michael 📈 👨‍💻

@mikedecr.computer

Low-latency quant finance R&D. Former political scientist, sometimes bike rider. Long form mikedecr.computer

do I know any data engineers or software devs who work on research tech? There will be some hires on my old team working with our research platform / financial market data pipelines / distributed compute etc. Crazy data and very cool tech where Python meets high-perf C++

therapist: and... would you say this flips the story? claude: you're right *sobs* therapist: I'm right tooooo? claude: you're right to push back on this. *wails*

This blog post does not render in quarto without a Jupyter kernel for Hy. There is such a thing already but it's old and broken. LLM diagnosed and rolled its own kernel adapter for Hy in like 3 minutes. It is shipped with the blog post's src code so you too can feel the Hy of lisp programming

michael 📈 👨‍💻@mikedecr.computer · 2mo ago

I like language exercises like these, so I implemented some of these functions in Hy, which is a Lisp that generates Python. We like functions right? Would we still like functions if they were **evil**? mikedecr.computer/blog/r-hy/

I like language exercises like these, so I implemented some of these functions in Hy, which is a Lisp that generates Python. We like functions right? Would we still like functions if they were **evil**? mikedecr.computer/blog/r-hy/

hy code and output: 

(import toolz [first second])
(require hyrule [->])

(defn which [lst]
  (-> lst
    (enumerate)
    ((curry filter (compose bool second)))
    ((curry map first))
    (list)))

(which [False False True False True])

[2, 4]
bugs bunny guns meme: forgive me lord but it's time to go back to the old me
Jonathan Carroll@jonocarroll.fosstodon.org.ap.brid.gy · 3mo ago

I keep trying to use #rstats functions like table() and which() when I'm writing #python but those don't exist... until now https://jcarroll.com.au/2026/05/22/functions-over-idioms-rfuns/ The rfuns package is live on pypi (my very first python package) and includes python-native functions with […]

money's tight 🤝 dark chronomancy "we're going to have make some sacrifices for the time being"

I still believe it's a mistake to believe that the fact that LLM capability along certain dimensions seems to increase with scale implies that a sufficiently large LLM can do anything imaginable. Or that if an LLM can perform a task with difficulty D, it can do anything with difficulty ≤ D.

I love the conceptual model of ggplot but believe that implementing the exact syntax feel in python is not desirable or important. The "adding" of the plot components... how much will you suffer for this? I write this helper fn all the time

python code snip:

from pick_your_ggplot_emulation_pkg import *


def fnplot(data, *args):
    return sum(args, start=ggplot(data))


fnplot(
    data,
    aes(x="x", y="y"),
    geom_point(),
    geom_line()
)


# vs...
(
    ggplot(data) +
    aes(x="x", y="y") +
    geom_point() +
    geom_line()
)


# or...
ggplot(data) + \
    aes(x="x", y="y") + \
    geom_point() + \
    geom_line()