Tips and tricks: data science prototype into production - Ruth Luscombe (PyCon AU 2025) @PyConAU
Tips and tricks: data science prototype into production - Ruth Luscombe (PyCon AU 2025)  @PyConAU
Uploaded September 2025 | Updated September 2026, 24 minutes ago
(Ruth Luscombe) This is an overview of the tips and tricks I learned while bringing a mathematical optimization model from concept to prototype to production.
At its core, the math model is a multi-dimensional knapsack problem, with tens of thousands of items moving between warehouses with up to a hundred user-defined constraints. The model is solved with Google's OR-Tools and is deployed to AWS Lambda.
Some of the important ideas I want to share are how to build a test suite to ensure that a model of this type is internally consistent and how to handle errors-as-data for your end users. I also learned a really nice way to configure logging in python.

pretalx.com/pycon-au-2025/talk/EGQWHH

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Sun Sep 14 12:00:00 2025 at Ballroom 1
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"Tips and tricks: data science prototype into production" - Ruth Luscombe (PyCon AU 2025)

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