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.
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.
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.
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.
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.
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.
Python is the Arduino of software projects. It has a critical mass of libraries for anything from facial recognition and neural networks to robotics and remote sensing. And just like Arduino, I have yet to find the killer IDE for Python. Perhaps I just haven’t tried the right one yet, but it could be that I’m just doing Python wrong.
For Years I’ve Been IDLE
I’m a Linux-only type of a guy so using IDLE for Python is a natural fit. It’s in the repositories for super quick and easy install and there’s basically zero configuration to be done. Generally speaking my preferred development environment is text editor and command line compiler. IDLE is just one step above that. You get a separate window for the shell and each Python file you’re working on. Have IDLE run your code and it saves the file, then launches it in the shell window.
For me, there are two important features of IDLE’s shell. The first is that it keeps an interactive session open after you run your Python code. This means that any globals that your script uses are still available, and that you can experiment with your code by calling functions (and classes, etc) in real time. The second desirable feature is that while using this interactive shell, IDLE supports code completion and docstring support (it gives you hints for what parameters a function accepts/requires).
But simplicity has a tough time scaling. I’m working on larger and larger projects spread over many files and the individual nature of IDLE editor windows and lack of robust navigation has me looking to move forward.
I’ve tried perhaps a half-dozen different Python IDEs now, spending the most time on two of them: Geany and Atom. Both are easy to install on Linux and provide the more advanced features I want for larger projects: better navigation, cross-file code completion (and warnings), variable type and scope indication.
The look of Geany brings to mind an “IDE 1.0” layout style and theme. It’s the familiar three-pane layout that places symbols to the left, code to the right, and status along the bottom. When you run your program it launches in an interactive terminal, which I like, but you lose all IDE features at this point, which I despise. There is no code completion, and no syntax highlighting.
I have been using Atom much more than Geany and have grown to like it enough to stick with it for now. I’d call Atom the “IDE 2.0” layout. It launches with a dark theme and everything is a tab.
Atom depends heavily on packages (plugins that anyone may write). The package management is good, and the packages I’ve tried have been superb. I’m using autocomplete-python and tabs-to-spaces, but again I come up short when it comes to running Python files. I’ve tried platformio-ide-terminal, script, and runner plugins. The first brings up a terminal as a bottom pane but doesn’t automatically run the file in that terminal. Script also uses a bottom pane but I can’t get it to run interactively. I’m currently using runner which has an okay display but is not interactive. I’ve resorted to using a “fake” python file in my projects as a workaround for commands and tests I would normally run in the interactive shell.
Tell Us How You Python
It’s entirely possible I’ve just been using Python wrong all these years and that tinkering with your code in an interactive shell is a poor choose of development processes.
What do you prefer for your Python development? Does an interactive shell matter to you? Did you start with IDLE and move to a more mature IDE. Which IDE did you end up with and what kind of compromises did you make during that change. Let us know in the comments below.