Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/code-specialist/database-setup-tools
Easy to understand and use python tools that help you to create databases and interact with them
https://github.com/code-specialist/database-setup-tools
database database-connector database-management fastapi fastapi-sqlalchemy sqlalchemy sqlalchemy-python sqlmodel
Last synced: about 2 months ago
JSON representation
Easy to understand and use python tools that help you to create databases and interact with them
- Host: GitHub
- URL: https://github.com/code-specialist/database-setup-tools
- Owner: code-specialist
- License: mit
- Created: 2022-11-20T14:15:06.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-08T08:23:19.000Z (9 months ago)
- Last Synced: 2024-05-08T09:29:39.374Z (9 months ago)
- Topics: database, database-connector, database-management, fastapi, fastapi-sqlalchemy, sqlalchemy, sqlalchemy-python, sqlmodel
- Language: Python
- Homepage:
- Size: 239 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Database Setup Tools for SQLModel / SQLAlchemy
[](https://github.com/code-specialist/database-setup-tools/actions/workflows/github-code-scanning/codeql)
[](https://github.com/code-specialist/database-setup-tools/actions/workflows/test.yaml)
Simplified database lifecycle and session management based on [SQLModel](https://sqlmodel.tiangolo.com/) / [SQLAlchemy](https://www.sqlalchemy.org/).
Any contributions are welcome! But we only accept pull requests that come with tests.
## Installation
```bash
pip install database-setup-tools
```
## Features
- **Database creation on app startup**
- Thread-safe database **session manager**
- Opinionated towards `SQLModel` but feasible with any other framework or pure `sqlalchemy`
- Easily use a local database in your tests
## Usage
In order to use this library, you need some SQLModel or SQLAlchemy tables and a URI to connect to your database.
With this in place, the `DatabaseSetup` instance can be created - which contains all provided tools and also automatically
creates the database including all tables.
```python
from sqlmodel import Field, SQLModel
from database_setup_tools import DatabaseSetup
class User(SQLModel, table=True):
""" User database entity / table """
id: int = Field(index=True, primary_key=True)
name: str
# create database & tables, establish connection with session pool
database_setup = DatabaseSetup(
model_metadata = SQLModel.metadata,
database_uri="postgresql+psycopg2://postgres:postgres@localhost:5432/database",
)
```
> Note: The `DatabaseSetup` class acts as singleton, so if you create multiple instances with the same
> set of parameters, you will always get the same instance back instead of creating a new one.
After the setup is created, you can get a scoped session via the provided session manager and use it
for database transactions.
```python
# get scoped session
session = next(database_setup.session_manager.get_session())
# do stuff in session
user = User(name="Alice")
session.add(user)
session.commit()
```
The `DatabaseSetup` instance also provides lifecycle methods allowing to manually control the database:
```python
database_setup.create_database()
database_setup.drop_database()
```
## Development
### Testing
1. Spin up databases for local integration tests: `docker-compose -f tests/docker-compose.yaml up -d`
1. Create virtual environment & install dependencies: `poetry install`
1. Run tests: `poetry run pytest`