Ben Matthews

Hmm. I’m still using a 2014 iMac, as its 27" 5k screen still very good for coding (with added memory). Sometimes develops a bunch of thin vertical lines, which come and go maybe dependent on temperature, but hasn’t changed for for ten years and i can live with those. Just wish they’d continue providing security updates for it.

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

Although not an expert on that specific country, I can be sure that ’ almost all ’ is very misleading, even if it gets a lot upvotes because people find it convenient to blame some big bad other. Even if you have specific data for electricity, don’t forget a lot of CO2 is emitted by cars, and also by fuel to heat homes (including some peat in special case of ireland - and in that country a large fraction of GHG emissions is also methane from agriculture).

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.

From the tasks described, it seems to me they were not measuring ‘Computer Skills’ as reasoning, patience, tenacity - people could have similar issues with similar tasks involving a pile of papers.

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.