We build diverse community that supports free and open Python tools for processing scientific data. We also build technical skills needed to contribute to open source and that support open science. Join our global community.

Peer review of Python software to support open science

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Python Package Peer Review

We offer peer review of Python software to increase the quality, usability and long term maintenance of the open source tools that drive open science. JOSS accepts our review as theirs so you can get the benefits of pyOpenSci and JOSS through one review.

> Learn more about the benefits of peer review.
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Community Partnerships

We partner with domain-specific scientific Python communities such as Pangeo who want to review affiliated packages. Through this collaboration, we develop community-specific standards that are used in our reviews to evaluate whether a package meets affiliation requirements. This removes the need for communities to develop their own peer review process.

> Learn About Community Partners
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Simplifying Packaging

We are creating a beginner-friendly, community-driven Python packaging guide. Our guide is reviewed by members of the Python Packaging Authority, maintainers of core packaging tools and members of the scientific Python community. It recommends best practices for you to follow when creating a Python package.

> Read our packaging guide

Building Diverse Community Around Python Scientific Software

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Peer review mentorship program

We are building diverse community around the scientific packages that drive open science. We recruit and support editors and reviewers from different backgrounds and gender-identities in each review that we perform.

Are you new to peer review? We offer a mentorship program for anyone interested in participating in peer review but who might like a bit of support.

New pyOpenSci contributors


Recent blog posts & updates

2024: A Transformative Year for pyOpenSci

2024 was a transformative year for pyOpenSci—but our mission has never been more important. In a time when access, equity, and sustainability in open science face challenges, we doubled down on our commitment to breaking down barriers. Through training, mentorship, and peer review, we expanded our community, created free educational resources, and empowered scientists worldwide. Here’s what we built together—and why it matters now more than ever.

QuadratiK: Collection of Methods Constructed using Kernel-Based Quadratic Distances

QuadratiK provides a set of goodness-of-fit tests, a clustering technique using kernel-based quadratic distances, and algorithms for generating random samples from Poisson kernel-based distributions (PKBD). QuadratiK has recently been accepted into the pyOpenSci ecosystem.

pyOpenSci is hiring a Communications Lead

pyOpenSci is hiring a part-time Writer and Social Media Specialist to enhance communication and engagement within the scientific Python community. This flexible, remote role involves creating social media content, newsletters, and blogs and fostering community interaction on social media to support open source and open science. Join us to make a meaningful impact on the open source ecosystem!

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Recently Accepted Python Packages


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