Welcome - Day 1

09:10 – 09:40  in  Aula 4.101

Your Code Is Slower Than Expected - Hidden Performance Traps

by Michael Inden

09:45 – 10:15  in  Aula 4.101

Eliminate hidden exceptions via railway-oriented programming

by Christoph Gietl

10:20 – 10:50  in  Aula 4.101

How to make Django insecure

by Gaweng Tan

Pyladies presentation

11:35 – 12:05  in  Aula 4.101

Sentinel Values in Python: Why None Is Not Enough

by Florian Wilhelm

12:10 – 12:40  in  Aula 4.101

Securing the Supply Chain of your Python app

by Federico Fregosi

13:55 – 14:25  in  Aula 4.101

Pulumi: The Joy of Infrastructure as (Python) Code

by Jonas Böer

14:30 – 15:00  in  Aula 4.101

Profiling Python: From cProfile to Sampling

by Farid Mirzayev

15:40 – 16:10  in  Aula 4.101

Packaging FOSS Python applications and libraries for Debian

by Theodore Tucker

16:15 – 17:00  in  Aula 4.101

Lightning Talks - Day 1

Closing - Day 1

Welcome - Day 2

09:10 – 09:40  in  Aula 4.101

Before you open that OSS issue: evidence-first triage

by Pavel Sulimov, Sergey Eremeykin

09:45 – 10:15  in  Aula 4.101

Too Complicated to Model? Missing Female Athletes Data

by Hilal Işık

10:20 – 10:50  in  Aula 4.101

Beyond the Hype: Building a Python Game to Teach AI Concepts

by Vadim Vlasov, Eric Glaser

Pyladies presentation

11:35 – 12:05  in  Aula 4.101

Is Your Data Lying? Bayesian Data Credibility

by Vince Nelidov

12:10 – 12:40  in  Aula 4.101

Keeping data private in real-time pipelines

by Olena Kutsenko

13:55 – 14:25  in  Aula 4.101

No more model training? TabPFN v3 vs. tuned trees.

by Dominik Traxl

14:30 – 15:00  in  Aula 4.101

From Open Weights to Trusted Models

by Emmanuel Okedele

15:40 – 16:10  in  Aula 4.101

Did we break up? Auditing Instagram data with Python

by Almudena Barreiro Carrillo

16:15 – 17:00  in  Aula 4.101

Lightning Talks - Day 2

Closing - Day 2