The next Python Exchange is coming up!
Our Guest Panelist will be:
Guillaume Lemaitre
“Developments in the scikit-learn Ecosystem: Going Beyond model.fit(X, y).predict(X)”
Scikit-learn is one of the de facto libraries when it comes to predictive modeling with tabular data. For over a decade, it has provided traditional and reliable algorithms to address data science problems. While it excels at model fitting and prediction, these stages represent only a small portion of a data science project and are relatively well-defined. Many data scientists are familiar with the notion that 90% of their time is spent on preprocessing, while the modeling stage takes up only 10% of their efforts. Additionally, tracking and organizing experiments, as well as transitioning from experimentation to production, can be challenging. This talk aims to shed light on recent developments and efforts within the scikit-learn ecosystem. We will provide an overview of the following tools through a series of short notebook demos.
- scikit-learn to provide some context.
- skrub, which offers tools to prepare your tabular data and aims to bridge the gap between the database world and the scikit-learn modeling environment.
- skops, which provides tools for transitioning from experimentation to production settings.
- skore, which aims to provide guidance throughout the lifecycle of a data science project by abstracting the above tools, making them more general and less opinionated.
About Our Guest
Guillaume Lemaitre is Chief Machine Learning Officer and an open-source software engineer at Probabl. He is a core maintainer of several packages from the scikit-learn ecosystem such as scikit-learn, skrub, skore, and imbalanced-learn. He holds a PhD in computer science / medical imaging.
Zoom Webinar Link:
Past Events
March 25th, 2025
“Narwhals: Lightweight and extensible compatibility layer between dataframe libraries!”
Marco Gorelli
February 26th, 2025
“skrub for tables: Less wrangling, more machine learning”
Gaël Varoquaux
February 26th, 2025
“skrub for tables: Less wrangling, more machine learning”
Gaël Varoquaux
January 25th, 2025
“Accelerate your Python code with Rust”
Juan Luis Cano Rodríguez
December 4th, 2024
“Possible futures for Jupyter”
Sylvain Corlay
October 30th, 2024
“Recent Tools and Trends in the Python Ecosystem”
Wes McKinney
August 28th, 2024
“Kubernetes for Data Science and Machine Learning”
Hugo Shi
July 31st, 2024
“Globus Compute: Managed Python Execution Across the Computing Continuum”
Kyle Chard
June 26th, 2024
“Topic modeling with Top2Vec”
Dimo Angelov
May 29th, 2024
“Cloud Streaming Science”
James Colliander
April 24th, 2024
“An introduction to finite element modelling in FEniCS”
Jørgen Dokken
March 27th, 2024
“Building an Open-source Ecosystem in the Golden Age of Solar Physics”
Will Barnes
February 28th, 2024
“VocalPy as a case study of domain-driven design in scientific Python”
David Nicholson, Ph.D.
January 31th, 2024
“iminuit: A foundational flexible library for fitting”
Hans Debinski
November 29th, 2023
“The Pathway to Open Source Science”
Dr. Katrina Riehl, President of the Board of Directors at NumFOCUS and Adjunct Lecturer at Georgetown University
November 1st, 2023
“Experiences from Software Collaborations Spanning Multiple Large Scale User Facilities”
Stuart Campbell, NSLS-II Chief Data Scientist & Deputy Program Manager, Data Sci & System Integration, National Synchrotron Light Source II
September 27th, 2023
“To infinity and beyond: design thoughts and experiences from writing Python code to tackle annoyingly large biological data sets”
Titus Brown, Professor, UC Davis School of Veterinary Medicine
August 30th, 2023
“Reduce, Reuse, Reinterpret: an end-to-end pipeline for recycling particle physics results”
Dr. Giordon Stark, Deaf post-doctoral, experimental particle physicist
June 30th, 2023
“pyOpenSci: building diverse community around the Python tools that drive open science”
Leah A Wasser, Executive Director, pyOpenSci
May 31st, 2023
“The Workflows Community Initiative
and the PSI/J Python Reference Implementation”
Rafael Ferreira da Silva
Apr 26th, 2023
“Tools for rapidly generating interactive user interfaces and objects”
Talley Lambert
Mar 29th, 2023
“DLSIA, or Deep Learning for Scientific Image Analysis”
Eric Roberts
Feb 22nd, 2023
“A History of UMAP As a Python Open Source Project”
Leland McInnes, Researcher, Tutte Institute
John Healy, Researcher, Tutte Institute
January 26th, 2023
“What we are doing to make Python faster”
Pablo Galindo Salgado
"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
“Sustaining the HPC software ecosystem with Spack”
Todd Gamblin, Lawrence Livermore National Labs
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”
Emanuele Laface
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
“The napari n-dimensional array viewer with Py-ART”
Draga Doncila Pop and Juan Nunez-Iglacias
Juan:
"I’m currently a Senior Research Fellow at Monash University in Melbourne, Australia. My scientific path started in genetics and biochemistry, continued through
computational 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.
Draga:
"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
all."
August 31th, 2022
“Enabling the Open Radar Science Community with Py-Art”
Max Grover and Zachary Sherman, Argonne National Laboratory
Maxwell Grover 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.
Zachary Sherman 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
PyIron — an integrated development environment (IDE) for scientific workflows at scale.
Jan Janssen
Jan Janssen 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
“The Modern Python Analysis Ecosystem for High-energy Physics”
Matthew Feickert, Gordon Watts, and Jim Pivarski
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
“The Needles in the Growing Haystack”
Mattias Bussonnier
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”
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 direction Python and PyData are headed.
December 1st, 2021
“Python: The Language for Effective Scientific Computing”
October 27, 2021
“Exploring network structure, dynamics, and function using NetworkX”
Aric Hagberg
About Us
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.
Disclaimer
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.
Host Panelists
Dan Allen
(BNL, NSLS-II)
Andi Barbour
(BNL, NSLS-II)
Matthew Carbone
(BNL, CSI)
Matthew Carbone
(BNL, CSI)
Tanny Chavez
(LBL)
Cameron Riddell
(Don't Use This Code)
James Powell
(Don't Use This Code, NumFOCUS)
Hiran Wijesinghe
(BNL NSLS-II)