flecs VS Node RED

I've also been enjoying building My First Game™ in Bevy using ECS. The community around Bevy really shines, but Flecs (https://github.com/SanderMertens/flecs) is arguably a more mature, open-source ECS implementation. You don't get to write in Rust, though, which makes it less cool in my book :)

I'm not very proud of the code I've written because I've found writing a game to be much more confusing than building websites + backends, but, as the author notes, it certainly feels more elegant than OOP or globals given the context.

I'm building for WASM and Bevy's parallelism isn't supported in that context (yet? https://github.com/bevyengine/bevy/issues/4078), so the performance wins are just so-so. Sharing a thread with UI rendering suuucks.

If anyone wants to browse some code or ask questions, feel free! https://github.com/MeoMix/symbiants

Flecs does just that: https://ajmmertens.medium.com/why-it-is-time-to-start-thinking-of-games-as-databases-e7971da33ac3

I'm trying to optimize my workflow as much as possible, and came across this thing called an ECS. After doing a little bit more digging I found some decent guides on how you would make one, I also found one premade called FLECS. FLECS is nice and all, but I was looking for something more simple that just has the bare bones of what I need and is also configurable. I haven't been able to really find anything like that, so I was wondering if anyone had an example of maybe their way of implementing an ECS. I know how to go about it, but I'm unsure of exactly what the code would look like.

Since we wanted a common game simulation that would be on both the server and the client we looked into a few libraries that would fit our ECS needs. It was decided we were going to write this common part of our game in C++, but rust was considered. C++ was a familiar language for us so naturally EnTT and flecs came up right away. I had used EnTT before, writing some small demo projects, so our choice was made based on familiarity. In order to integrate with Unity we created a small C interface to communicate between our simulation code and Unity’s C#. Here’s close to what it looked like. I removed some parts for brevity sake.

Repository: https://github.com/SanderMertens/flecs

This is the project: https://github.com/SanderMertens/flecs (query engine implementation lives here: https://github.com/SanderMertens/flecs/tree/master/src/addons/rules)

There's also a performance question. While we can now use Blueprint nativization to convert Blueprints to C++ the result will be a fairly naive version, fast enough for most purposes but not if you're trying to push every bit of performance. This is where you're looking at making sure you're hitting things such as using the CPU cache as well as possible for an ECS system (Look at ENTT or Flecs if you want to see what they're about and why you'd want one), or a system needing to process massive amounts of data quickly such as the Voxel Plugin.

If I knew C++ and I'd heard about it before I started my current project, I would have been tempted to use this https://github.com/SanderMertens/flecs which can be built to WASM. Of course you still need JavaScript in the front end to link to the WASM part. I've recently been using esbuild to bundle my front end code, which does a pretty similar job to webpack, but is a bit faster.

When do think bevy will support entity-entity relationships ? https://github.com/bevyengine/bevy/issues/3742.

Flecs ECS already supports this: https://github.com/SanderMertens/flecs/blob/master/docs/Rela...

For a modern engine you’re probably best looking at Unity’s DOTS. You may also want to check out some of the different open source ECS libraries such as flecs and EnTT are two popular ones for C++, but there’s lots of them. Largely you’ll see lots of different approaches taken, all with their own pros and cons. Not all of them will be performant (some focus more on the design benefits) while others will be optimised for certain use cases. What you should prioritise will depend on your specific needs.

Good question.

I expect that we're moving into a phase of AIs talking to AIs, and initially it'll be wasteful (because it'll be mostly English), but eventually, they'll derive their own language and seamlessly upgrade protocols when they determine they're talking to an AI. No clue how that will come about or what that language will look like, but honestly, it's kind of exciting.

Really interesting to think about how they might handle context, as well. Even though we have much bigger context windows (and they'll only get larger), context management is still a resource-management issue, which we'll probably continue to refine, as well. Imagine different strategies for managing both what is brought into the context of each request, as well as what form it could take (level of detail, additional references or commentary on it, etc). Things could get really unreadable even in English, and still be very interpretable for an LLM.

W.r.t. the graph-oriented interfaces, are you thinking something like Node-RED [1]? I'm seeing more and more people mention having LLMs produce non-text or structured outputs, like JSON, UI, and other things. Easy to imagine an LLM that wires together various open-source platforms, on-demand. Something like Node-RED for pipelines/functions, some UI tools for visualization/interactivity, other platforms for messaging, etc...

[1] https://nodered.org/

I skipped to chapter 9 in the article ("Clogged"), and it looked like Pipes failed because it didn't have a large enough team or a well-defined mission. As a result they couldn't offer a super robust product that would lure in enterprise users. "You could not purchase some number of guaranteed-to-work Pipes calls per month" is the quote from the article.

The reason I think that interesting is because that's the model these days for everything from AI tokens to Monday.com seats. It makes me feel like Pipes was before its time.

That said I've been collecting different "business glue" products that are similar to Pipes. To me, like you say, they aren't as interesting, exciting and intuitive as Pipes was, but maybe it just takes a little more digging. I tried to focus on open source tools but some aren't.

- n8n io: https://n8n.io/integrations/mondaycom/

- Node-RED: https://nodered.org/ (just read about this one in this thread)

- trigger dev: trigger.dev

- automatisch.io: https://automatisch.io/docs/

- Activepieces: https://www.activepieces.com/docs/getting-started/introducti...

- Huginn: https://github.com/huginn/huginn

- budibase: https://budibase.com/

- windmill: https://www.windmill.dev/

- tooljet: https://www.tooljet.com/workflows

- Bracket: https://www.usebracket.com/pricing (just SalesForce <-> PostgreSQL)

- Zapier: zapier.com/

Anyway I hope some of these are fun!

Source: https://github.com/node-red/node-red

I believe Node-RED (https://nodered.org/) the way to go. It's just an NPM package to install and you can run it how ever you wish (even on Windows). It has a friendly and helpful community with even the main developers tirelessly answering even beginner level questions. In fact the community forum its THE friendliest forum I've ever been a member of by a large margin. Node-RED's development is supported by the JS Foundation and it's completely free and open source. It's widely used in the industrial automation industry and even integrated by some PLC manufacturers such as Siemens.

Does anyone know if their are plans to implement something like this (or if there are already custom nodes out there). I'd like to experiment with things like looping and incrementing values (like a for loop) for a Ksampler for example. It's only an example though, so I am not looking for a ksampler specific solution; just a generic way to have a variable (e.g. Seed value), run some nodes that use that value, increment the value, and then loop back to the beginning until some sort of condition is met. Node-Red (an event driven node based programming language) has this functionality so it could defintely work in a node based environment such as ComfyUI (see here).