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UID:pretalx-euroscipy-2026-EBDPBB@pretalx.com
DTSTART;TZID=CET:20260721T163000
DTEND;TZID=CET:20260721T165000
DESCRIPTION:Pre- and post-processing of large engineering simulation datase
 ts in some scientific domains often demand performance that pure Python ca
 nnot yet deliver\, and the general approach within the scientific Python e
 cosystem for overcoming the performance barrier is the combination of Pyth
 on with compiled languages.\n \nIn this talk\, I will share practical insi
 ghts\, experiences\, and lessons drawn from the development and maintenanc
 e of PyDPF-Core\, an open-source library that interacts with a C/C++ backe
 nd via a client-server architecture for the processing of large engineerin
 g simulation datasets. We will start by discussing the challenges of devel
 oping and maintaining such a library and then examine how each of these ch
 allenges were solved for PyDPF-Core.\n \nThe focus of the talk is on trans
 ferrable insights and my goal is for attendees to leave the talk with:\n- 
 Knowledge of architectural blueprints that can be applied to their own hig
 h-performance python projects\, especially those involving the processing 
 of large simulation datasets\;\n- Patterns for managing complexity in larg
 e scientific codebases\; and\n- Understanding the trade-offs that might be
  encountered.
DTSTAMP:20260603T201530Z
LOCATION:Room 1.19 (Ground Floor\, Shannon)
SUMMARY:Lessons from Building a Large-Scale Engineering Simulation Data Pro
 cessing Library - Muhammed Adedigba
URL:https://pretalx.com/euroscipy-2026/talk/EBDPBB/
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