Contributing to DoWhy
DoWhy is a PyWhy community project and welcomes contributions.
There are multiple ways to contribute to DoWhy. Here are some examples:
Adding a Jupyter notebook that describes the use of DoWhy for solving causal problems.
Helping update the documentation for DoWhy.
Helping implement a new method for any of the four steps of causal analysis: model, identify, estimate, refute
Integrating DoWhy’s API with external implementations for any of the four steps, so that external libraries can be called seamlessly from the identify_effect, estimate_effect or refute_estimate methods.
Helping extend the DoWhy API so that we can support new functionality like interpretability of the estimate, counterfactual prediction and more.
If you would like to contribute, you can raise a pull request, see Contributing code for more info. If you have questions before contributing, you can start by opening an issue on Github.