Causal Inference 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.

pgmpy

Python Toolkit for Causal and Probabilistic Reasoning

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.

rdrobust

Robust Local Polynomial Methods for RD designs

causalml

Uplift modeling and causal inference with machine learning algorithms

doubleml

DoubleML - Double Machine Learning in Python

diff-diff

Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.

scikit-uplift

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

lingam

Python package for causal discovery based on LiNGAM.

causalpy

A Python package for causal inference in quasi-experimental settings

morie

Multi-domain scientific computing toolkit hosting the MRM framework (Python + R).

tfcausalimpact

Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.

dqtlib

A Data Quality Tool that tells you what and surfaces the why

bsts-causalimpact

Bayesian CausalImpact for Python — R-compatible Gibbs sampler in Rust (PyO3), 30x faster, no TensorFlow

pytorch-tcn

(Realtime) Temporal Convolutions in PyTorch

cdt

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

y0

❓y0 (pronounced "why not?") is for causal inference in Python

gcastle

Trustworthy AI related projects

mini-causal

A Python package for measuring the impact of features

neuro-cortex-memory

Persistent memory for Claude Code — 41 neuroscience papers, 26 biological mechanisms with paper-bearing per-mechanism ablation evidence (E1 v3). LongMemEval R@10 98.4% / MRR 0.9124 (n=500). LoCoMo R@10 94.2% / MRR 0.8278 (n=1986). BEAM-10M +33.4% over flat retrieval. PostgreSQL + pgvector. Verified via 31-row two-benchmark ablation campaign.

pysyncon

A python module for the synthetic control method

moirais

Multi-domain scientific computing toolkit hosting the MRM framework (Python + R).