Supabase Pydantic Schemas

A project for generating Pydantic and SQLAlchemy models from Supabase and MySQL databases. This tool bridges the gap between your database schema and your Python code, providing type-safe models for FastAPI and other frameworks.

Currently, this is ideal for integrating FastAPI with supabase-py as a primary use-case. This project is inspired by the TS type generating capabilities of supabase cli. Its aim is to provide a similar experience for Python developers.

Project status (August 2026): maintenance mode. supabase-pydantic continues to receive bug fixes and dependency updates; nothing is being removed, and no end-of-life date has been set. New feature work has moved to castiron, its successor, which carries this project's schema-fidelity engine onto a source-agnostic architecture.

castiron is 0.1.0 and pre-alpha: today it reads the OpenAPI document a Supabase/PostgREST project publishes — no database connection, no driver — and emits Pydantic v2 models. It does not yet connect to a live database, emit SQLAlchemy models, read MySQL, or generate seed data, all of which supabase-pydantic does today. If you rely on those, stay here for now.

Install with pip install cast-iron (the distribution is hyphenated; the command and the import package are castiron). Docs · Repo · What this means for supabase-pydantic users

📣 NEW (Aug 2025): MySQL support! Generate models directly from MySQL databases with the --db-type mysql flag. See the docs

📣 NEW (Aug 2025): SQLAlchemy models with Insert and Update variants for better type safety. Learn more

Installation

# Install with pip
$ pip install supabase-pydantic

# Or with conda
$ conda install -c conda-forge supabase-pydantic

Configuration

Create a .env file with your database connection details:

DB_NAME=<your_db_name>
DB_USER=<your_db_user>
DB_PASS=<your_db_password>
DB_HOST=<your_db_host>
DB_PORT=<your_db_port>

Usage

Generate Pydantic Models

Example with full command output (using a local connection):

$ sb-pydantic gen --type pydantic --framework fastapi --local

2025-08-18 15:47:42 - INFO - supabase_pydantic.db.connection:check_connection:72 - PostGres connection is open.
2025-08-18 15:47:42 - INFO - supabase_pydantic.db.connection:construct_tables:136 - Processing schema: public
2025-08-18 15:47:42 - INFO - supabase_pydantic.db.connection:__exit__:105 - PostGres connection is closed.
2025-08-18 15:47:42 - INFO - supabase_pydantic.cli.commands.gen:gen:239 - Generating Pydantic models...
2025-08-18 15:47:42 - INFO - supabase_pydantic.cli.commands.gen:gen:251 - Pydantic models generated successfully for schema 'public': /path/to/your/project/entities/fastapi/schema_public_latest.py
2025-08-18 15:47:42 - INFO - supabase_pydantic.cli.commands.gen:gen:258 - File formatted successfully: /path/to/your/project/entities/fastapi/schema_public_latest.py

Common Commands

Using a database URL:

$ sb-pydantic gen --type pydantic --framework fastapi --db-url postgresql://postgres:postgres@127.0.0.1:54322/postgres

Generating models for specific schemas:

$ sb-pydantic gen --type pydantic --framework fastapi --local --schema extensions --schema auth

Generate SQLAlchemy models:

$ sb-pydantic gen --type sqlalchemy --local

Using MySQL:

$ sb-pydantic gen --type pydantic --framework fastapi --db-type mysql --db-url mysql://user:pass@localhost:3306/dbname

Makefile Integration

# Makefile examples for both Pydantic and SQLAlchemy generation

gen-pydantic:
    @echo "Generating FastAPI Pydantic models..."
    @sb-pydantic gen --type pydantic --framework fastapi --dir ./entities/fastapi --local

gen-sqlalchemy:
    @echo "Generating SQLAlchemy ORM models..."
    @sb-pydantic gen --type sqlalchemy --dir ./entities/sqlalchemy --local

# Generate all model types at once
gen-all: gen-pydantic gen-sqlalchemy
    @echo "All models generated successfully."

For full documentation, visit our docs site.