Come join the BoF to do a practice run on contributing to a GitHub project. We will walk through how to open a Pull Request for a bugfix, using the workflow most libraries participating at the weekend sprints use (hosted by the sprint chairs)

If you have interest in NumPy, SciPy, Signal Processing, Simulation, DataFrames, Linear Programming (LP), Vehicle Routing Problems (VRP), or Graph Analysis, we'd love to hear what performance you're seeing and how you're measuring.

Come share your ideas next year's SciPy. Participants will have an opportunity to sign up to be on next year's organizing committee.

Lightning talks are 5-minute talks on any topic of interest for the SciPy community. We encourage spontaneous and prepared talks from everyone, but we can’t guarantee spots. Sign ups are at the NumFOCUS booth during the conference.

The SciPy library provides objects representing well over 100 univariate probability distributions. These have served the scientific Python ecosystem for decades, but they are built upon an infrastructure that has not kept up with the demands of today’s users. To address its shortcomings, SciPy 1.15 includes a new infrastructure for working with probability distributions. This talk will introduce users to the new infrastructure and demonstrate its many advantages in terms of usability, flexibility, accuracy, and performance.

As scientific computing increasingly relies on diverse hardware (CPUs, GPUs, etc) and data structures, libraries face pressure to support multiple backends while maintaining a consistent API. This talk presents practical considerations for adding dispatching to existing libraries, enabling seamless integration with external backends. Using NetworkX and scikit-image as case studies, we demonstrate how they evolved to become a common API with multiple implementations, handle backend-specific behaviors, and ensure robustness through testing and documentation. We also discuss technical challenges, differences in approaches, community adoption strategies, and the broader implications for the SciPy ecosystem.

The SciPy Proceedings (https://proceedings.scipy.org) have long served as a cornerstone for publishing research in the scientific python community; with over 330 peer-reviewed articles being published over the last 17 years. In 2024, the SciPy Proceedings underwent a significant transformation, adopting MyST Markdown (https://mystmd.org) and Curvenote (https://curvenote.com) to enhance accessibility, interactivity, and reproducibility — including publishing of Jupyter Notebooks. The new proceedings articles are web-first, providing features such as deep-dive links for cross-references and previews of GItHub content, interactive 3D visualizations, and rich-rendering of Jupyter Notebooks. In this talk, we will (1) present the new authoring & reading capabilities introduced in 2024; (2) highlight connections to prominent open-science initiatives and their impact on advancing computational research publishing; and (3) demonstrate the underlying technologies and how they enhance integrations with SciPy packages and how to use these tools in your own communication workflows.

Our presentation will give an overview of the revised authoring process for SciPy Proceedings; how we improve metadata standards in a similar way to code-linting and continuous integration; and the integration of live previews of the articles, including auto-generated PDFs and JATS XML (a standard used in scientific publishing). The peer-review process for the proceedings currently happens using GitHub’s peer-review commenting in a similar fashion to the Journal of Open Source Software; we will demonstrate this process as well as showcase opportunities for working with distributed review services such as PREreview (https://prereview.org). The open publishing pipeline has streamlined the submission, review, and revision processes while maintaining high scientific quality and improving the completeness of scholarly metadata. Finally, we will present how this work connects into other high-profile scientific publishing initiatives that have incorporated Jupyter Notebooks and live computational figures as well as interactive displays of large-scale data. These initiatives include Notebooks Now! by the American Geophysical Union, which is focusing on ensuring that Jupyter Notebooks can be properly integrated into the scholarly record; and the Microscopy Society of America’s work on interactive publishing and publishing of large-scale microscopy data with interactive visualizations. These initiatives and the SciPy Proceedings are enabled by recent improvements in open-source tools including MyST Markdown, JupyterLab, BinderHub, and Curvenote, which enable new ways to share executable research content. These initiatives collectively aim to improve both the reproducibility, interactivity, and the accessibility of research by providing improved connections between data, software and narrative research articles.

By embracing open science principles and modern technologies, the SciPy Proceedings exemplify how computational research can be more transparent, reproducible, and accessible. The shift to computational publishing, especially in the context of the scientific python community, opens new opportunities for researchers to publish not only their final results but also the computational workflows, datasets, and interactive visualizations that underpin them. This transformation aligns with broader efforts in open science infrastructure, such as integrating persistent identifiers (DOIs, ORCID, ROR), and adopting FAIR (Findable, Accessible, Interoperable, Reusable) principles for computational content. Building on these foundations, as well as open tools like MyST Markdown and Curvenote, provides a scalable model for open scientific publishing that bridges the gap between computational research and scholarly communication, fostering a more collaborative, iterative, and continuous approach to scientific knowledge dissemination.

Lightning talks are 5-minute talks on any topic of interest for the SciPy community. We encourage spontaneous and prepared talks from everyone, but we can’t guarantee spots. Sign ups are at the NumFOCUS booth during the conference.

This track highlights the fantastic scientific applications that the SciPy community creates with the tools we collectively make. Talk proposals to this track should be stories of how using the Scientific Python ecosystem the speakers were able to overcome challenges, create new collaborations, reduce the time to scientific insight, and share their results in ways not previously possible. Proposals should focus on novel applications and problems, and be of broad interest to the conference, but should not shy away from explaining the scientific nuances that make the story in the proposal exciting.

This keynote will trace the personal journey of NumPy's development and the evolution of the SciPy community from 2001 to the present. Drawing on over two decades of involvement, I’ll reflect on how a small group of enthusiastic contributors grew into a vibrant, global ecosystem that now forms the foundation of scientific computing in Python. Through stories, milestones, and community moments, we’ll explore the challenges, breakthroughs, and collaborative spirit that shaped both NumPy and the SciPy conventions over the years.

Join us for an evening of connection and creativity at the Museum of Glass, just a short walk from the conference venue. Explore stunning glass art exhibits, enjoy refreshments, and connect with fellow SciPy attendees in a unique and inspiring setting.

The virtual poster session takes place 6:00–7:00 p.m. in the SciPy 2025 Gather space. Meet with the poster authors to ask questions and learn about the posters that will be on display in the poster hall inside our virtual space. Virtual and in-person ticket holders are all welcome to attend in Gather!

The Poster session will be in the Ballroom from 6:00-7:00pm. Meet with the poster authors to ask questions and learn about the posters that will be on display throughout the main conference.

Lightning talks are 5-minute talks on any topic of interest for the SciPy community. We encourage spontaneous and prepared talks from everyone, but we can’t guarantee spots. Sign ups are at the NumFOCUS booth during the conference.

Many scientists rely on NumPy for its simplicity and strong CPU performance, but scaling beyond a single node is challenging. The researchers at SLAC need to process massive datasets under tight beam time constraints, often needing to modify code on the fly. This is where cuPyNumeric comes in—a drop-in replacement for NumPy that distributes work across CPUs and GPUs. With its familiar NumPy interface, cuPyNumeric makes it easy to scale computations without rewriting code, helping scientists focus on their research instead of debugging. It’s a great example of how the SciPy ecosystem enables cutting-edge science.

Generative Artificial Intelligence (AI) is reshaping engineering education by offering students new ways to engage with complex concepts and content. Ethical concerns including bias, intellectual property, and plagiarism make Generative AI a controversial educational tool. Overreliance on AI may also lead to academic integrity issues, necessitating clear student codes of conduct that define acceptable use. As educators we should carefully design learning objectives to align with transferrable career skills in our fields. By practicing backward design with a focus on career-readiness skills, we can incorporate useful prompt engineering, rapid prototyping, and critical reasoning skills that incorporate generative AI. Engineering students want to develop essential career skills such as critical thinking, communication, and technology. This talk will focus on case studies for using generative AI and rapid prototyping for scientific computing in engineering courses for physics, programming, and technical writing. These courses include assignments and reading examples using NumPy, SciPy, Pandas, etc. in Jupyter notebooks. Embracing generative AI tools has helped students compare, evaluate, and discuss work that was inaccessible before generative AI. This talk explores strategies for using AI in engineering education while accomplishing learning objectives and giving students opportunities to practice career readiness skills.

Block-based programming divides inputs into local arrays that are processed concurrently by groups of threads. Users write sequential array-centric code, and the framework handles parallelization, synchronization, and data movement behind the scenes. This approach aligns well with SciPy's array-centric ethos and has roots in older HPC libraries, such as NWChem’s TCE, BLIS, and ATLAS.

In recent years, many block-based Python programming models for GPUs have emerged, like Triton, JAX/Pallas, and Warp, aiming to make parallelism more accessible for scientists and increase portability.

In this talk, we'll present cuTile and Tile IR, a new Pythonic tile-based programming model and compiler recently announced by NVIDIA. We'll explore cuTile examples from a variety of domains, including a new LLAMA3-based reference app and a port of miniWeather. You'll learn the best practices for writing and debugging block-based Python GPU code, gain insight into how such code performs, and learn how it differs from traditional SIMT programming.

By the end of the session, you'll understand how block-based GPU programming enables more intuitive, portable, and efficient development of high-performance, data-parallel Python applications for HPC, data science, and machine learning.

This talk walks all Pythonistas through recent CuPy feature development. Join me and hear my story on how an open-source novice started contributing to and helping CuPy over the years grow into a full-fledged, reliable, GPU-accelerated array library that covers most of NumPy, SciPy, and Numba functionalities.

Scientific Python is not only at the heart of discovery and advancement, but also infrastructure. This talk will provide a perspective on how open-source Python tools that are already powering real-world impact across the sciences are also supportive of public institutions and critical public data infrastructure. Drawing on her previous experience leading policy efforts in the Department of Energy as well as her experience in open-source scientific computing, Katy will highlight the indispensable role of transparency, reproducibility, and community in high-stakes domains. This talk invites the SciPy community to recognize its unique strengths and to amplify their impact by contributing to the public good through technically excellent, civic-minded development.

Ontologies provide a powerful way to structure knowledge, enable reasoning, and support more meaningful queries compared to traditional data models. Recently, interest in ontologies has resurged, driven by advancements in language models, reasoning capabilities, and the growing adoption of platforms like Palantir Foundry.

In this hands-on tutorial, participants will explore ontology development across multiple domains using a variety of Python-based tools such as rdflib, Owlready2, PySpark, Pandas, and SciPy. They will learn how ontologies facilitate semantic reasoning, improve data interoperability, and enhance query capabilities.
Additionally, attendees will build a rudimentary reasoning engine to better understand inference mechanisms.
The tutorial emphasizes practical applications and comparisons with conventional data representations, making it ideal for researchers, data engineers, and developers interested in knowledge representation and reasoning.