Affiliated Projects

NumFOCUS Affiliated Projects are focused on open source data science, make meaningful use of NumFOCUS-sponsored tools, have an active community of contributors, and have a Code of Conduct, either adopted from our own or similar in spirit. Affiliated Projects are not fiscally sponsored by NumFOCUS.

We highlight affiliated projects to encourage the community to contribute to, promote, and support these open source tools!

Affiliated Projects enjoy a number of benefits. If your project is interested in becoming a NumFOCUS Affiliated Project, click here to learn more.


ArviZ is a Python package for exploratory analysis of Bayesian models. Includes functions for posterior analysis, sample diagnostics, model checking, and comparison.

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The goal is to provide backend-agnostic tools for diagnostics and visualizations of Bayesian inference in Python, by first converting inference data into xarray objects. See here for more on xarray and ArviZ.


Chainer is a powerful, flexible and intuitive deep learning framework. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.

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Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures. Forward computation can include any control flow sta