Black Box is a GTK4 Terminal App With Unique Look

Tired of the standard GNOME Terminal but cool on its successor Console? You’ll definitely want to check in with Black Box. Black Box is a new GTK4 terminal emulator built in Vala and GTK4. The debutant release on Flathub has all of the core features you’d expect, plus a large dose of ones you might not. Yes, this app has a few innovative UI approaches that make it stand out from the (many) terminal apps already available for Linux desktops. I do think of Black Box as the “eye candy terminal”. It may sound like contradiction given that CLIs are usually focused on raw function (and it may sound like a negative, but it’s not; things are allowed to look nice). Thing is, Black Box isn’t afraid to be ‘beautiful’, as its immersive ‘headerbar-less’ mode proves. When enabled this gives every inch of the console’s canvas over to whatever command is running.

Linux 5.19-rc5

So last week, we had a rc4 that was slightly larger than normal, and
while I thought it was mostly just due to timing and pull requests
shifting between rc's, I wanted to keep an eye on it.

And this week, we have an rc5 that is slightly _smaller_ than normal,
so it all pans out and really does just look like just random timing
noise.

So everything looks ok - we certainly have some issues still being
looked at, but on the whole 5.19 looks normal, and nothing
particularly bad seems to be going on.

See the shortlog below for details, but nothing here looks very odd.
It's the usual mixture of driver fixes, arch updates, filesystems and
networking. And associated tooling and selftests.

The diffstat shows a couple of blips - random number handling fix and
simplification in s390, a couple drivers, and some patches to fs code
that are not exactly one-liners (copy_file_range fix, some xfs fixes),
and some mptcp fixes.  But none of it is huge by any means, and most
of the rest of commits are one- or few-liners.

So in between the general summer vacation (Europe) and the July 4th
extended weekend (US), and whatever the rest of the world is doing -
take some time off, build a new kernel and boot it. Just to verify
things are looking ok for you. But it should all be pretty calm.

             Linus

today's leftovers

• RFID and Raspberry PI: RC522 wiring and code with Python

  RFID systems are common in our lives as they are widely used to secure access, monitor objects’ positions (IoT) and a lot of other applications. Their technology is so mature that they are today reliable components and easy to use. The RC522 module with Raspberry PI can bring to your hands this technology with a few steps and a cheap budget In this tutorial, I’m going to show you how to connect and configure a Raspberry PI with an RFID RC522 module, using Python.

• This DIY basketball scoreboard looks and sounds like the real thing | Arduino Blog

  Inspired by his time as a scorekeeper in elementary school, now-high schooler Collin Wentzien wanted to recreate this setup by building a DIY scoreboard several years ago. His idea involved making a bright display composed of several seven-segment displays that could all be controlled by an external device in order to set scores, start/stop the clock, and more. The controller sits inside of a small custom box that contains a pair of button matrices, which either increment the score for the home/guest team or provides a keypad that can be used to enter numerical values and set the clock. Below its custom PCB is an Arduino Mega 2560 that handles all of the button inputs, along with a character LCD for showing what has been entered and an nRF24L01+ wireless transceiver for sending new data to the scoreboard.

• What Metric to Use When Benchmarking?

  What is the right metric to use when measuring a program's performance? There are various possibilities, from memory usage to branch prediction hit rates, but I'm going to pick on two that I see widely used: CPU instructions executed (what modern CPUs call "instructions retired") and wall-clock time (i.e. "how much time has elapsed in the real world?"). In this post, I'm going to try and compare both, showing why each has fundamental weaknesses, before explaining why I use each in different circumstances.

• Linux Weekly Roundup #189

  Welcome to this week's Linux Weekly Roundup. We had a full week in the world of Linux releases with ArcoLinux 22.07.03, Nitrux OS 20220629, Pisi Linux 2.3, and Condres OS 1.0.

• What if WordPress Didn’t Exist?

  WordPress powers like 40% of the internet or something, so I don’t think it will be going anywhere anytime soon. But what if Matt and the team decide to go in a direction I don’t agree with, like Ghost have? My knee-jerk reaction would be to go back to Jekyll – it’s light and I know it fairly well. But like I said, managing content is painful and Ruby can be a bit of pig to manage.

Programming Leftovers

• A Major Contribution to Learning R

  Prominent statistician Frank Harrell has come out with a radically new R tutorial, rflow. The name is short for “R workflow,” but I call it “R in a box” –everything one needs for beginning serious usage of R, starting from little or no background. By serious usage I mean real applications in which the user has a substantial computational need. This could be a grad student researcher, a person who needs to write data reports for her job, or simply a person who is doing personal analysis such as stock picking. Like other tutorials/books, rflow covers data manipulation, generation of tables and graphics, etc. But UNLIKE many others, rflow empowers the user to handle general issues as they inevitably pop up, as opposed to just teaching a few basic, largely ungeneralizable operations. I’ve criticized the tidyverse in particular for that latter problem, but really no tutorial, including my own, has this key “R in a box” quality.

• The deep learning obesity crisis - Vincent Lequertier's blog

  Deep learning have made dramatic improvements over the last decades. Part of this is attributed to improved methods that allowed training wider and deeper neural networks. This can also be attributed to better hardware, as well as the development of techniques to use this hardware efficiently. All of this leads to neural networks that grow exponentially in size. But is continuing down this path the best avenue for success? Deep learning models have gotten bigger and bigger. The figure below shows the accuracy of convolutional neural networks (left) and the size and number of parameters used for the Imagenet competition (right). While the accuracy is increasing and reaching impressive levels, the models get both bigger and use more and more resources. In Schwartz et al., 2020, as a result of rewarding more accuracy than efficiency, it is stated that the amount of compute have increased 300k-fold in 6 years which implies environmental costs as well as increasing the barrier to entry in the field.

• Mint: A New Programming Language for Building Single Page Apps (SPAs)

  Mint is a refreshing programming language for the front-end web development. It is developed and maintained by a large community of experienced developers.

• Understanding Have I Been Pwned's Use of SHA-1 and k-Anonymity

  Four and a half years ago now, I rolled out version 2 of HIBP's Pwned Passwords that implemented a really cool k-anonymity model courtesy of the brains at Cloudflare. Later in 2018, I did the same thing with the email address search feature used by Mozilla, 1Password and a handful of other paying subscribers. It works beautifully; it's ridiculously fast, efficient and above all, anonymous.