“To infinity and beyond:design thoughts and experiences from writing Python code to tackle annoyingly
large biological data sets”
I’ll talk about our experience in developing two scientific Python packages, khmer and sourmash, designed for dealing with really
large sequencing data sets. Topics will
include switching from C++ to Rust for the performance layer, integrating tests and documentation into your daily life, and the interplay between algorithmic novelty and
Titus Brown is a professor at the UC Davis School of Veterinary Medicine, where he works on software and pipelines for
biological data analysis. He has been involved in
the Python community for over 20 years, and is an advocate of open source, open science, and reproducibility in computational science. He also invests heavily in training
and capacity building. He blogs at https://ivory.idyll.org/blog/ and is currently not particularly active on any other social
media. Github at https://github.com/dib-lab/.
August 30th, 2023
Dr. Giordon Stark, Deaf post-doctoral, experimental particle physicist
“Reduce, Reuse, Reinterpret: an end-to-end pipeline for recycling particle physics results”
June 30th, 2023
Leah A Wasser, Executive Director, pyOpenSci
“pyOpenSci: building diverse community around the Python tools that drive open science”
May 31st, 2023
Rafael Ferreira da Silva
“The Workflows Community Initiative and the PSI/J Python Reference Implementation”
Apr 26th, 2023
“Tools for rapidly generating interactive user interfaces and objects”
Mar 29th, 2023
“DLSIA, or Deep Learning for Scientific Image Analysis”
Feb 22nd, 2023
Leland McInnes, Researcher, Tutte Institute
John Healy, Researcher, Tutte Institute
“A History of UMAP As a Python Open Source Project”
January 26th, 2023
Pablo Galindo Salgado
“What we are doing to make Python faster”
"Python 3.11 is faster than previous Python versions. This is the result of the effort of the Faster CPython collaboration, which is a team that Guido van Rossum started at
Microsoft and that later some other contributors and core devs (including myself) joined as collaborators. In this discussion, I will go into detail on how we are making
Python faster, what techniques are we using, what challenges are we facing, and what may be stored for future versions."
November 30th, 2022
Todd Gamblin, Lawrence Livermore National Labs
“Sustaining the HPC software ecosystem with Spack”
Spack is an open source package management tool, written in Python, that simplifies the process of building and
installing scientific software. It is used widely in the HPC community — by end users, HPC facility staff, and software developers who need to manage dependencies. Spack is
very general; it is designed to allow packages to be built with many different versions, configurations, build options, and compiler flags, for CPU and GPU machines. This
talk will give an overview of Spack, its community, and how enables users to be more productive.
October 26th, 2022
“Python in particle accelerators”
Python is a daily instrument in science for data analysis, modelling and computing in general.
In this talk, I discuss the role of Python at the European Spallation Source, a particle accelerator facility for neutron production.
I briefly describe the science that a neutron source can achieve and then my discussion will be focused on the use of Python in our laboratory.
In particular, I talk about Python and Jupyter in the control system of the particle accelerator as a front-end to access the
multiple systems used to archive data, query the accelerator devices, and simulate online the dynamics of the particle beam.
September 28th, 2022
Draga Doncila Pop and Juan Nunez-Iglacias
“The napari n-dimensional array viewer with Py-ART”
"I’m currently a Senior Research Fellow at Monash University in Melbourne, Australia. My scientific path started in genetics and biochemistry, continued through
biology and bioinformatics, then to image analysis — where I connected with the Scientific Python community and got hooked on open source development. I’ve since become a
core developer on
scikit-image, co-authored the book Elegant SciPy, and co-founded the napari library for image visualisation, annotation, and analysis.
"I am currently a PhD student working on an open source interactive interface for cell segmentation and tracking optimisation. I work part time as a software engineer
making contributions to open source software, and am a napari core developer.
I am passionate about scientific software, open source development and open research. I love sharing my knowledge with others and making software development accessible for
August 31th, 2022
Max Grover and Zachary Sherman, Argonne National Laboratory
Max is a software developer at Argonne National Laboratory, primarily working with the Atmospheric Radiation Measurement (ARM) User Facility, focused on
developing open-source tools to improve how we work with climate and weather datasets. He is one of the primary developers for the Python ARM radar toolkit (Py-ART) and
the Atmospheric Data Community Toolkit (ACT). While his background is in meteorology and atmospheric science, his passion is software engineering, working with
scientists to find ways to improve their software tools and general data workflows, advocating for open science practices.
Zach is a software developer at Argonne National Laboratory working between ARM and the Geospatial Computing Innovations, and Sensing (GCIS). Zach works
primarily as a developer on Py-ART as well as the Atmospheric Community Toolkit (ACT). Zach started with little software knowledge, but overtime developed a passion for
open source software and developing tools to help individuals with their research utilizing Python and many tools in the Scientific Python Stack as well as utilizing
and teaching coding practices such as continuous integration, PEP8 and more.
July 27th, 2022
Jan Janssen discussed the topic of PyIron — an integrated development environment (IDE) for
scientific workflows at scale.
As part of his PhD, he developed the open-source workflow framework pyiron, which couples atomistic simulation codes written in Fortran, C or C++ to a modern jupyter-based
user interface, data storage and job management. With this combination pyiron enables rapid prototyping and up-scaling of simulation protocols for exascale computing and
is applied for parameter studies in materials science ranging from uncertainty quantification for density functional theory to the prediction of melting temperatures for
interatomic potentials and beyond.
June 29th, 2022
Matthew Feickert, Gordon Watts, and Jim Pivarski hosted a discussion around the topic of “The Modern Python Analysis Ecosystem for High-energy Physics”
Matthew Feickert is a postdoctoral researcher in experimental high energy physics and data science at the American Family Insurance
Data Science Institute at the University of Wisconsin-Madison.
Jim Pivarski was trained as a particle physicist with a Ph.D. from Cornell and helped commission the CMS experiment at the
Large Hadron Collider (LHC).
Gordon Watts is a professor at the University of Washington, Seattle. His research concentrates on searches for long-lived
particle using CERN’s Large Hadron Collider and is a member of the ATLAS Experiment.
May 25th, 2022
Mattias Bussonnier: “The Needles in the Growing Haystack”
Matthias Bussonnier is a Software Engineer, and long-time open source contributor to many projects from the scientific stack. He
has been a maintainer of IPython for over 10 years, and co-founder of Jupyter, for which he shares the ACM System Software award in 2017.
April 27th, 2022
“Exploding Stars on Your Computer” by Wolfgang Kerzendorf
Wolfgang Kerzendorf is Assistant Professor, Department of Physics and Astronomy in the Department of Computational Mathematics,
Science, and Engineering, at Michigan State University.
March 30, 2022
“An overview of Python at
NERSC in the era of Perlmutter”
by Laurie Stephey and Daniel Margala
We dug into scaling Python on large scale GPU systems, as well as how to manage, and promote the usage of, those systems.
January 26th, 2022
We introduced our newest committee members and took a look ahead to what 2022 might hold for Python and the PyData community.
We also discussed some of the projects and initiatives our host panelists are working on and they shared their views on the
Python and PyData are headed.
December 1st, 2021
Ross Barnowski discussed "Python: The Language for Effective Scientific Computing"
October 27, 2021
Aric Hagberg held a discusion around "Exploring network structure, dynamics, and function using NetworkX"
We want to create a unique opportunity to see Python succeed and thrive within the National Labs! We propose creating a new resource for scientists,
researchers, and technical staff to support their use of Python and to build a strong, lasting community for Python users within the Department of Energy National Labs.
The Python Exchange is an independent group of Python enthusiasts who wish to see the use of Python and open-source computing thrive within the National Lab
system. The Python Exchange is not sponsored by or affiliated with the Department of Energy.