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


  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

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