semvec/pypi-packages huggingface dataset:
sqlsugar 0.1
Automatic migrations for SQLAlchemy
License: Apache License, Version 2.0
Requires Python: >=3.7

# SQLSugar - Automatic migrations for SQLAlchemy

[![PyPI](https://img.shields.io/pypi/v/sqlsugar.svg)](https://pypi.org/project/sqlsugar/)
[![Changelog](https://img.shields.io/github/v/release/Teemu/sqlsugar?include_prereleases&label=changelog)](https://github.com/Teemu/sqlsugar/releases)
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/Teemu/sqlsugar/blob/main/LICENSE)

This library is for you if you want to use a real database without spending time to generate migrations. This is experimental and you should switch to [Alembic](https://alembic.sqlalchemy.org/en/latest/) as your project matures. This only supports adding new tables, columns and indexes.

## Installation

Install this library using `pip`:

    pip install sqlsugar

## Usage

Look for examples with [SQLAlchemy](https://github.com/Teemu/sqlsugar/blob/main/examples/use_with_sqlalchemy.py) or [SQLModel](https://github.com/Teemu/sqlsugar/blob/main/examples/use_with_sqlmodel.py).

```python
from sqlsugar import migrate

migrate(engine.connect(), Base.metadata)
```

## How it works

We use Alembic to autogenerate the difference between the models you have defined with SQLAlchemy and the database. We then execute operations that create tables, add new columns or add new indexes. That is often all that's needed for rapid prototyping or running very small hobby projects.

However, we don't support renaming columns, dropping columns or removing tables. You should switch to using Alembic as your needs evolve. Alternatively, you can try running those migrations manually.

## Development

To contribute to this library, first checkout the code. Then create a new virtual environment:

    cd sqlsugar
    python -m venv .venv
    source .venv/bin/activate

Now install the dependencies and test dependencies:

    pip install -e '.[test]'
    pre-commit install

To run the tests:

    pytest