✍ Blog Posts ✍

1. 2023-02-13: first day of recurse center

💐 Nice Things 💐

Plants for a Future

a database of edible plants

Help Yourself

nonprofit helping create public access food forests in western MA

East Bay Permanent Real Estate Cooperative

an inspiring model of using community control to prevent gentrification and create affordable resident controlled housing

Radical Homeownership Part 2

a v. fun video on some great alternative options on community stewardship

egg: e-graphs good

a cool tool to help build replacement systems without having to worry about rule order 😱.

🏡 Things I have worked on 🏡

Valley Housing Cooperative

a project with some friends to find a place to live, do fun things, and try something out

Plant Friends

an iOS app I started to help people become better friends with plants near them

metadsl

a library to use pattern matching and type analysis to build safe DSLs in Python, in order to allow scientific computing libraries to better collaborate and share key abstractions.

python-code-data

provides a friendly isomporphic representation of Python's bytecode objects

jupyterlab

an open source data science IDE in your browser. I was a core maintainor for a while and helped on a variety of extensions as well

lineapy

a python code analysis tool, which helps productionize data science code by building a DAG of python code

🔄 Links to Links 🔄

blog posts

my new blog posts on Github Discussions

old blog posts

my old blog posts on my previous statically generated website

🎭 Talks 🎭

April 28, 2020: Using Altair, Ibis, and Vega for interactive exploration of OmniSci

Altair is a lovely tool that lets you build up complex interactive charts in Python. Ibis is also a lovely tool that lets you use a Pandas, like API to compose SQL expressions in OmniSci and other backends. By tying them together you can use the familiar syntax of Pandas, combined with the expressive power of Vega and Vega Lite, to visualize large amounts of data stored in OmniSci. This talk will walk through a number of examples of using this pipeline and then go through how it works.

The OmniSci summer sessions

December 8, 2019: metadsl: separating API from execution

metadsl is a Python framework for writing APIs that are detached from how they are executed. With it we can be framework agnostic definitions of concepts like "arrays" and compile them to backends like Tensorflow or LLVM. In this talk, we will use metadsl to build high performance scientific computing libraries.

PyData Austin 2019

November 4, 2019: Same API, Different Execution

Can the Python data science and scientific computing ecoystem remain in the hands of community open source projects? Or will increasingly complex performance and hardware requirements leave room only for vertically integrated corporate sponsored projects?

PyData New York 2019

November 17, 2018: uarray - Efficient and Generic Array Computation

Efficient array computing is required to continue advances in fields like IoT and AI. We demonstrate a system, uarray, that does array computation generically and targets different backends. We rely on a Mathematics of Arrays, a theory of shapes and indexing, to reduce array expressions. As a result, temporary arrays and unneeded calculations are eliminated leading to minimal memory and CPU usage.

PyData Washington DC 2018

💌 Contact 💌

Feel free to reach out to me via email, twitter mastadon, or github.