Linux Fu: Better Bash Scripting

It is easy to dismiss bash — the typical Linux shell program — as just a command prompt that allows scripting. Bash, however, is a full-blown programming language. I wouldn’t presume to tell you that it is as fast as a compiled C program, but that’s not why it exists. While a lot of people use shell scripts as an analog to a batch file in MSDOS, it can do so much more than that. Contrary to what you might think after a casual glance, it is entirely possible to write scripts that are reliable and robust enough to use in many embedded systems on a Raspberry Pi or similar computer.

I say that because sometimes bash gets a bad reputation. For one thing, it emphasizes ease-of-use. So while it has features that can promote making a robust script, you have to know to turn those features on. Another issue is that a lot of the functionality you’ll use in writing a bash script doesn’t come from bash, it comes from Linux commands (or whatever environment you are using; I’m going to assume some Linux distribution). If those programs do bad things, that isn’t a problem specific to bash.

One other limiting issue to bash is that many people (and I’m one of them) tend to write scripts using constructs that are compatible with older shells. Often times bash can do things better or neater, but we still use the older ways. For example:

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The Site Of A Hundred Languages

Silent film star [Lon Chaney] had the nickname “man of a thousand faces.”  The Try It Out website (tio.run) might well be the site of a hundred languages. Well, in all fairness, they only have 97 “practical” languages, but they do have 172 “recreational languages” but the site of 269 languages doesn’t trip off the tongue, does it? The site lets you run some code in each of those languages from inside your browser.

By the site’s definition, practical languages include things like C, Java, Python, and Perl. There’s also old school stuff like FOCAL-69, Fortran, Algol, and APL. There’s several flavors of assembly and plenty of other choices. On the recreational side, you can find Numberwang, LOLCODE, and quite a few we’ve never heard of.

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Using The GPU From JavaScript

Everyone knows that writing programs that exploit the GPU (Graphics Processing Unit) in your computer’s video card requires special arcane tools, right? Well, thanks to [Matthew Saw], [Fazil Sapuan], and [Cheah Eugene], perhaps not. At a hackathon, they turned out a Javascript library that allows you to create “kernel” functions to execute on the GPU of the target system. There’s a demo available with a benchmark which on our machine sped up a 512×512 calculation by well over five times. You can download the library from the same page. There’s also a GitHub page.

The documentation is a bit sparse but readable. You simply define the function you want to execute and the dimensions of the problem. You can specify one, two, or three dimensions, as suits your problem space. When you execute the associated function it will try to run the kernels on your GPU in parallel. If it can’t, it will still get the right answer, just slowly.

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Don’t Be A Code Tyrant, Be A Mentor

Hardware hacking is a way of life here at Hackaday. We celebrate projects every day with hot glue, duct tape, upcycled parts, and everything in between. It’s open season to hack hardware. Out in the world, for some reason software doesn’t receive the same laissez-faire treatment. “Too many lines in that file” “bad habits” “bad variable names” the comments often rain down. Even the unsafest silliest of projects isn’t safe. Building a robot to shine lasers into a person’s eyes? Better make sure you have less than 500 lines of code per file!

Why is this? What makes readers and commenters hold software to a higher standard than the hardware it happens to be running on? The reasons are many and varied, and it’s a trend I’d like to see stopped.

Software engineering is a relatively young and fast evolving science. Every few months there is a new hot language on the block, with forums, user groups, and articles galore. Even the way software engineers work is constantly changing. Waterfall to agile, V-Model, Spiral model. Even software design methodologies change — from pseudo code to UML to test driven development, the list goes on and on.

Terms like “clean code” get thrown around. It’s not good enough to have software that works. Software must be well commented, maintainable, elegant, and of course, follow the best coding practices. Most of these are good ideas… in the work environment. Work is what a lot of this boils down to. Software engineers have to stay up to date with new trends to be employable.

There is a certain amount of “born again” mentality among professional software developers. Coders generally hate having change forced upon them. But when they find a tool or system they like, they embrace it both professionally, and in their personal projects. Then they’re out spreading the word of this new method or tool; on Reddit, in forums, to anyone who will listen. The classic example of this is, of course, editors like the vi vs emacs debate.

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AI Generates Color Palettes; Has Remarkably Good Taste

Color palettes are key to any sort of visual or graphic design. A designer has to identify a handful of key colours to make a design work, making calls on what’s eye catching or what sets the mood appropriately. One of the problems is that it relies heavily on subjective judgement, rather than any known mathematical formula. There are rules one can apply, but rules can also be artistically broken, so it’s never a simple task. To this end, [Jack Qiao] created colormind.io, a tool that uses neural nets to generate color palettes.

It’s a fun tool – there’s a selection of palettes generated from popular media and sunset photos, as well as the option to generate custom palettes yourself. Colours can be locked so you can iterate around those you like, finding others that match well. The results are impressive – the tool is able to generate palettes that seem to blend rather well. We were unable to force it to generate anything truly garish despite a few attempts!

The blog explains the software behind the curtain. After first experimenting with a type of neural net known as an LSTM, [Jack] found the results too bland. The network was afraid to be wrong, so would choose values very much “in the middle”, leading to muted palettes of browns and greys. After switching to a less accuracy-focused network known as a GAN, the results were better – [Jack] says the network now generates what it believes to be “plausible” palettes. The code has been uploaded to GitHub if you’d like to play around with it yourself.

Check out this primer on neural nets if you’d like to learn more. We’d like to know – how do you pick a palette when starting a project? Let us know in the comments.

A ‘Do Not Disturb’ Digital Assistant

Flow requires a certain amount of focus, and when that concentration is broken by pesky colleagues, work can suffer, on top of time wasted attempting to re-engage with the task at hand. The Technical Lead in [Estera Dezelak]’s office got fed up with being interrupted, and needed his own personal assistant to ward off the ‘just one question’-ers.

Initially, [Grega Pušnik] — the tech lead — emailed the office his schedule and blocked out times when he wasn’t to be disturbed, with other developers following suit. When that route’s effectiveness started to wane, he turned the product he was working on — a display for booking meeting rooms — into his own personal timetable display with the option to book a time-slot to answer questions. In an office that  is largely open-concept — not exactly conducive to a ‘do not disturb’ workstation — it was a godsend.

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FlowCode Graphical Programming

If you’ve ever been curious if there’s a way to program microcontrollers without actually writing software, you might be interested in FlowCode. It isn’t a free product, but there is a free demo available. [Web learning] did a demo of programming a Nucleo board using the system. You can check it out below.

The product looks slick and it supports a dizzying number of processors ranging from AVR (yes, it will do Arduino), PIC, and ARM targets. However, the pricing can add up if you actually want to target all of those processors as you wind up paying for the CPU as well as components. For example, the non-commercial starter pack costs about $75 and supports a few popular processors and components like LEDs, PWM, rotary encoders, and so on.

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