Tootfinder

from my link log —
I don't like NumPy.
https://dynomight.net/numpy/
saved 2025-05-16 https://dotat.at/:/WXM12.html

I don’t like NumPy
it’s too hard

What I've planned to be doing: adding CPU_FLAGS_* support to #NumPy package in #Gentoo.
What I am doing instead: digging through #ARM documentation, kernel sources, NumPy sources to figure out what's missing from CPU_FLAGS_ARM and how to detect it.

Czym miałem się zajmować: dodawaniem wsparcia CPU_FLAGS_* do paczek #NumPy w #Gentoo.
Czym się zajmuję: przegrzebywaniem dokumentacji #ARM, źródeł jądra, źródeł NumPy, by ogarnąć brakujące flagi w CPU_FLAGS_ARM i sposó…

Fast Capture of Cell-Level Provenance in Numpy
Jinjin Zhao, Sanjay Krishnan
https://arxiv.org/abs/2506.18255 https://arxiv.org/pdf/25…

Fast Capture of Cell-Level Provenance in Numpy
Effective provenance tracking enhances reproducibility, governance, and data quality in array workflows. However, significant challenges arise in capturing this provenance, including: (1) rapidly evolving APIs, (2) diverse operation types, and (3) large-scale datasets. To address these challenges, this paper presents a prototype annotation system designed for arrays, which captures cell-level provenance specifically within the numpy library. With this prototype, we explore straightforward memor…

"Vibe coding" is one of the dumbest ideas that I've heard in a long time.
Yes, there are often reasons to use tools (such as Knuth's books) to lookup methods. And well established and tested libraries are great. (Thank you "numpy".)
But "vibe coding" just turns programmers into little more than proofreaders - proofreading complex and often boring material. That is putting the cart before the horse. (Is there a modern phrase for that adage?…

An AI-powered coding tool wiped out a software company’s database, then apologized for a ‘catastrophic failure on my part’
An experiment with an AI coding tool took a disastrous turn when an AI agent reportedly deleted a live company database during an active code freeze.

Very interesting origin story of Scipy/Numpy which is the foundation of so much #ML stuff and why Python became the dominant language for ML / #AI.
https://www.youtube.com/watch?v=-xhai2iu_QY

Resolvent4py: a parallel Python package for analysis, model reduction and control of large-scale linear systems
Alberto Padovan, Vishal Anantharaman, Clarence W. Rowley, Blaine Vollmer, Tim Colonius, Daniel J. Bodony
https://arxiv.org/abs/2506.20539

Resolvent4py: a parallel Python package for analysis, model reduction and control of large-scale linear systems
In this paper, we present resolvent4py, a parallel Python package for the analysis, model reduction and control of large-scale linear systems with millions or billions of degrees of freedom. This package provides the user with a friendly Python-like experience (akin to that of well-established libraries such as numpy and scipy), while enabling MPI-based parallelism through mpi4py, petsc4py and slepc4py. In turn, this allows for the development of streamlined and efficient Python code that can b…

Statistical Quality and Reproducibility of Pseudorandom Number Generators in Machine Learning technologies
Benjamin A. Antunes (LIRMM | DALI)
https://arxiv.org/abs/2507.03007 ht…