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.
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Upcoming Events
May 16, 2026
PyCon US Maintainers Summit
Long Beach, CA
Join pyOpenSci and the broader Python community for a day of talks and roundtables on sustainable open source maintainership.
Learn moreMay 17, 2026
PyCon US Development Sprint
Long Beach, CA
Join pyOpenSci contributors for a one-day collaborative sprint focused on improving open science tooling, docs, and contributor workflows.
Learn moreOur programs are community powered
We Run Software Peer Review
We review Python packages and software with the goal of helping scientists build better, discoverable and usable software.
Your package can also be published in JOSS through our review process.
Submit a package for review today.
Apply to become a reviewer.
We Connect Researchers, Contributors, and Developers
pyOpenSci brings together researchers, core Python and conda developers, and data scientists from organizations like NVIDIA and Microsoft — alongside university partners like Stanford — to collectively strengthen scientific open source. We partner with open source communities to share resources, knowledge and processes like peer review.
We Break Down Python Packaging Pain Points
Check out our beginner-friendly:
Python Package Tutorials
Python Package Guide
All of our resources are co-developed with the broader Python community and reviewed by beginner to expert Pythonistas to ensure the material is accessible for all.
Broadening participation in scientific open source
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
Recent blog posts & updates
Building Resilience: pyOpenSci in 2026
pyOpenSci learned a lot about resilience in 2025. As we navigate generative AIs impact on scientific open source and shifting funding landscapes, pyOpenSci is building resilience through training, sponsorship, and community-centered leadership. Learn more about our plan.
CyNetDiff: A Python Library for Accelerated Implementation of Network Diffusion Models
CyNetDiff is a Python package for accelerating network diffusion simulations, recently accepted into the pyOpenSci ecosystem.
Navigating LLMs in Open Source: pyOpenSci’s New Peer Review Policy
Generative AI products are reducing the effort and skill necessary to generate large amounts of code. In some cases, this strains volunteer peer review programs like ours. Learn about pyOpenSci's approach to developing a Generative AI policy for our software peer review program.
Recently Accepted Python Packages
Plenoptic
a python library for model-based synthesis of perceptual stimuli
BlockingPy
Blocking records for record linkage and deduplication with Approximate Nearest Neighbor algorithms.;
ChemInformant
A robust, high-throughput Python client for retrieving chemical information from the PubChem API; it returns analysis-ready Pandas/SQL outputs, handles caching, rate-limiting and retries, and includes convenient CLI tools.