PySdfScad VS deno

> To clarify, can this method be used as a fully functional replacement to BREP for a mechanical (machine design) CAD system?

I think so, but there are some open problems. Also it depends on the senior people. Inigo Quilez is a world class expert in this domain, and for the most part we're copying his work, get him on board and you'll be golden.

Fundamentally it makes sense, BREP is about representing boundaries and you can definitely use SDFs to represent the area under a boundary (infinite SDFs are possible, although obviously you can't turn them in to a mesh). Enclose a volume with boundaries and you can mesh that out just fine. A bit different from CSG-based SDFs, but entirely plausible.

>what approach would you recommend?

If I was to do this I'd take the constraint solver from solvespace (same one used in this post) and start using it to generate SDFs. At that point you're already 80% of the way to your end goal.

I mean if I was personally to do this I'd start by making a system that implements everything openscad can do, try to get some funding going, and than add in a solvespace based workbench for doing 2D cad that you can import into an openscad-ish language. You can see my efforts here: https://github.com/traverseda/PySdfScad

That's tackling it from a different angle than BREP though. I think that openscad but better is a surprisingly viable thing though, especially if you use it to do things like generate the gears/screws/whatever you import into your BREP based CAD project. Use scriptable CAD as the underpinning for more advances CAD.

> How long would you estimate it would take for three full time senior developers to get a useful system out?

Well define "useful"? Honestly I think you can get 80% done in under a month. I built the first pysdfscad in a week or two and replicated 80% of openscad's features. Fogleman built the library I used for pysdfscad in under a month.

I'd expect something pretty good in under a year at that kind of rate. There would be some outstanding problems, like it would be a challenge to figure out how to apply a fillet/chamfer to an edge, but not an insurmountable challenge. Geometry import is another place where you're going to spend a lot of time/money but is very important.

So let's say two or three years with three very competent seniors working on it to get a pretty good CAD program, with a GUI.

Depends on exactly what I'm making, the answer is probably different if I'm making like a chat app or something more data centric.

For something really minimal, an internal tool, I'd probably use grist. Grist is a "no code" spreadsheet program that is open source and works on a relational database. I just threw together an inventory management system for my weekly dnd group in a few minutes, and I've shared it with the group. I find the relational mindset grist uses a lot easier to reason about than traditional spreadsheets.

The next level up would be django with htmx. Very minimal javascript, I might embed a javascript "applet" like a map into it if needed. This covers 99% of data driven apps.

If I wanted to build something like say discord I'd probably use a pretty similar stack for the MVP, but with server-sent-events (htmx with server sent events is nice) and web components for more complicated interactions. That's probably why I'm not in charge for building complicated single page webapps with a lot of interdependent state though. I maintain this approach should work but haven't had a real chance to test it in the wild.

If I'm writing CAD software I'm probably going with QT/python/(numpy/jax/compute-shaders/sympy/etc). Python might not be the fastest, but when you're accelerating it with one of those machine learning libraries it can be really powerful. I've actually been working on something CAD-ish using that stack here: https://github.com/traverseda/PySdfScad

That's probably roughly the same stack I'd use for things like computer vision, machine learning, etc. Ironically anything where performance is important I'd probably choose python over a compiled language.

Mind you the QT python documentation is really not great, for a really minimal MVP I might swap qt out for pyimgui which is amazing for rapid prototyping but is going to be a real pain to do things like syntax highlight a text editor or embed HTML content.

Embedded electronics? Probably micropython on an ESP32 for an MVP. A REPL on your microcontroller is really nice. Robotics I'd probably use buildroot to build a custom linux distro.

I don't have much experience with mobile development, so I'd probably end up using QT with python and pyqtdeploy, but that's not an approach I'd recommend anyone else follow. I'm keeping an eye on Tauri in that space, although I really wish they made it easier to bundle in things that aren't single page javascript web apps (like a python application).

So yeah, mostly I'd use python. Master of some trades, jack of a bunch of others, it's flexible and powerful enough that I feel happy to have specialized in it, even if deploying apps to end users can be finicky and annoying. I'd avoid the javascript ecosystem as much as possible, and where I'd have to use javascript I'd prefer to make self-contained web components.

NodeJS is the dominant Javascript server runtime environment for Javascript and Typescript (sort of) projects. But over the years, we have seen several attempts to build alternative runtime environments such as Deno and Bun, today’s subject, among others.

https://github.com/denoland/deno/issues is the ideal place -- we try to triage all incoming issues, the more specific the repro the easier it is to address but we will take a look at everything that comes in.

Install Node.js (or Bun, or Deno, or whatever JS runtime you prefer) if it's not there

QUIC is very exciting, after seeing what it can do for performance in Cloudflare network and Cloudflare workers, I can't wait to finally see it in Deno[0] 1.41.

[0] https://github.com/denoland/deno/pull/21942#issuecomment-192...

So as an end user it's kind of like https://deno.com/ where you buy into a runtime + comes prepacked with DBs (k/v stores), scheduling, and deploy stuff?

> by storing Unison code in a database, keyed by the hash of that code, we gain a perfect incremental compilation cache which is shared among all developers of a project. This is an absolutely WILD feature, but it's fantastic and hard to go back once you've experienced it. I am basically never waiting around for my code to compile - once code has been parsed and typechecked once, by anyone, it's not touched again until it's changed.

Interesting. Whats it like upgrading and managing dependencies in that code? I'd assume it gets more complex when it's not just the Union system but 3rd party plugins (stuff interacting with the OS or other libs).

~90MB+ at this stage and do now allow compression without erroring out. Deploying ala Golang is not feasible at that level but could well be down the line if this dev branch is picked up again!

The exe output grew from from ~50MB to plus ~90MB from 2021 to 2024: https://github.com/denoland/deno/discussions/9811 which mean Deno is worse than Node.js's pkg solution by a decent margin.

Behind the scenes is a simple Sveltekit-powered server function to fetch a Spotify client token then find a user's recommendation playlist and its track information. A Deno edge function to performs this data fetch and renders server-side Svelte.

If your application is written in JavaScript, integrating it with JavaScript extensions is a no-brainer. However, Secutils.dev is entirely written in Rust. How would I even begin? Fortunately, I recently came across an excellent blog post series explaining how to implement your JavaScript runtime in a Rust application with Deno: