Ben Matthews

As a kid, I learned to write i = i +1, before school maths taught me it can’t. The point is, computers do iteration well, especially to model dynamics of real non-linear systems, while classical maths is good at finding algebraic solutions to equilibria - typically more theoretical than real. Calculus is great for understanding repeatable dynamics - such as waves in physics, also integrating over some distributions. But even without knowing that well you could still approximate stuff numerically with simple loops, test it, and if an inner-loop turns out to be time-critical or accuracy-critical (most are not), ask a mathematical colleague to rethink it - believe in iteration rather than perfect solutions.

Indeed to use scala-native you’d need pure-scala libraries, but the core lib re-implements most java lib, and there are now small simple external libs available for common tasks like file management, database, etc. - for example check out the lihaoyi suite.
I mainly use scala-js (to make this) which was formerly a java app - as it compiles to both js and jvm (cross-project) can gradually convert stuff you already wrote. I’ve tried native for stuff like pre-processing data files.

Scala compiles either to native, js or jvm - obviously the IO / interface options vary between these envs, but the lang is the same. Recently Scala 3.5 incorporates a simple-to-use CLI which makes it easier to compile to native (or just run a small file as a script, or experiment with a repl), native binaries are small and fast, and there are some simple io libraries. Since you can also compile to jvm to interop with java, that might help with transition.

I now use Scala 3, and very happy with syntactic whitespace (combined with an intelligent compiler)

Scala-js is working on it - as its compiler design may facilitate this.
I haven’t yet tried (on todo list) and am not an expert, but bookmarked in passing:
recent github implementation, some history, following older discussion

I use vscode as I develop this model in Scala3, whose language-server ‘metals’ integrates well with vscode, and when scala3 was new in mid-21 this was the platform they first targeted. But the scala command-line tools do the clever analysis, vscode provides the layout, colours, git integration, search/regex, web-preview etc… Now considering other options (eg zed) as vscode too dependent on potentially unsafe extensions (of which too much choice), also don’t want M$ scraping my code. Long ago when same model was in java I used netbeans, then eclipse. Would prefer a pure-scala toolset.

Thanks, fixed! As you can see parts of the science code are already accessible via the ‘cogs’, but not yet the structural code - anyway keeps evolving, update soon.

Similar - I thought about codeberg for the source of my interactive climate model,
but am not yet ready to give it a pure-foss license - might split in parts with different licenses. Could try self-hosting.

I don’t buy this. I’m still using SMTP on my own domain and it’s working fine, a bit of spam but not unmanageable, real messages get read. Main challenge is digesting so many potentially-interesting list messages, indicating email’s continued dominance for professional topics. Seems this author has another agenda.
Having said that, it’s a pity the world never agreed a protocol for micro-payment for emails (and for many other services), which would resolve the spam problem, and not be a burden for honest users.

That’s great progress, thanks for all the work!
Glad to see enhanced federation with rest of fediverse - a small detail : the link for ‘Automatically includes a hashtag with new posts’ should point to pull #4533 (not #4398 ) - should help discoverability from mastodon, especially if community tags become customisable.

Hi, excuse me for replying so late, but i’ve been away from lemmy for.a while. Well, to summarise, the model calculates the future trajectories, of population, economy, emissions, atmospheric gases, and climate response etc., according to a set of (hundreds of) diverse options and uncertainties which you can adjust - the key feature is that the change shows rapidly enough to let you follow cause -> effect, to understand how the system responds in a quasi-mechanical way.
Indeed you are right, complexity is beautiful, but hard. A challenge with such tools is to adjust gradually from simple to complex. Although SWIM has four complexity levels, they are no longer systematically implemented - also what seems simple or complex varies depending where each person is coming from, so i think to adapt the complexity filter into a topic-focus filter. Much todo …

I can relate to this, having developed a coupled socio-emissions-carbon-climate model, which evolved for 20 years in java, until recently converted to scala3. You can have a look here. The problem is that “coupling” in such models of complex systems is a ‘good’ thing, as there are feedbacks - for example atmospheric co2 drives climate warming but the latter also changes the carbon cycle, demography drives economic growth but the latter influences fertility and migration, etc… (some feedbacks are solved by extrapolating from the previous timestep - the delay is anyway realistic). There are also policy feedbacks - between top-down climate-stabilisation goals, and bottom up trends and national policies, the choice affects the logical calculation order. All this has to work fast within the browser (now scala.js - originally java applet), responding interactively to parameter adjustments, only recalculating curves which changed - getting all these interactions right is hard.
If restarting in scala3 I’d structure it differently, but having a lot of legacy science code known to work, it’s hard to pull it apart. Wish I’d known such principles at the beginning, but as it grew gradually, one doesn’t anticipate such complexity.

One reason people stick on Lemmy and other fediverse communities, is the choice of quality over quantity (in this case - wrt comments). So quality over quantity could also apply to platforms like Codeberg. Github has so many abandoned student projects or forks going nowhere - maybe making the effort to look beyond the obvious is an indicator of serious (new) projects and contributors ?

I began programming java climate model with UK keyboard. When I moved to the continent, switched to swiss then belgian keyboard to better type emails/docs in french, but it was so tedious for code brackets {[()]} and some other punctuation, eventually switched back. Recently converted whole codebase to Scala 3 (here’s the model), now can drop most of those brackets. I speculate whether one motivation for creating scala3 (made in in Lausanne) was swiss/french keyboards.

I like Scala:

• multi-paradigm, you can explore many ways of doing something, within one codebase - arguably the most complex language, if you want, but doesn’t have to be: start simply, later scales robustly
• compiles and interoperates with JS, JVM, native
• Scala3 dropped brackets - easily readable like python
• great tooling (recently) - compiler infers so much -> less puzzles / testing
• developed mainly in europe, not controlled by big-tech

Fwiw, here’s my interactive climate system model running in pure scala.

Too true.
I still remember when java5 came out, many new features, great potential for a massive refactoring of my interactive climate model. Within that, I had an idea called “parallel worlds” for comparing scenarios, whereby for efficiency data was shared for parts of the system, and split across parts that varied as user adjusted parameters. So I pulled apart the whole codebase, and joined it back together again… - about two years later, by which time colleagues had given up interest.
[ story simplified to relate to point of OP - not only task in two years! ].
Now I develop a derivative climate system model in scala, but evidently it’s more interesting to develop some new complex part of the science code, than fix a graphical interface for beginners. But moods vary - some days lacking energy for refactoring, could be satisfied ticking off a few small tasks in a todo list. Yet after some time, brain craving for another big new complex idea…

In defence of the jack-of-all-trades, if everybody is a cog in the machine, nobody sees the overview of how the cogs could connect.
For what it’s worth, here’s an overview of some cogs made by a j-o-a-t, for whom software developer is just a sub-role, within understanding complex climate system.

Hi, thanks for the encouragement, delayed response due focusing on the code, and a related conference, and now trying to keep up with the COP. As it happens, the “ratchet” system of pledges created in Paris (COP21) is an iterative algorithm - start with wild guesses and gradually improve them by feedback - this made sense given the weaknesses of diplomacy, but it’s hard to summarise this mess with neat code in a compact model.

This principle works most but not all the time. I develop an interactive climate-system model that evolved with many small steps over 23 years. So it has many patchy fixes as climate policy structure changed, gases and sectors added etc. Then converted from java to scala module by module (out of ±50) , each step checking the plots looked as before. Result is it works, but parts are messy with legacy options and outdated code style. So sometimes it’s necessary to radically rethink the structure, take big bold steps before it works again, that’s hard. Scala strong type system, with hints from compiler (and “metals”) help make such refactoring easier.

Some of us will even remember when compilers ran on big central computers, and you might have to wait 15–30 minutes to find out if your code was syntactically correct (let alone if it worked.)

My father remembers when he wrote code printed on a set of punched cards, they traveled several hours on an evening train to a warehouse with a big government statistics computer (that was too busy during daytime), the result came back by train next morning. Syntax error? try again tomorrow…