causallift VS dodiscover

What are some alternatives?

causalml - Uplift modeling and causal inference with machine learning algorithms

causal-learn - Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

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 Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

alibi - Algorithms for explaining machine learning models

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

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

pysyncon - A python module for the synthetic control method