Pydantic and SQLAlchemy, carefully designed to be compatible with both.
Requirements
A recent and currently supported version of Python.
As SQLModel is based on Pydantic and SQLAlchemy, it requires them. They will be automatically installed when you install SQLModel.
Installation
$ pip install sqlmodel
---> 100%
Successfully installed sqlmodel
Example
For an introduction to databases, SQL, and everything else, see the SQLModel documentation.
Here's a quick example. ✨
A SQL Table
Imagine you have a SQL table called hero
with:
id
name
secret_name
age
And you want it to have this data:
id | name | secret_name | age |
---|---|---|---|
1 | Deadpond | Dive Wilson | null |
2 | Spider-Boy | Pedro Parqueador | null |
3 | Rusty-Man | Tommy Sharp | 48 |
Create a SQLModel Model
Then you could create a SQLModel model like this:
from typing import Optional
from sqlmodel import Field, SQLModel
class Hero(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
name: str
secret_name: str
age: Optional[int] = None
That class Hero
is a SQLModel model, the equivalent of a SQL table in Python code.
And each of those class attributes is equivalent to each table column.
Create Rows
Then you could create each row of the table as an instance of the model:
hero_1 = Hero(name="Deadpond", secret_name="Dive Wilson")
hero_2 = Hero(name="Spider-Boy", secret_name="Pedro Parqueador")
hero_3 = Hero(name="Rusty-Man", secret_name="Tommy Sharp", age=48)
This way, you can use conventional Python code with classes and instances that represent tables and rows, and that way communicate with the SQL database.
Editor Support
Everything is designed for you to get the best developer experience possible, with the best editor support.
Including autocompletion:

And inline errors:

Write to the Database
You can learn a lot more about SQLModel by quickly following the tutorial, but if you need a taste right now of how to put all that together and save to the database, you can do this:
from typing import Optional
from sqlmodel import Field, Session, SQLModel, create_engine
class Hero(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
name: str
secret_name: str
age: Optional[int] = None
hero_1 = Hero(name="Deadpond", secret_name="Dive Wilson")
hero_2 = Hero(name="Spider-Boy", secret_name="Pedro Parqueador")
hero_3 = Hero(name="Rusty-Man", secret_name="Tommy Sharp", age=48)
engine = create_engine("sqlite:///database.db")
SQLModel.metadata.create_all(engine)
with Session(engine) as session:
session.add(hero_1)
session.add(hero_2)
session.add(hero_3)
session.commit()
That will save a SQLite database with the 3 heroes.
Select from the Database
Then you could write queries to select from that same database, for example with:
from typing import Optional
from sqlmodel import Field, Session, SQLModel, create_engine, select
class Hero(SQLModel, table=True):
id: Optional[int] = Field(default=None, primary_key=True)
name: str
secret_name: str
age: Optional[int] = None
engine = create_engine("sqlite:///database.db")
with Session(engine) as session:
statement = select(Hero).where(Hero.name == "Spider-Boy")
hero = session.exec(statement).first()
print(hero)
Editor Support Everywhere
SQLModel was carefully designed to give you the best developer experience and editor support, even after selecting data from the database:

SQLAlchemy and Pydantic
That class Hero
is a SQLModel model.
But at the same time, ✨ it is a SQLAlchemy model ✨. So, you can combine it and use it with other SQLAlchemy models, or you could easily migrate applications with SQLAlchemy to SQLModel.
And at the same time, ✨ it is also a Pydantic model ✨. You can use inheritance with it to define all your data models while avoiding code duplication. That makes it very easy to use with FastAPI.
License
This project is licensed under the terms of the MIT license.