Anyone work with time series data professionally? Either modeling or data engineering? Have some questions and would appreciate a call.

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.

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.

Will this be streamed?

sisyphus's comment on "Why is everything in Java & Scala?" Explore this conversation and more from the dataengineering community

Why do I take this personally?

www.reddit.com/r/dataengine...

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.

I’ve been thinking a lot about how to scale symbolic regression: this seems like a plausible direction.

mchav.github.io/grow-and-mow/

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

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...

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.

[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...

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...

Either is fine. Anything that won't be infected

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.

This is almost exactly how you'd do in Haskell dataframes with some macro trickery though.

Started a new position @coreweave.bsky.social working on @marimo.io

Sometimes you gotta do the boring thing that gets the job done.

www.datahaskell.org/blog/2026/03...

[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...

Sabela - A reactive Notebook for #Haskell by the DataHaskell project

Announcement: discourse.haskell.org/t/ann-sabela...

Github Repository: github.com/DataHaskell/...

I gotta starting taking cold showers before a job interview for a job that I want - wash off the smell of desperation.

Where would Haskell sit here? There's a way to write it such that you can balance human and machine readability.

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...

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.

All is data science

www.datahaskell.org/blog/2025/12...

On the flip side some Haskell can get extremely dense and people can do crazy with types. Enough so that they become a distraction from the actual logic. Same with inheritance in Java. Line by line go is typically very readable. More broadly would be a matter of experience and taste.

Okay. I guess we agree that it’s readable by some definition. I think the broader definition of readability (blocks of code) depends on style guide, domain knowledge, and team context more than programming language.

The trade off is that you get:
- very readable code
- good, predictable performance
- fast compile times
- a lot of built in tooling (go profile + bench are great)

I admit that it’s easy to write bad code but we invested in linters a style guide and tests so we don’t deal with the ugly parts.

I write go at work and I think it’s a great language in general. What do you dislike about it?

I find that working with Haskell developers often involves trying to make them think more like engineers - conversely working with Go and Python developers often involves trying to make them think like scientists.

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).

Great article! The fix also really outlines that contributions don’t have to be hundreds of lines of code to be impactful.

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...

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...

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.