I'm making this thing called BDServer for my website blenderdumbass . org and I am coding some analytics tools for it right now, because apparently I found a new way to procrastinate.

I made some of the calls accessible to the public:

https://blenderdumbass.org/json/analytics/ua?days=10&skip_me=True&human_only=True

https://blenderdumbass.org/json/analytics/rss?days=10

https://blenderdumbass.org/json/analytics/totals

And also made a UI version: https://blenderdumbass.org/analytics

Am I going crazy?

After needing to find a small delimiter for my data format I started wondering if I could use 0x1E-0x1F?

They are part of the control codes so I thought they might do something weird?

https://en.wikipedia.org/wiki/C0_and_C1_control_codes#Field_separators

I'm creating a JavaScript UI framework for my own projects. It's a learning journey and I'd like to share my progress.

I've written some blog posts about my progress so far:

1. Functional Web Components - https://positive-intentions.com/blog/dim-functional-webcomponents
2. Functional Todo App - https://positive-intentions.com/blog/dim-todo-list
3. Async State Management - https://positive-intentions.com/blog/async-state-management
4. Bottom-up Browser Storage - https://positive-intentions.com/blog/bottom-up-storage

Note: The UI framework is far from finished. I want to share progress to see if there are any outstanding issues I'm overlooking.

cross-posted from: https://beehaw.org/post/17683690

Archived version

Download study (pdf)

GitHub, the de-facto platform for open-source software development, provides a set of social-media-like features to signal high-quality repositories. Among them, the star count is the most widely used popularity signal, but it is also at risk of being artificially inflated (i.e., faked), decreasing its value as a decision-making signal and posing a security risk to all GitHub users.

A recent paper by Cornell University published on Arxiv, the researchers present a systematic, global, and longitudinal measurement study of fake stars in GitHub: StarScout, a scalable tool able to detect anomalous starring behaviors (i.e., low activity and lockstep) across the entire GitHub metadata.

Analyzing the data collected using StarScout, they find that:

(1) fake-star-related activities have rapidly surged since 2024

(2) the user profile characteristics of fake stargazers are not distinct from average GitHub users, but many of them have highly abnormal activity patterns

(3) the majority of fake stars are used to promote short-lived malware repositories masquerading as pirating software, game cheats, or cryptocurrency bots

(4) some repositories may have acquired fake stars for growth hacking, but fake stars only have a promotion effect in the short term (i.e., less than two months) and become a burden in the long term.

The study has implications for platform moderators, open-source practitioners, and supply chain security researchers.

Try it yourself: https://codeburg.org

The actual site is https://codeberg.org

Edit: sorry I was making a baseless claim in the title. I dont have proof that Microsoft did it. Here's the whois for what information is actually known.

I created a solution...with a pi 4 but it just doesn't seem to work very well. OCR is very finicky and while I was able to get pytesseract to pull the images off of a webcam, the numbers that get returned are very wrong. It looks like they only allow businesses to pull the powermeter data if I am reading this right: https://www.pge.com/en/save-energy-and-money/energy-saving-programs/smartmeter.html

My rate has increased 6 times this year, so power is very expensive here: 50c per KWH...on the lowest consumption rate. I need to figure out how to cut back or get solar panels. But I want to see in near real time how much energy we are using.

When learning a new programming language, there’s only one place to start. Let’s take a look at a Hello World channel!

DRY = Don't repeat yourself

cross-posted from: https://lemmy.ml/post/23785552

After nearly 2 years of work, I'm excited to release the first version of bjForth, featuring partial JONESFORTH compatibility and initial Java interop.

Grab it and start hacking: https://github.com/bahmanm/bjforth/releases/tag/v0.0.2

PS: bjForth is a Forth (indirect threaded) written entirely in Java and its execution model is influenced by that of JONESFORTH.

Lots of new features being added.

But the most interesting part is that they seem to want to change the configuration format from JS to using a CSS.

Youtube

cross-posted from: https://lemmy.ml/post/23703703

Hey all.

First off, bjForth is a Forth written from the ground up with modern Java and its execution model is largely influenced by that of JONESFORTH.

Currently I'm working on Java inter-op and would like to ask for your opinions/experience on semantics and syntax.

The relevant GitHub issue.

Thanks in advance.

It was merged after they where rightfully ridiculed by the community.

The awful response to the backlash by matwojo really takes the cake:

I've learned today that you are sensitive to ensuring human readability over any concerns in regard to AI consumption

Hi all, I have been pretty frustrated with how I had to bring together bunch of different tools together, so I built a CLI tool that brings together data ingestion, data transformation using SQL and Python and data quality in a single tool called Bruin:

https://github.com/bruin-data/bruin

Bruin is written in Golang, and has quite a few features that makes it a daily driver:

it can ingest data from many different sources using ingestr it can run SQL & Python transformations with built-in materialization & Jinja templating it runs Python fully locally using the amazing uv, setting up isolated environments locally, mix and match Python versions even within the same pipeline it can run data quality checks against the data assets it has an open-source VS Code extension that can do things like syntax highlighting, lineage, and more. We had a small pool of beta testers for quite some time and I am really excited to launch Bruin CLI to the rest of the world and get feedback from you all. I know it is not often to build data tooling in Go but I believe we found ourselves in a nice spot in terms of features, speed, and stability.

Looking forward to hearing your feedback!