pyphi VS causallift

What are some alternatives?

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.

causalml - Uplift modeling and causal inference with machine learning algorithms

NeuroTS - Topological Neuron Synthesis

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.

alibi - Algorithms for explaining machine learning models

CARLA - CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms

dodiscover - [Experimental] Global causal discovery algorithms

cdci-causality - Python implementation of CDCI, a method to identify causal direction between two variables

pysyncon - A python module for the synthetic control method