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CALSCALE:GREGORIAN
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UID:meetup-66a3a50d4e@palaner.app
DTSTAMP:20260802T150437Z
DTSTART:20260806T093000Z
DTEND:20260806T110000Z
SUMMARY:PythonWA Meetup August
LOCATION:Riff\, powered by Spacecubed
DESCRIPTION:Saved in Palaner as: saved\n\nPalaner match: 43% · why: lots of
  people going · easy to get to\n\nHi\, and welcome to our August Python Me
 etup!\n\nWe're a community of Python enthusiasts who enjoy learning\, shar
 ing knowledge\, and helping grow the Python ecosystem. Whether you're writ
 ing your first lines of code or you're an experienced developer building t
 he tools others rely on every day\, you'll find a place here.\n\nCome alon
 g to meet fellow Python programmers\, learn something new\, share your exp
 eriences\, and be part of a welcoming and supportive community.\n\nHow Pix
 i has revolutionalised Xarray's dev workflows: A story of perfectly reprod
 ucible environments and more\nby Nick Hodgskin\n\nOver the past few years 
 Pixi has been getting meteoric adoption in industry and the scientific com
 munity. The story is analogous to that of uv: where uv solved a lot of env
 ironment management pain for pure Python (i.e.\, PyPI) packages\, Pixi is 
 solving many environment management pains in the conda ecosystem - providi
 ng many features and workflows that are just not possible with conda or wi
 th uv. This talk explains what Pixi is\, the powerful workflows it enables
 \, as well as how its being used in large open source projects like Xarray
 . This talk will also contextualise the position of Pixi in the modern env
 ironment management scene\, and explain the cases where using Pixi will ma
 ke your life much easier than uv.\n\nNick Hodgskin is a UWA graduate\, now
  Research Software Engineer at Utrecht University in the Netherlands. He p
 rimarily works on Parcels\, but has also become a maintainer on Xarray and
  an active member in the Pangeo and Scientific Python communities. His pri
 mary contributions to Xarray have been introducing and maintaining their P
 ixi development workflows\, and has also written pages in the Pixi docs al
 ong the way.\n\nMaking Xarray Lazier - Optimising Computation Graphs\nBy C
 harles Turner\n\nSqueezing performance out of a program more or less boils
  down to a single principle - don’t make the CPU do any work it doesn’t ne
 ed to. There are a heap of ways to do this - use simpler data structures w
 ith less overhead\, pick a better algorithm\, rewrite it in Rust™.\n\nIf y
 ou wanted to try something more eccentric\, you could take a users code\, 
 infer the intent\, and rewrite it to do something that takes less work to 
 produce provably equivalent results. At a high level\, this is how a JIT c
 ompiler\, like numba works - it takes your code\, figures out what you wan
 t to do\, and then removes all the extra unnecessary work that python has 
 to do around that.\n\nPolars does this whenever you use its LazyFrame API 
 - it builds a plan\, and then rewrites that plan to be as efficient as pos
 sible. xarray\, despite being lazy\, builds its plan eagerly\, which leave
 s performance on the table. A year ago\, I started trying to fix this. Now
 \, with the help of Jean Claude van Code\, I’ve got something that does so
 mething useful.\nWarning: WIP\, this will be chaos.\n\nCharles works at AC
 CESS-NRI\, where he works on open source tools to make analysing climate m
 odel data less painful. He previously built similar tooling for air qualit
 y and observational oceanography.
URL:https://www.meetup.com/pythonwa/events/315743740/
CATEGORIES:palaner,saved
STATUS:TENTATIVE
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