EconML
Estimate causal effects with ML
For Developers
You can get started by cloning this repository. We use setuptools (opens in new tab) for building and distributing our package. We rely on some recent features of setuptools, so make sure to upgrade to a recent version with pip install setuptools --upgrade. Then from your local copy of the repository you can run python setup.py develop to get started.
Running the Tests
This project uses pytest (opens in new tab) for testing. To run tests locally after installing the package, you can use python setup.py pytest.
Generating the documentation
This project’s documentation is generated via Sphinx (opens in new tab). Note that we use graphviz (opens in new tab)‘s dot application to produce some of the images in our documentation, so you should make sure that dot is installed and in your path.
To generate a local copy of the documentation from a clone of this repository, just run python setup.py build_sphinx -W -E -a, which will build the documentation and place it under the build/sphinx/html path.
The reStructuredText files that make up the documentation are stored in the docs directory (opens in new tab); module documentation is automatically generated by the Sphinx build process.
Enviroment
The econml package works on macOS, Windows, and Linux, and supports Python versions 3.5-3.7. The econml package relies on numpy, scipy, and scikit-learn for most of its underlying numerical computation and machine learning routines, and uses keras for the components built on deep neural networks. If you don’t already have these dependencies installed locally, then installing the econml package from PyPI via pip will also install them.