Powering Human-Centered Scientific Open Source

We support the people, projects, and practices that make scientific open-source software more reliable, inclusive, and sustainable.

What's next

UN Open Source Week — pyOpenSci is leading an AI discussion

New York City

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Current project

AI tools are reshaping scientific open source. We're studying how — and building what comes next.

In 2026, we’re studying how AI tools are reshaping scientific open source — and building community-validated guidance for using them intentionally and responsibly. Over the next six months, we’re collecting data from across the community to shape a shared path forward — so no maintainer has to figure this out alone.
Gen AI reminds us that the centerpiece of open source is building community around a specific problem. AI may add functionality — but it cannot replace the context and judgment of a diverse and engaged community."
— Eliot Robson, pyOpenSci Peer Review Lead

Our programs are community powered

Illustration for software peer review — person at a laptop with pyOpenSci branding.

We run software peer review

We review Python packages with the goal of helping scientists build better, discoverable, and usable software. Accepted packages can be published in JOSS through our review process.
About peer review →
Illustration for community partnerships — diverse figures collaborating.

We connect researchers, contributors, and developers

pyOpenSci brings together researchers, core Python and conda developers, and data scientists from industry and universities to strengthen scientific open source. We partner with communities to share resources, knowledge, and processes like peer review.
Community partnerships →
Python packaging guide graphic with a laptop and hands over keyboard.

We break down Python packaging pain points

Beginner-friendly tutorials and a community Python packaging guide, co-developed with the broader Python ecosystem so the material stays accessible at every level.
Python packaging guide →

Submit your package

Ready for review? Learn what we look for and how to submit your scientific Python package.
Author guide →

Become a reviewer

Join reviewers who care about usability, docs, and maintainability — mentorship is available for your first review.
Reviewer guide →

Events & training

Workshops, cohort courses, sprints, and community calls — online and at conferences.
Browse events →

Training

New cohort coming fall 2026

Ship It: Python Packaging in the Era of AI

A 10-day online course for researchers, academics, and RSEs — from working code to a published package.

Learn more

Python packaging guide graphic with a laptop and hands over keyboard.

Broadening participation in scientific open source

Three people working at two computers during a PyCon USA sprint in 2023.

You don’t need to be an expert to get involved

Are you new to software peer review but you want to get involved? We’ve got you! We offer support and mentorship to new reviewers completing their first review.

Reviewers do not need to be Python packaging experts. We welcome reviewers who focus on software accessibility and usability.

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

pyOpenSci has a diverse and vibrant community of pythonistas! To date, 392 wonderful people have contributed to pyOpenSci.

Recent blog posts & updates

View more on the blog

Recently accepted Python packages

lintquarto

Amy Heather

Package for running linters, static type checkers and code analysis tools on python code in quarto (.qmd) files.

tda-mapper

Luca Simi

A Python library implementing the Mapper algorithm for Topological Data Analysis.

C4dynamics

Ziv Meri

Python framework for algorithms of dynamic systems

View all accepted packages