Causality Python Packages

causallib

A Python package for modular causal inference analysis and model evaluations

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

causal-learn

Causal Discovery in Python. Learning causality from data.

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

eliot

Eliot: the logging system that tells you *why* it happened

scikit-uplift

:exclamation: uplift modeling in scikit-learn style in python :snake:

lingam

Python package for causal discovery based on LiNGAM.

cdt

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

gcastle

Trustworthy AI related projects

syntheticcontrolmethods

A Python package for causal inference using Synthetic Controls

dependence-forecastability

Forecastability triage for time series using AMI, pAMI, and covariate-aware dependence diagnostics before expensive model search.

pyphi

A toolbox for integrated information theory.

causalegm

CausalEGM: an encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies

causetrace

Causal traceability for AI agent runtimes — observe, replay, understand agent behavior

causallift

CausalLift: Python package for causality-based Uplift Modeling in real-world business

pybbn

Inference in Bayesian Belief Networks using Probability Propagation in Trees of Clusters (PPTC) and Gibbs sampling

causeinfer

Machine learning based causal inference/uplift in Python

copent

Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python

ylearn

YLearn, a pun of "learn why", is a python package for causal inference

babino2020masks

Code used in https://arxiv.org/abs/2006.05532

pytrad

Causal Discovery in Python. Learning causality from data.

pywhy-graphs

[Experimental] Causal graphs that are networkx-compliant for the py-why ecosystem.

nonlincausality

Python package for Granger causality test with nonlinear (neural networks) forecasting methods.

avici

Amortized Inference for Causal Structure Learning