# Causal Discovery Toolbox: Uncovering causal relationships in Python

Diviyan Kalainathan, Olivier Goudet, Ritik Dutta.

Year: 2020, Volume: 21, Issue: 37, Pages: 1−5

#### Abstract

This paper presents a new open source Python framework for causal discovery from observational data and domain background knowledge, aimed at causal graph and causal mechanism modeling. The cdt package implements an end-to-end approach, recovering the direct dependencies (the skeleton of the causal graph) and the causal relationships between variables. It includes algorithms from the Bnlearn' and Pcalg' packages, together with algorithms for pairwise causal discovery such as ANM.