Causal Models Python Packages

causallib

A Python package for modular causal inference analysis and model evaluations

pgmpy

Python Toolkit for Causal and Probabilistic Reasoning

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.

bnlearn

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

lingam

Python package for causal discovery based on LiNGAM.

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.

syntheticcontrolmethods

A Python package for causal inference using Synthetic Controls

pylift

Uplift modeling and evaluation library. Actively maintained pypi version.

torch-utilities

Simplifying audio and deep learning with PyTorch.

ylearn

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

esa-2scm

ESA-2SCM Python Package for Causal Discovery

tfce-mediation

Fast regression and mediation analysis of vertex or voxel MRI data with TFCE

actualcauses

Code for the python model `actualcauses` that implements algorithms for HP-causes identification.

dagsim

A framework and specification language for simulating data based on user-defined graphical models

pqp

High-performance causal identification in Rust.

tmi-viewer

Fast regression and mediation analysis of vertex or voxel MRI data with TFCE

scmopy

scmopy: Distribution-Agnostic Structural Causal Models Optimization in Python

cause2e

A package for end-to-end causal analysis

jupyterlab-dagitty

JupyterLab renderer of dagitty causal diagrams

causationentropy

Implementation of Causation Entropy from Clarkson Center for Complex Systems Science (C3S2)

iscan-dag

A Python 3 package for identifying distribution shifts (a.k.a feature-shifts) between datasets. Official implementation of the paper: "iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models".

pgmpy-rcr

A customized fork of pgmpy for RCR library compatibility

causalflows

Causal Normalizing flows in PyTorch