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SUMMARY:Pure functions + Separate I/O: Functional Python Pipelines for Rep
 roducible Experiments - Niels Neerhoff\, Simon Brugman
DTSTART;TZID=Poland:20260720T152000
DTEND;TZID=Poland:20260720T155000
DTSTAMP:20260911T010040Z
UID:pretalx-euroscipy-2026-JUEQLF@pretalx.com
DESCRIPTION:Scaling data science pipelines in research and industry poses 
 well-known maintainability challenges ([big ball of mud](https://www.laput
 an.org/pub/foote/mud.pdf)). Research codebases must support rapid iteratio
 n as insights evolve\, while industry systems must scale amid changing bus
 iness needs and organizational complexity. Effective projects should remai
 n maintainable without overhauling the entire code base for each change. I
 deally\, evolving from a notebook experiment to a production-grade applica
 tion should feel natural\, with minimal overhead.\n\nIn this talk\, we sho
 w how data science projects benefit from established software engineering 
 principles\, particularly those inspired by functional programming\, in Py
 thon. The first part of the talk outlines the design principles. The secon
 d part\, will go into our (brutally honest) insights from applying these i
 n various research projects\, spanning from master student experiments to 
 the applications in our R&D teams.
LOCATION:Room 2.41 (First Floor\, Turing)
URL:https://pretalx.com/euroscipy-2026/talk/JUEQLF/
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