A weird thing about being 50 is that there are programming languages that I've used regularly for longer than some of the software developers I work with have been alive. I first wrote BASIC code in the 1980s. The first time I wrote an expression evaluator--a fairly standard programming puzzle or homework--was in 1990. I wrote it in Pascal for an undergraduate homework assignment. I first wrote perl in the early 1990s, when it was still perl 4.036 (5.38.2 now). I first wrote java in 1995-ish, when it was still java 1.0 (1.21 now). I first wrote scala, which I still use for most things today, in 2013-ish, when it was still scala 2.8 (3.4.0 now). At various times I've been "fluent" in 8086 assembly, BASIC, C, Pascal, perl, python, java, scala; and passable in LISP/Scheme, Prolog, old school Mathematica, (early days) Objective C, matlab/octave, and R. I've written a few lines of Fortran and more than a few lines of COBOL that I ran in a production system once. I could probably write a bit of Haskell if pressed but for some reason I really dislike its syntax so I've never been enthusiastic about learning it well. I've experimented with Clean, Flix, Curry, Unison, Factor, and Joy and learned bits and pieces of each of those. I'm trying to decide whether I should try learning Idris, Agda, and/or Lean. I'm pretty sure I'm forgetting a few languages. Bit of 6502 assembly long ago. Bit of Unix/Linux shell scripting languages (old enough to have lived and breathed tcsh before switching to bash; I use fish now mostly).
When I say passable: in graduate school I wrote a Prolog interpreter in java (including parsing source code or REPL input), within which I could run the classic examples like append or (very simple) symbolic differentiation/integration. As an undergraduate I wrote a Mathematica program to solve the word recognition problem for context-free formal languages. But I'd need some study time to be able to write these languages again.
I don't know what the hell prompted me to reminisce about programming languages. I hope it doesn't come off as a humblebrag but rather like old guy spinning yarns. I think I've been through so many because I'm never quite happy with any one of them and because I've had a varied career that started when I was pretty young.
I guess I'm also half hoping to find people on here who have similar interests so I'm going to riddle this post with hashtags:
February's TIOBE index has #Fortran as the 11th most popular language, marking its 12th consecutive month in the top 20, beating languages like #Rust, #R, #MATLAB and #Julia. About time to do away with that "Fortran is ancient/dead/obsolete" myth?
“Local Functions: Define functions anywhere in scripts and live scripts”
”Python Interface: Convert between MATLAB tables and #Python#Pandas DataFrames”
The TIOBE Programming Community index is an indicator of the popularity of programming languages. This ranking is organized according to their popularity as of Sep 2023:
(1) Python
(2) C
(3) C++
(4) Java
(5) C#
(6) JavaScript
(7) Visual Basic
(8) PHP
(9) Assembly Language
(10) SQL
(11) Fortran
(12) Go
(13) MATLAB
(14) Scratch
(15) Delphi/Object Pascal
(16) Swift
(17) Rust
(18) R
(19) Ruby
(20) Kotlin
@r_ivorra
Yes, #Fortran stands for "Formula Translator". It is still one of the major language in the scientific field. But #Python has also been adopted a lot for computation (often using Fortran libraries) on the desktop. #Matlab is also using a lot of Fortran libraries. And there are also #C++ and #Julia.
Being a compiled language, Fortran programs can run fast, as C and C++.
For example, many climate models are written in Fortran or use Fortran libraries.
I used to be heavily invested in GNU #Octave, a free #Matlab replacement. That was a bit of a more ambitious goal, because Godot isn't trying to be exactly like Unity, but Octave is trying to be exactly like Matlab. The overall problem, however, is similar.
It's a difficult, mostly thankless task. Users don't care what it takes to make it look exactly like what it's supposed to be replacing. Photoshop users going to the GNU IMP, Matlab users going to Octave, Maya users going to Blender, Chrome users going to Firefox... they all want the same thing: basically the same software, but without the fees, restrictions, or anti-user misfeatures. It is extremely draining to continuously disappoint people who aren't getting exactly the same software but without paying for it.
A few users will offer donations, but never enough to rival the budget of the software they're fleeing from. Nowadays there's better infrastructure to collect from these benevolent donors and get a steady income than when I was working on Octave. This offers some hope.
All this to say: if you're migrating to better, less enshittified software, donate if you can. If you cannot, then at least try to be kind and considerate of the smaller, more grassroots organisation and individuals that are trying to give you a comparable experience with no strings attached. :)
Don't get me wrong, I love #Linux and ran it for about 3 years before being forced to go back to #Windows. Coming back to it recently has been a great joy.
But the pain of installing #Matlab and losing my entire #Factorio run recently really broke me.
Linux is fun, but the installation of software is often a pain, and I can see the barrier it would have for even my technical friends. The other thing is the weird instability I sometimes experience. Something like my software working great and then just crashing for days without changing anything.
Overall, it is fun for a developer, but I sometimes miss the fire and forget the ease of use I had with Windows and 90% of my #Steam library.
I had a lovely conversation with the #NWB devs yesterday. I messaged them cryptically like "hey can we talk about the history of this thing and the design decisions and constraints" and they were refreshingly candid and willing to engage with such a vague and open ended question. Formats and standards are always 100 times as complicated as they appear, and this one is this particularly heady mixture of neuroscientists riffing on something, computer scientists coming in later to be like "OK nice but let's make that work" and about a million rounds of historical baggage and iteration.
I freaking love finding ppl who care about what they do enough to hold it at arms length for a second to evaluate its history and the constraints it navigates. Good people, I like em.
One of the major sources of complexity in #NWB is actually a pretty interesting replay of blank nodes in #RDF / #SemanticWeb tech.
So you've got a complex type of thing where your thing not only has properties but those properties are themselves other things with their own properties. Concretely, say I've got some electrophysiological recording- that's a timeseries, yes, but it also has metadata like the electrode group that collected it. That electrode group has multiple electrodes, and each has its own properties like impedance, position, etc.
Neuroscientists would probably model this as a bigass nested untyped anonymous blob, one might call this the "cognitive style of #MATLAB structs." so that's where the format seems to have started...
When making choices 🤔, we often have to weigh up ⚖️ evidence before making a decision. New research shows EEG 🧠 can track the neural accumulation of evidence leading up to a decision.
Question for #Python#Programmers:
Getting tired of my #Spyder version that relies on different versions of Python modules than the ones I need for coding…
What is your favourite #IDE for Python (and why?)?
Consciousness is a key mystery of the brain🧠. New research decodes conscious awareness from brain activity patterns in frontal cortex, showing that responses in this area do not depend on observers reporting their perception.
Ever wonder how the brain keeps track of decisions? New research shows that information is transferred between LIP neurons to keep track of a target when gaze changes.
It is nice tradition to introduce yourself on #Mastodon. I am a geoscientist, studied #music, #geophysics, and #geology, and have a doctoral degree in #paleoceanography. My research is on the influence of climate in #Africa on human evolution using time series analysis methods. I learned #Fortran77 in the 1980s, have been using #MATLAB since 1992, and recently #Python - and have written several textbooks on data analysis in the earth sciences. I look forward to make new connections with you!