diff --git a/series/brno-pyvo/events/2026-01-29.yaml b/series/brno-pyvo/events/2026-01-29.yaml new file mode 100644 index 0000000..8a04296 --- /dev/null +++ b/series/brno-pyvo/events/2026-01-29.yaml @@ -0,0 +1,38 @@ +city: brno +start: 2026-01-29 19:00:00 +name: Brněnské Pyvo +topic: Lednové +venue: artbar +description: | + První Pyvo v novém roce. Podíváme se na dizajn API a Polars, rychlou, škálovatelnou alternativu k Pandas. + + Poslední čtvrtek v měsíci v ArtBaru, jako obvykle. + + --- + + First Pyvo of the new year. We'll take a look at API design and Polars, fast and scalable alternative to Pandas. + + Last Thursday of the month at ArtBar, as usual. + +talks: + - title: How Beautiful APIs Come to Life + speakers: + - Ladislav Dobrovský + description: | + Let's deep dive into popular APIs and see how the authors make them work. Expect to see some import magic, + a LOT of decorators, chaining, proxy objects, and introspection. + + Ladislav Dobrovský works as researcher at CEITEC BUT with HPC systems and uses Python since 3.3 (2012). Likes also C++ and GPUs. + - title: Are you working with a dataset so large that your notebook running Pandas starts to freeze? + speakers: + - Dalibor Trapl + description: | + This talk is about modern alternatives for fast and scalable data analysis. + Our main focus will be the Polars DataFrame library, which offers a dramatic speed improvement compared to Pandas. + We will show when it pays off to use Polars instead of Pandas and discuss the key difference in approach: eager vs. lazy evaluation. + We will briefly compare Polars with PySpark and I will share our experience integrating these technologies into our data pipelines. + Learn how to speed up your data analysis and modernize your tech stack! + + Hi, I’m Dalibor. I moved from computational molecular simulation research to a Data Analyst role at Datamole during COVID lockdown. + My daily work revolves around time-series analysis. + I started out as a Pandas power user and have been adopting the latest tools in the Python data stack in recent years.