Accepted Talks

1. A BuildEngineer in a buildless lang

   Joshua Cannon

1. A Look at the Community Life Cycle in the Open Source Space

   Reshama Shaikh

1. Accelerate your workflow from local Python prototype to the cloud

   Savannah Ostrowski

1. Large Language Models Are Biased and Inaccurate. Can They Be Improved?

   Bard Fetler

1. Awesome Web Testing with Playwright

   Andrew Knight

1. Behind the Scenes of tox: The Journey of Rewriting a Python Tool with Over 10 Million Monthly Downloads

   Jürgen Gmach

1. Brink: Saving a Society from Starvation

   Krishi Sharma

1. Don't rely in memory: knowledge management for eng teams

   Hugo Bessa

1. Exploring Functional Options in Python

   Rami Awar

1. Formalizing a Language

   Jeremy Paige

1. Green Data Processing with Python 3.12 Polars on ARM CPU

   Asher Sterkin

1. How (and Why) to Chain Generators in Python

   Ciprian Stratulat

1. Human-Friendly, Production-Ready Data Science with Metaflow

   Hugo Bowne-Anderson

1. Let them explore! Building interactive, animated reports in Streamlit with ipyvizzu & a few lines of Python

   Peter Vidos

1. Open Source: from Passion to Hobby to Work, or There and Back Again

   Julian Berman

1. PEP talk

   Mariatta

1. Portrait of a Python Program

   Pamela Fox

1. Powering Youth Civic Engagement and Social Impact with Python data analytics.

   Anay Pant

1. Python: A career changing/shaping language

   Indranil Ghosh

1. Python2Nite with Mario Munoz

   Mario Munoz

1. Stop writing so many darn logs

   Owein Reese

1. Supercharging Large Language Model training using Metaflow and the Cloud

   Valay Dave, Utkarsh Kashyap

1. Swiss Army Django: Small Footprint ETL

   Noah Kantrowitz

1. The Lost Art of Diagrams: Making Complex Ideas Easy to See with Python

   Tadeh Hakopian

1. The Philosophy of the Peripatetic Pythonist

   Herve Aniglo

1. Unlocking the Hidden Potential: The synergy between Scripting and Software Engineering

   Anuj Menta

1. Video Game-ifying Your Learning Processes

   Jay Miller

1. When is extreme too extreme? A Bayesian approach to modeling NYC rainfall with PyMC

   Jorn Mossel

1. Why large Django projects need a data (prefetching) layer

   Flávio Juvenal

1. Would Tufte Like Matplotlib?

   Cameron Riddell