• Stars
    star
    13,694
  • Rank 2,236 (Top 0.05 %)
  • Language
    Python
  • License
    MIT License
  • Created over 3 years ago
  • Updated 5 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

SQL databases in Python, designed for simplicity, compatibility, and robustness.

SQLModel

SQLModel, SQL databases in Python, designed for simplicity, compatibility, and robustness.

Test Publish Coverage Package version


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.

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 (right now, Python supports versions 3.6 and above).

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.

More Repositories

1

fastapi

FastAPI framework, high performance, easy to learn, fast to code, ready for production
Python
73,897
star
2

full-stack-fastapi-template

Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.
TypeScript
24,890
star
3

typer

Typer, build great CLIs. Easy to code. Based on Python type hints.
Python
14,943
star
4

uwsgi-nginx-flask-docker

Docker image with uWSGI and Nginx for Flask applications in Python running in a single container.
Python
2,986
star
5

uvicorn-gunicorn-fastapi-docker

Docker image with Uvicorn managed by Gunicorn for high-performance FastAPI web applications in Python with performance auto-tuning.
Python
2,699
star
6

asyncer

Asyncer, async and await, focused on developer experience.
Python
1,517
star
7

pydantic-sqlalchemy

Tools to convert SQLAlchemy models to Pydantic models
Python
1,173
star
8

nginx-rtmp-docker

Docker image with Nginx using the nginx-rtmp-module module for live multimedia (video) streaming.
Dockerfile
1,110
star
9

dockerswarm.rocks

Docker Swarm mode rocks! Ideas, tools and recipes. Get a production-ready, distributed, HTTPS served, cluster in minutes, not weeks.
Python
1,093
star
10

uwsgi-nginx-docker

Docker image with uWSGI and Nginx for applications in Python (as Flask) in a single container.
Python
646
star
11

uvicorn-gunicorn-docker

Docker image with Uvicorn managed by Gunicorn for high-performance web applications in Python with performance auto-tuning.
Python
628
star
12

full-stack

Full stack, modern web application generator. Using Flask, PostgreSQL DB, Docker, Swagger, automatic HTTPS and more.
Python
523
star
13

meinheld-gunicorn-flask-docker

Docker image with Meinheld and Gunicorn for Flask applications in Python.
Python
486
star
14

full-stack-fastapi-couchbase

Full stack, modern web application generator. Using FastAPI, Couchbase as database, Docker, automatic HTTPS and more.
Python
440
star
15

typer-cli

Run Typer scripts with completion, without having to create a package, using Typer CLI.
Python
367
star
16

poetry-version-plugin

Poetry plugin for dynamically extracting the package version from a __version__ variable or a Git tag.
Python
361
star
17

fastapi-cli

Run and manage FastAPI apps from the command line with FastAPI CLI. 🚀
Python
287
star
18

blog-posts

Blog posts and related code by Sebastián Ramírez (@tiangolo)
Python
273
star
19

uvicorn-gunicorn-starlette-docker

Docker image with Uvicorn managed by Gunicorn for high-performance Starlette web applications in Python with performance auto-tuning.
Python
182
star
20

latest-changes

A GitHub Action to add latest changes after each PR merged automatically
Python
172
star
21

babun-docker

Use Docker Toolbox with Babun (Cygwin) in Windows
Shell
170
star
22

meinheld-gunicorn-docker

Docker image with Meinheld managed by Gunicorn for high-performance WSGI (Flask, Django, etc) web applications in Python with performance auto-tuning.
Python
165
star
23

docker-with-compose

Docker image with Docker Compose installed for CI.
Shell
158
star
24

node-frontend

Instrutctions to buid a frontend Docker image built with Node.js and then served with Nginx. Previously a Docker image.
Dockerfile
137
star
25

flask-frontend-docker

Minimal project generator with a Flask backend, a modern frontend (Vue, React or Angular), a Traefik load balancer with HTTPS, all based on Docker.
Vue
130
star
26

python-machine-learning-docker

Docker image with Python 3.6 and 3.7 using Conda, with CUDA variants. To serve as base image for Machine Learning projects.
Dockerfile
84
star
27

uvicorn-gunicorn-machine-learning-docker

Docker image for high-performance Machine Learning web applications. With Uvicorn managed by Gunicorn in Python 3.7 and 3.6, using Conda, with CUDA and TensorFlow variants.
Python
67
star
28

issue-manager

Automatically close issues that have a label, after a custom delay, if no one replies back.
Python
62
star
29

full-stack-flask-couchbase

Full stack, modern web application generator. Using Flask, Couchbase as database, Docker, Swagger, automatic HTTPS and more.
Python
59
star
30

label-approved

Label a Pull Request after a number of approvals
Python
34
star
31

full-stack-flask-couchdb

Full stack, modern web application generator. Using Flask, CouchDB as database, Docker, Swagger, automatic HTTPS and more.
Python
31
star
32

tiangolo

16
star
33

github-actions-sandbox

Not useful for you. It's just a sandbox GitHub repo for me to try out stuff and develop GitHub Actions.
Python
16
star
34

tiangolo.com

Python
16
star
35

docker-auto-labels

Generate each Docker constraint label in random nodes in the cluster.
Python
15
star
36

angular-docker-multi-stage-example

Angular in Docker with Nginx, supporting environments, built with multi-stage Docker builds
15
star
37

ngx-http-client

Angular (4.3+) HttpClientModule with parameter encodings compatible with back ends (Node.js, Python, PHP, etc)
TypeScript
11
star
38

compose-to-rancher

Convert Docker Compose V2 to Rancher compatible Docker Compose V1
Python
10
star
39

markdown-include-variants

Markdown extension to expand directives to include source example files to also include their variants. Only useful to tiangolo's projets. Don't use it. 😅
Python
9
star
40

wunderlist2csv

Convert from Wunderlist backup json file to a CSV file importable by TaskCoach
Python
6
star
41

anaconda_cluster_install

Automatically Install Anaconda Python in a cluster of machines, for a specified user.
Shell
5
star
42

bitbucket_issues_to_redmine_csv

Python
3
star