  DoubleML is an open-source Python library implementing the double machine
learning framework of Chernozhukov et al. (2018) for a variety of causal
models. It contains functionalities for valid statistical inference on causal
parameters when the estimation of nuisance parameters is based on machine
learning methods. The object-oriented implementation of DoubleML provides a
high flexibility in terms of model specifications and makes it easily
extendable. The package is distributed under the MIT license and relies on core
libraries from the scientific Python ecosystem: scikit-learn, numpy, pandas,
scipy, statsmodels and joblib. Source code, documentation and an extensive user
guide can be found at https://github.com/DoubleML/doubleml-for-py and
https://docs.doubleml.org.
