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Michael Chavinda

@mschav.bsky.social
79 followers 59 following 153 posts

Curious about many things

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Michael Chavinda @mschav.bsky.social · 22/09/2026
Haskell parquet features now tracked on the official parquet site: parquet.apache.org/docs/file-fo...
parquet.apache.org
Implementation status
This page summarizes the features supported by different Parquet implementations. Note: If you find out of date information, please help us improve the accuracy of this page by opening an issue or sub...
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Michael Chavinda @mschav.bsky.social · 26/08/2026
Some thoughts on what I call context complexity: mchav.github.io/context-comp...
mchav.github.io
Context complexity: what is the Big-O of an agent API?
TLDR; small, local models are a good instrument for measuring what a harness costs an agent. an API is only as good as its outputs’ specificity, parsimony, and truthfulness. obvious code repair...
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Michael Chavinda @mschav.bsky.social · 15/08/2026
Zurihac talk is up: youtu.be/WpDVrUdbT2o?...
youtu.be
Can Haskell Become a Great Language for Data Science? | Michael Chanvinda | ZuriHac 2026
YouTube video by OST – Ostschweizer Fachhochschule
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Reposted by Michael Chavinda
Haskell programming language @haskell.org · 28/07/2026
On the blog: "Quick tips for fast iteration in #Haskell" by Tom Ellis & Laurent P. René de Cotret blog.haskell.org/quick-tips-f...
blog.haskell.org
Quick tips for fast iteration in Haskell | The Haskell Programming Language's blog
Quick tips about tools and techniques for fast iteration when developing Haskell
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Michael Chavinda @mschav.bsky.social · 24/07/2026
Prompting is really a form a brainrot.
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Reposted by Michael Chavinda
Gordon Padelford @gordonofseattle.bsky.social · 08/07/2026
Who needs some good news today? @pikeplacemarket.bsky.social is introducing a "Locals Night" every Wednesday evening through September 9th where there will be a farmers market on the street and many businesses will be open later than usual! You love to see it. www.pikeplacemarket.org/events-calen...
produce on pike flyerBusinesses staying open late on Wednesdays include:

Grocery & Shops
Darras – until 7pm
Delaurenti Food & Wine – until 6pm
Don & Joe’s Meats – until 6pm
Golden Age Collectables – until 7pm
Le Panier – until 6pm
Made in Washington – until 6pm
Pike and Western Wine – until 6pm
Ventures Marketplace – until 7pm
Woodring Northwest – until 6pm

Restaurants & Entertainment Venues
Alibi Room – until 2am
Bottega Gelato – until 9pm
El Borracho – until 9pm
Lonely Siren – until 12am
Pike Place Bar & Grill – until 10pm
Il Bistro – until 2am
Le Pichet – until 9pm
Matt’s in the Market – until 10pm
Maximilien – until 9pm
Mee Sum Pastry – until 7pm
Old Stove Brewing – until 10pm
Pike Place Chinese Cuisine – until 9pm
Piroshky Piroshky – until 7pm
Pizza and Pasta Bar – 9:30pm
Rachel’s Ginger Beer – until 9pm
Radiator Whiskey –  until 10pm
Taproom at Pike Place – until 10pm
The Rabbit Box – until 12am
The Pink Door – 11:30pm
Unexpected Productions – 10pm
Urara – until 8pm
Virginia Inn – until 9pm
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Michael Chavinda @mschav.bsky.social · 02/07/2026
Models are programs A motivation and brief tour of dataframe-learn. At its best DataHaskell is a place for these kind of cross-cutting experiments. www.datahaskell.org/blog/2026/07...
datahaskell.org
Models are programs
OverviewWe present dataframe-learn, a machine learning library where the output of training models is symbolic expressions. We first motivate why symbolic mo...
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Reposted by Michael Chavinda
Flavio 🏴‍☠️ @flaviocorpa.com · 24/06/2026
I recently really enjoyed @mschav.bsky.social's talk at #ZuriHac so I tried to reproduce this chart in Sabela (a Jupyter-notebook-like project for #Haskell) seems like this Mbappé guy is not so bad either! 🤭
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Michael Chavinda @mschav.bsky.social · 22/06/2026
Before we solve data workflows in Haskell we have to teach people Haskell. sabela.datahaskell.com/c/1ea40000
sabela.datahaskell.com
Learn You a Haskell for Great Good!
Curated reactive Haskell notebooks.
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Michael Chavinda @mschav.bsky.social · 14/06/2026
sabela.datahaskell.com Sabela now has a community gallery. The highlighted examples show that Haskell can be a good tool for exploratory work.
sabela.datahaskell.com
Sabela Community Gallery
Curated reactive Haskell notebooks.
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Michael Chavinda @mschav.bsky.social · 30/05/2026
It’s pretty annoying that LLMs like to use the construction “X is real”.
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Michael Chavinda @mschav.bsky.social · 25/04/2026
A small experiment comparing token efficiency between Haskell and Python. Not rigorous at all but I’ll follow it up eventually. mchav.github.io/a-first-look...
mchav.github.io
A first look at token efficiency
A while ago I saw the article Which languages are most token efficient. The article was largely discredited since it didn’t have a clear methodology. Unfortunately, I haven’t come up with one yet but ...
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Michael Chavinda @mschav.bsky.social · 23/04/2026
I’ve been doing a small social experiment on how to best to market Haskell (dataframe) to non Haskell programmers. It seems engagement and stars go up when the article doesn’t foreground Haskell but instead uses it as a conduit for a larger concept.
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Michael Chavinda @mschav.bsky.social · 15/04/2026
Anyone work with time series data professionally? Either modeling or data engineering? Have some questions and would appreciate a call.
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Seattle Streets Alliance @streetsalliance.bsky.social · 13/04/2026
Lake Washington Blvd will be open to people & closed to car traffic every weekend this summer from Memorial Day to Labor Day! The predictable schedule makes it easier walk, bike, roll, along, or drive to the boulevard. Thank you Mayor Wilson, community advocates, and Rainier Valley Safe Streets.
Illustrated poster from Seattle Parks & Recreation promoting “Bicycle Weekends 2026.” 

The scene shows a person riding a bike and another walking along a scenic path with mountains, trees, and flowers. Text reads: “Bike, walk, or roll with us on Lake Washington Blvd! No cars on select dates,” followed by dates in May through September.
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Michael Chavinda @mschav.bsky.social · 10/04/2026
Why do I take this personally? www.reddit.com/r/dataengine...
reddit.com
sisyphus's comment on "Why is everything in Java & Scala?"
Explore this conversation and more from the dataengineering community
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Reposted by Michael Chavinda
April Verrett @seiupres.bsky.social · 09/04/2026
Using your debt, your search history, and your private data to decide how much you’re worth? Hell no. This is what happens when technology is built to serve profit instead of people. This is why every worker needs a union.
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Michael Chavinda @mschav.bsky.social · 09/04/2026
I’ve been thinking a lot about how to scale symbolic regression: this seems like a plausible direction. mchav.github.io/grow-and-mow/
mchav.github.io
Grow and mow: interpretable models with boosting, symbolic regression and e-graphs
This post is the convergence of two ideas that have been floating in my head for about a year. Can we learn messy stochastic models and use algorithmic/algebraic tools to rein in model complexity to make models interpretable?
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Michael Chavinda @mschav.bsky.social · 03/04/2026
With more and more code being written by AI I think human coding will mostly be for prototyping and brain storming. Notebooks will become a much more important developer interface. So I mixed interactivity, Lean, Haskell, and Python into a single notebook runtime sabela.datahaskell.com
sabela.datahaskell.com
Sabela
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Michael Chavinda @mschav.bsky.social · 29/03/2026
I took a crack at category theory + dataframes. I find the difficulty with reading and writing about this kind of stuff is that it's really hard to communicate what the "point" is. Hopefully it all makes sense: mchav.github.io/what-categor...
mchav.github.io
What Category Theory Teaches Us About DataFrames
Every dataframe library ships with hundreds of operations. pandas alone has over 200 methods on a DataFrame. Is pivot different from melt? Is apply different from map? What about transform, agg, apply...
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Michael Chavinda @mschav.bsky.social · 27/03/2026
I've been looking at symbolic regression for some time now. I think most genetic approaches would benefit from large e graph databases to reduce the search space. Having to start every search from scratch every time seems silly.
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Reposted by Michael Chavinda
Haskell programming language @haskell.org · 22/03/2026
Today is a great day for some major news! DataFrame v1.0.0.0 has been officially released! Step up your exploratory data analysis in #Haskell with Typed data frames, direct connection to HuggingFace data sets, and Python integration through Apache Arrow. discourse.haskell.org/t/ann-datafr...
discourse.haskell.org
[ANN] dataframe 1.0.0.0
It’s been roughly two years of work on this and I think things are in a good enough state that it’s worth calling this v1. Features Typed dataframes We got there eventually and I think we got there i...
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Michael Chavinda @mschav.bsky.social · 13/03/2026
Anyone know what could be a good second career? Even if coding makes it out of the AI era I fear it won’t be interesting.
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Michael Chavinda @mschav.bsky.social · 03/03/2026
Started a new position @coreweave.bsky.social working on @marimo.io
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Michael Chavinda @mschav.bsky.social · 02/03/2026
Sometimes you gotta do the boring thing that gets the job done. www.datahaskell.org/blog/2026/03...
datahaskell.org
Sabela: A Reactive Haskell Notebook
Overview
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Reposted by Michael Chavinda
Haskell programming language @haskell.org · 24/02/2026
Sabela - A reactive Notebook for #Haskell by the DataHaskell project Announcement: discourse.haskell.org/t/ann-sabela... Github Repository: github.com/DataHaskell/...
discourse.haskell.org
[ANN] sabela - A reactive Notebook for Haskell
Sabela is a reactive notebook environment for Haskell. The name is derived from the Ndebele word meaning “to respond.” The project has two purposes. Firstly, it is an attempt to design and create a mo...
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Michael Chavinda @mschav.bsky.social · 22/01/2026
I gotta starting taking cold showers before a job interview for a job that I want - wash off the smell of desperation.
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Michael Chavinda @mschav.bsky.social · 17/01/2026
Small experiment: treat feature engineering as program synthesis, then use an LLM as a lightweight prior over which derived quantities are “nameable.” The learner stays classical; the artifact gets way more readable. mchav.github.io/learning-bet...
mchav.github.io
Learning better decision tree splits - LLMs as Heuristics for Program Synthesis
A lot of tabular modeling gets easier the moment you stumble onto the right derived quantity. Not something mysterious or “deep.” It’s usually something you can name: a ratio that turns two raw column...
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Michael Chavinda @mschav.bsky.social · 29/12/2025
Symbolic AI is built on the premise that models should be presented in terms that are understandable to us. When you interact with a symbolic system you learn something about the reality that it tries to model. That alone makes symbolic approaches worth betting on in the long term.
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Michael Chavinda @mschav.bsky.social · 26/12/2025
All is data science www.datahaskell.org/blog/2025/12...
datahaskell.org
Exploring GHC profiling data in Jupyter
Exploratory data analysis (EDA) isn’t just for data scientists. Anyone that uses a system that emits data can benefit from the tools of EDA. And since charit...
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Michael Chavinda @mschav.bsky.social · 21/12/2025
In software it’s often important to distinguish between solving the scientific problem (how do we make this generalize for all instances of the problem) versus the engineering problem (how do we make this work for the environment we anticipate it’ll be used in).
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Michael Chavinda @mschav.bsky.social · 20/12/2025
Great article! The fix also really outlines that contributions don’t have to be hundreds of lines of code to be impactful.
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Michael Chavinda @mschav.bsky.social · 18/12/2025
Just updated the dataframe SQL library to auto generate expression bindings from the table types. The read input surface is looking pretty great now: CSV, JSON lines, Parquet and now various SQL DBs. hackage.haskell.org/package/data...
hackage.haskell.org
dataframe-persistent
Persistent database integration for the dataframe library
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Reposted by Michael Chavinda
Haskell programming language @haskell.org · 10/12/2025
The State of #Haskell 2025 survey is out! Please take ~10 minutes to fill this out and share it with friends/colleagues/coworkers, whether or not they are users of Haskell.
discourse.haskell.org
State of Haskell 2025
Hello everyone! The Haskell Foundation is reviving @taylorfausak’s State of Haskell Survey. It’s been a few years and so we’re doing it a bit differently, but the plan is to start doing this yearly a...
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Michael Chavinda @mschav.bsky.social · 10/12/2025
Learning how to do the necessary but boring skill is underrated. It pays off so much in the long run.
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Haskell programming language @haskell.org · 05/12/2025
Layoutz – A tiny zero-dep lib for beautiful #Elm-style TUI's in #Haskell 🪶 flora.pm/packages/@ha... www.reddit.com/r/haskell/co... discourse.haskell.org/t/layoutz-0-...
flora.pm
@hackage › layoutz — Flora.pm
Simple, beautiful CLI output for Haskell
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Reposted by Michael Chavinda
Jonathan Carroll @jonocarroll.fosstodon.org.ap.brid.gy · 05/12/2025
Perhaps you saw the post series "Python is not a great language for data science"... well, here's Haskell IS a Great Language for Data Science jcarroll.com.au/2025/12/05/haskell-… #haskell :haskell: #rstats :rstats:
jcarroll.com.au
Haskell IS a Great Language for Data Science
I’ve been learning Haskell for a few years now and I am really liking a lot of the features, not least the strong typing and functional approach. I thought it was lacking some of the things I missed from R until I found the dataHaskell project. In this post I’ll demonstrate some of the features and explain why I think it makes for a good (great?) data science language.
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Michael Chavinda @mschav.bsky.social · 02/12/2025
Great article that gives a quick run through of Hasktorch. www.stackbuilders.com/insights/has...
stackbuilders.com
Hasktorch: LibTorch Haskell bindings for deep learning using FFI
This blog post will introduce Hasktorch, a Haskell binding for deep learning. We'll explore how Hasktorch leverages Foreign Function Interface (FFI) to integrate with Libtorch. The post will demonstra...
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Michael Chavinda @mschav.bsky.social · 26/11/2025
Article to checkpoint where we are with the Haskell Jupyter kernels. www.datahaskell.org/blog/2025/11...
datahaskell.org
A tale of two kernels
Overview
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Michael Chavinda @mschav.bsky.social · 12/11/2025
There’s something beautiful at the end of all this. I just know it.
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Michael Chavinda @mschav.bsky.social · 05/11/2025
Continuing the series on program synthesis: mchav.github.io/an-introduct...
mchav.github.io
An introduction to program synthesis (Part II) - Automatically generating features for machine learning
Introduction This post kicks off the second part of a hands-on series about program synthesis. We’ll apply the previously explored technique (an enumerative bottom-up search) to a slightly more realis...
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Michael Chavinda @mschav.bsky.social · 20/10/2025
As cultural beings, we are echoes of the past: even our most personal thoughts, emotions, and experiences are mediated by words, images, and ideas we inherited from previous generations. Your mind was born and started growing many thousands of years before your body.” Francois Chollet
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Michael Chavinda @mschav.bsky.social · 14/10/2025
Wrote a new article where I checkpoint the work we’ve done so far enabling Kaggle style EDA-to-model workflows in Haskell. Covers Jupyter notebooks, dataframes, charting and machine learning with the iris dataset as the working example. mchav.github.io/iris-classif...
mchav.github.io
Progress towards Kaggle-style workflows in Haskell
There’s been a lot of work in the Haskell ecosystem that has made it easier to write interactive Kaggle-like scripts. I’d like to showcase the synergy between 3 such tools: dataframe (my own creation)...
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Michael Chavinda @mschav.bsky.social · 10/10/2025
Lorem ipsum is taken from an excerpt about stoicism which says: “The wise man, therefore, always holds in these matters to this principle of selection: he rejects pleasures to secure other greater pleasures, or else he endures pains to avoid worse pains.”
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Polars @pola.rs · 09/10/2025
Swiss insurer La Mobilière refactored their risk model to Polars, achieving 5-10x speedups and enabling actuaries to run millions of simulation years on laptops. A scale previously unfeasible with pandas due to memory and single-core limitations. pola.rs/posts/case-m...
pola.rs
Polars helps coping with black swan events at La Mobilière
DataFrames for the new era
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Michael Chavinda @mschav.bsky.social · 04/10/2025
The MIT program synthesis class finally has problem sets. I’ll dedicate most of the fall/winter to completing it. people.csail.mit.edu/asolar/Synth...
people.csail.mit.edu
Introduction to Program Synthesis
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Michael Chavinda @mschav.bsky.social · 03/10/2025
There are a lot of things I wish I had the discipline to learn over the years. I convinced myself I needed the right mentor or book. Years later, more has been lost from indecision than wrong decision.
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Michael Chavinda @mschav.bsky.social · 30/09/2025
Rebooting the work started by @ocramz.bsky.social with dataHaskell Come through: discord.gg/UXcv5Eaz
discord.gg
Join the DataHaskell Discord Server!
Check out the DataHaskell community on Discord - hang out with 5 other members and enjoy free voice and text chat.
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The Urbanist @theurbanist.org · 19/09/2025
“When a full-service grocer leaves a neighborhood, it doesn’t just take away a shopping option; it reshapes the local food landscape. Competition shrinks, which means prices rise and choices narrow. Families end up paying more whether they stay local or spend extra time and money traveling farther.”
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Michael Chavinda @mschav.bsky.social · 19/09/2025
Everything is converging to the same syntax.
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