Tom's Blog

It’s time for another review for books I read this year (previously: 2024, 2022).

This post gives detailed background to my PyData Global talk, “GPU-Accelerated Zarr” (slides, video).

Last weekend I had the chance to sail in the 2025 Corn Coast Regatta.

You can watch a video version of this talk at https://youtu.be/BFFHXNBj7nA On Thursday, I presented a talk, GPU Accelerated Cloud-Native Geospatial, at the inaugural Cloud-Native Geospatial Conference (slides here).

I have a new post up at the NVIDIA technical blog on High-Performance Remote IO with NVIDIA KvikIO.1 This is mostly general-purpose advice on getting good performance out of cloud object stores (I guess I can’t get away from them), but has some specifics…

My local Department of Education has a public comment period for some proposed changes to Iowa’s science education standards.

Over at https://github.com/opengeospatial/geoparquet/discussions/251, we’re having a nice discussion about how best to partition geoparquet files for serving over object storage.

Here’s another Year in Books (I missed last year, but here’s 2022).

This post is a bit of a tutorial on serializing and deserializing Python dataclasses.

I wrote up a quick introduction to stac-geoparquet on the Cloud Native Geo blog with Kyle Barron and Chris Holmes.

I have, as they say, some personal news to share.

Ned Batchelder recently shared Real-world match/case, showing a real example of Python’s Structural Pattern Matching.

I wanted to share an update on a couple of developments in the STAC ecosystem that I’m excited about.

Last week, I was fortunate to attend Dave Beazley’s Rafting Trip course.

A few colleagues and I recently presented at the CIROH Training and Developers Conference.

Over in Planetary Computer land, we’re working on bringing Sentinel-5P into our STAC catalog.

Today, I was debugging a hanging task in Azure Batch.

The Planetary Computer made its January 2023 release a couple weeks back.

Over on the Planetary Computer team, we get to have a lot of fun discussions about doing geospatial data analysis on the cloud.

I came across a couple of new (to me) uses of queues recently.

It’s “Year in X” time, and here’s my 2022 Year in Books on GoodReads.

Mike Duncan is wrapping up his excellent Revolutions podcast.

Like some others, I’m getting back into blogging.

Some personal news: Last Friday was my last day at Anaconda.

As pandas’ documentation claims: pandas provides high-performance data structures.

Dask Summit Recap Last week was the first Dask Developer Workshop.

Compatibility Code Most libraries with dependencies will want to support multiple versions of that dependency.

This post describes the start of a journey to get pandas’ documentation running on Binder.

This post describes a few protocols taking shape in the scientific Python community.

Scikit-Learn 0.20.0 will contain some nice new features for working with tabular data.

This work is supported by Anaconda Inc.

The other day, I put up a Twitter poll asking a simple question: What’s the type of series.values?

This is part 1 in my series on writing modern idiomatic pandas.

This work is supported by Anaconda Inc and the Data Driven Discovery Initiative from the Moore Foundation. dask-ml 0.4.1 was released today with a few enhancements.

This is a status update on some enhancements for pandas.

This work is supported by Anaconda Inc and the Data Driven Discovery Initiative from the Moore Foundation.

This past week, I had a chance to visit some of the scikit-learn developers at Inria in Paris.

Today we released the first version of dask-ml, a library for parallel and distributed machine learning.

This work is supported by Anaconda, Inc. and the Data Driven Discovery Initiative from the Moore Foundation.

This work is supported by Anaconda, Inc. and the Data Driven Discovery Initiative from the Moore Foundation.

This work is supported by Anaconda Inc. and the Data Driven Discovery Initiative from the Moore Foundation.

I’m faced with a fairly specific problem: Compute the pairwise distances between two matrices $X$ and $Y$ as quickly as possible.

Today I released stitch into the wild.

This is part 7 in my series on writing modern idiomatic pandas.

This is part 6 in my series on writing modern idiomatic pandas.

This is part 5 in my series on writing modern idiomatic pandas.

This is part 3 in my series on writing modern idiomatic pandas.

This is part 4 in my series on writing modern idiomatic pandas.

This is part 2 in my series on writing modern idiomatic pandas.

This is part 1 in my series on writing modern idiomatic pandas.