Tootfinder

So #Gentoo #Python eclasses are pretty modern, in the sense that they tend to follow the best practices and standards, and eventually deal with deprecations. Nevertheless, they have a long history and carry quite some historical burden, particularly regarding to naming.
The key point is that the eclasses were conceived as a replacement for the old eclasses: "distutils" and "python". Hence, much like we revision ebuilds, I've named the matching eclasses "distutils-r1" and "python-r1". For consistency, I've also used the "-r1" suffix for the remaining eclasses introduced at the time: "python-any-r1", "python-single-r1" and "python-utils-r1" — even though there were never "r0"s.
It didn't take long to realize my first mistake. I've made the multi-impl eclass effectively the "main" eclass, probably largely inspired by the previous Gentoo recommendations. However, in the end I've found out that for the most use cases (i.e. where "distutils-r1" is not involved), there is no real need for multi-impl, and it makes things much harder. So if I were naming them today, I would have named it "python-multi", to indicate the specific use case — and either avoid designating a default at all, or made "python-single" the default.
What aged even worse is the "distutils-r1" eclass. Admittedly, back when it was conceived, distutils was still largely a thing — and there were people (like me) who avoided unnecessary dependency on setuptools. Of course, nowadays it has been entirely devoured by setuptools, and with #PEP517 even "setuptools" wouldn't be a good name anymore. Nowadays, people are getting confused why they are supposed to use "distutils-r1" for, say, Hatchling.
Admittedly, this is something I could have done differently — PEP517 support was a major migration, and involved an explicit switch. Instead of adding DISTUTILS_USE_PEP517 (what a self-contradictory name) variable, I could have forked the eclass. Why didn't I do that? Because there used to be a lot of code shared between the two paths. Of course, over time they diverged more, and eventually I've dropped the legacy support — but the opportunity to rename was lost.
In fact, as a semi-related fact, I've recognized another design problem with the eclass earlier — I should have gone for two eclasses rather than one: a "python-phase" eclass with generic sub-phase support, and a "distutils" (or later "python-pep517") implementing default sub-phases for the common backends. And again, this is precisely how I could have solved the code reuse problem when I introduced PEP517 support.
But then, I didn't anticipate how the eclasses would end up looking like in the end — and I can't really predict what new challenges the Python ecosystem is going to bring us. And I think it's too late to rename or split stuff — too much busywork on everyone.

This https://arxiv.org/abs/2312.16139 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Abnormal component analysis
At the crossway of machine learning and data analysis, anomaly detection aims at identifying observations that exhibit abnormal behaviour. Be it measurement errors, disease development, severe weather, production quality default(s) (items) or failed equipment, financial frauds or crisis events, their on-time identification and isolation constitute an important task in almost any area of industry and science. While a substantial body of literature is devoted to detection of anomalies, little att…

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SmartGuard: Leveraging Large Language Models for Network Attack Detection through Audit Log Analysis and Summarization
Hao Zhang, Shuo Shao, Song Li, Zhenyu Zhong, Yan Liu, Zhan Qin, Kui Ren
https://arxiv.org/abs/2506.16981

SmartGuard: Leveraging Large Language Models for Network Attack Detection through Audit Log Analysis and Summarization
End-point monitoring solutions are widely deployed in today's enterprise environments to support advanced attack detection and investigation. These monitors continuously record system-level activities as audit logs and provide deep visibility into security events. Unfortunately, existing methods of semantic analysis based on audit logs have low granularity, only reaching the system call level, making it difficult to effectively classify highly covert behaviors. Additionally, existing works main…

I guess the US Army can't defend itself and needs a fence to protect its tanks from the public that paid for those tanks.
"DC prepares for Trump’s military parade with 18 miles of fencing and 175 magnetometers"
I guess this is a second TACO - The Army Chickens Out.

DC prepares for Trump's June 14 military parade
As Washington, D.C., cleans up from the weekend’s culmination of World Pride, the capital city’s focus now shifts straight into a very different mass event — the June 14 military parade to honor the 250th birthday of the army and the 79th birthday of President Donald Trump. Army officials have estimated around 200,000 attendees for the evening military parade. More than 18 miles of security fencing will be erected and 175 magnetometers will be deployed at security checkpoints for the birt…

Search for very-high-energy photon clusters and transients outside the galactic plane in the Fermi-LAT data
M. S. Pshirkov, A. S. Kovankin
https://arxiv.org/abs/2506.12833

Search for very-high-energy photon clusters and transients outside the galactic plane in the Fermi-LAT data
We present a search for spatio-temporal clusters in 16 years of Fermi-LAT very high-energy (VHE; $E>100$ GeV) data using the DBSCAN algorithm, focusing on high Galactic latitude ($|b|>10^{\circ}$) clusters with $\geq5$ events and transient doublets (two events within $\leq 3$ days). Of 107 detected clusters, two correspond to previously unidentified VHE sources: weak BL Lacertae objects 4FGL J0039.1-2219 and 4FGL J0212.2-0219, promising targets for next-generation VHE observatories. D…

$B\rightarrow K \text{axion-like particles}$: effective versus UV-complete models and enhanced two-loop contributions
Xiyuan Gao, Ulrich Nierste
https://arxiv.org/abs/2506.14876

$B\rightarrow K + \text{axion-like particles}$: effective versus UV-complete models and enhanced two-loop contributions
An axion-like particle $a$ (ALP) can explain the excess of $B\rightarrow K + \text{invisible}$ events at Belle-II. However, many analyses of ALP scenarios are over-simplified. We revisit the $B\rightarrow K a$ transition rate in a popular minimal and UV complete model with two Higgs doublets (2HDM) and a complex singlet (DFSZ model). To this end we compare our results with previous studies which derived the $\overline{b}sa$ vertex from the $\overline{b}sA$ vertex, where $A$ is the heavy pseudo-…

Disaster Risk Financing through Taxation: A Framework for Regional Participation in Collective Risk-Sharing
Fallou Niakh, Arthur Charpentier, Caroline Hillairet, Philipp Ratz
https://arxiv.org/abs/2506.18895

Disaster Risk Financing through Taxation: A Framework for Regional Participation in Collective Risk-Sharing
We consider an economy composed of different risk profile regions wishing to be hedged against a disaster risk using multi-region catastrophe insurance. Such catastrophic events inherently have a systemic component; we consider situations where the insurer faces a non-zero probability of insolvency. To protect the regions against the risk of the insurer's default, we introduce a public-private partnership between the government and the insurer. When a disaster generates losses exceeding the tot…

NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning
Ashish Gautam, Prasanna Date, Shruti Kulkarni, Robert Patton, Thomas Potok
https://arxiv.org/abs/2506.14138

NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning
Spiking Neural Networks (SNNs) are computational models inspired by the structure and dynamics of biological neuronal networks. Their event-driven nature enables them to achieve high energy efficiency, particularly when deployed on neuromorphic hardware platforms. Unlike conventional Artificial Neural Networks (ANNs), which primarily rely on layered architectures, SNNs naturally support a wide range of connectivity patterns, from traditional layered structures to small-world graphs characterize…

In other news, I've sent a few fun patches to improve epytest in #Gentoo.
This includes forcing short summaries, creating junit .xml for machine processing, and most importantly, EPYTEST_PLUGINS to handle specifying the plugins to load. The goal is to eventually move away from plugin autoloading by default.
#PyTest #Python