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# ayx-learn
A foundation of [scikit-learn](https://scikit-learn.org/stable/) compatible data science tools, such as Transformers, that both Alteryx Assisted Modeling and Code Fee ML Tools are built on.
## Source code organization
` . ├── README.md ├── ayx_learn: Source code for the ayx_learn package. │ ├── classifiers: Classifiers source code. │ ├── regressors: Regressors source code. │ ├── transformers: Transformer source code. │ └── utils: Utility functions, such as validation. ├── docs: Sphinx documentation. ├── requirements-dev.txt: Requirements for development env. ├── requirements.txt: Requirements for building and running in a production env. ├── setup.py ├── tests │ └── unit: pytest unit tests. └── tox.ini: Ini file for tox. `
## Code standards
ayx-learn follows the [Alteryx Python Code Standards](https://alteryx.quip.com/qR3kAG4OA32X/Python-Code-Standards)
## Testing
Unit tests are written using [pytest](https://docs.pytest.org/) and are located in ./tests/unit.
[tox](https://tox.readthedocs.io/) can be used for creating a virtualenv and automatically running the pytest unit tests.
## Documentation
ayx-learn follows the [Alteryx Python Documentation Standards](https://alteryx.quip.com/bFgiAZThHaJv/Python-Documentation-Standards).
See [README](docs/README.md).
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