Often times, when building an application, it is handy to create some seed data with which to use and test how parts of your application will work. When this dataset is small, a python script works just fine, but as that data set (and number of different data models) grow, this approach becomes quite cumbersome.
Foundry is an tool designed to make this easier, by allowing you to orgainze this data in a data friendly format, YAML. All data that is imported is defined by a key in the YAML file, and Foundry acts as a proxy to fetch these objects for you from the datastore. This also allows the user to specify relations by referencing these keys to other objects.
Inside a virtualenv run
pip install foundry
from foundry import Foundry
from models import Crew, Ship
foundry = Foundry([('crew.yml', Crew), ('ship.yml', Ship)])
foundry.load()
zoidberg = foundry['zoidberg']
Then, in your app root path, create a directory foundry/data and create the two files crew.yml and ship.yml. See the tests for a more thorough example.
- Add an Example to README.md
- Expand support for other backend datastores
If anything on the TODO list looks like something you'd like to take on, go ahead and fork the project and submit a Pull Request. For other features, please first open an issue proposing the feature/change.
To hack on foundry, make sure to install the development requirements in your virtual environment.
pip install -r dev_requirements.txt
Pull Requests should include tests covering the changes/features being proposed. To run the test suite, simply run:
nosetests
#LICENSE MIT License
Copyright (C) 2014 by Erik Taubeneck
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