It's a good onramp to building a programmatic intuition, but you're correct that it very quickly gets left behind once the 'magic' is understood. If you do a quick image search for , e.g. Rhino3D Grasshopper, Blender Geometry Nodes, Vectorworks Marionette, Autodesk Dynamo, ComfyUI, you'll quickly see the implementations of the real world procedures users are crafting become unwieldy rather fast.
I can't tell you why an 80 column wall of characters is easier to reason about than a visual graph, but I assume it has something to do with the reason Mitch Hedberg does not like arrows[0]; look, a function.. let's got that way.
I don't think this is for people that would just write code. Maybe you need that pressure release to get some edge cases, but for the most part, if you're using a visual programming tool, you are trying to avoid the code part for some reason.
So, I don't see that limit as something that's all that bad.
and then the evolution of the whole tool slows down as the answer for most limitations in native functions becomes "just use the 'code node' and write the function there" :)
I had a similar thought while building a visual workout programming system for bodybuilding.
One thing I keep running into is that workout programs are essentially state machines progression rules, deloads, conditional branches, different exercise substitutions, autoregulation etc...
That made me wonder whether a visual programming model would make these systems more approachable. I'm still unconvinced, though. Unlike automation workflows where the graph itself reveals the logic, I'm not sure what the right visual abstraction is for training programs without making them even more overwhelming.
A key feature about data-flow programming that seems too often missed is that it is (or can be) hierarchical.
Define a subgraph of atomic nodes as itself a node with its ports formed from as-yet unconnected ports of its atomic constituents. Compose yet higher subgraphs of subgraphs and atomic nodes. Package all this in some way.
This is directly analogous to syntactic programming where functions aggregate other function calls and all that packaged into a library with an API.
This is amazing work. I've used GPIOZero in my RPi projects before. In the future, you can introduce conditional operators in the flow. It can become a complete coding platform.
Technically, it seems to have three different paradigms that it exposes:
> Procedural/Event-based/Declarative - These three snippets achieve the same thing in different ways. One repeatedly asks the button if it is pressed; one tells the button to control the LED; and one tells the LED to follow the button's state.
Much of the article seems to focus on the latter "Declarative" way, which they created a Node-RED-like UI for, which is indeed flow-based. But other approaches seemingly can be used too :)
Houdini (VFX/3D tool), virtually unchallenged in some of its domains, it's basically visual programming. Very basic what you'd do inside of Houdini when working with it (with screenshots): https://www.sidefx.com/docs/houdini/basics/intro.html
Unreal Engine also have "Blueprints" for game logic that remains fairly popular, maybe not always as the underlying systems, but at least as a control surface for game designers, like a "API" kind of.
I don't know, "node-based" interfaces as a concept seem to have made inroads into quite a number of (specialized) fields, e.g. image processing or movie postproduction.
My takeaway is that simply visualizing the AST of a procedural language doesn't do much in reducing the complexity and just makes it harder to read or edit long programs.
In contrast, visualizing data flow graphs can have real utility.
Also, the general question is who is the target audience: It seems pretty obvious to me that programmers who live and breathe code wouldn't be very enthusiastic about visual programming. But that might be different for other professions that don't have that kind of coding expertise.
Also, a lot of programming skill is about keeping the logical abstractions and runtime state in your head that your code will create - not so much reading what is on the screen. That's far easier if you have written the code yourself than if you have to get familiar with existing code.
Thanks to agents, the second case is becoming the dominating situation now, so clever visualizations that help you make sense of existing code and its runtime state might be in demand in the future.
I think PLCs are programmed using a mix of text and visuals. Or at least that's what I remember from uni. I'm not entirely sure why that is. I suppose it makes it a lot more obvious to your coworkers and management when you make spaghetti code, which I suppose can create pressure to not make a total mess of things.
Before PLCs were popular, technicians built automation systems using various types of relays. The documentation was done using "ladder diagrams" and the procedure was known as "ladder logic." So the first PLCs tried to take advantage of this knowledge by being programmed the same way since it was already familiar.
Later systems added to this by being programmable with structured text.
The first time I came across a system that was programmed entirely with relays I was completely blown away by what was possible. And also by how heavy, noisy and power-hungry it was for a portable device.
Touchdesigner, VVVV, (Notch?) too. The big benefit here (besides dataflow programming working better for more pipeline-like programs) is that it's always runtime. This is a pretty big selling point for design where quick iteration and tweaking is important
I can't tell you why an 80 column wall of characters is easier to reason about than a visual graph, but I assume it has something to do with the reason Mitch Hedberg does not like arrows[0]; look, a function.. let's got that way.
[0] https://youtu.be/EI1DBRz3JLk?si=DCLNkbeCGWyw-Ceu
So, I don't see that limit as something that's all that bad.
(maybe more context would help)
If BizTalk has it, why shouldn't my visual programming tool have it?
One thing I keep running into is that workout programs are essentially state machines progression rules, deloads, conditional branches, different exercise substitutions, autoregulation etc...
That made me wonder whether a visual programming model would make these systems more approachable. I'm still unconvinced, though. Unlike automation workflows where the graph itself reveals the logic, I'm not sure what the right visual abstraction is for training programs without making them even more overwhelming.
So far i've a workout programming language and bunch of sample programs and an app which can help you execute these workout plans, all free ofc: https://symbiote-studio.macrocodex.app/?builtin=gzclp
Define a subgraph of atomic nodes as itself a node with its ports formed from as-yet unconnected ports of its atomic constituents. Compose yet higher subgraphs of subgraphs and atomic nodes. Package all this in some way.
This is directly analogous to syntactic programming where functions aggregate other function calls and all that packaged into a library with an API.
See JSONLogic UI for similar implementation: https://github.com/GoPlasmatic/datalogic-rs Disclaimer: I am the maintainer of the datalogic-rs project
... everything evolves until it can read mail^H^H^H becomes Turing complete?
https://github.com/flux-doctrine/awesome-fbp
> Procedural/Event-based/Declarative - These three snippets achieve the same thing in different ways. One repeatedly asks the button if it is pressed; one tells the button to control the LED; and one tells the LED to follow the button's state.
Much of the article seems to focus on the latter "Declarative" way, which they created a Node-RED-like UI for, which is indeed flow-based. But other approaches seemingly can be used too :)
Are there any exceptions?
Unreal Engine also have "Blueprints" for game logic that remains fairly popular, maybe not always as the underlying systems, but at least as a control surface for game designers, like a "API" kind of.
If you're curious how out of control and wacky these sort of graphs can get, https://blueprintsfromhell.tumblr.com/ has a bunch of fun examples.
https://dev.epicgames.com/documentation/unreal-engine/bluepr...
My takeaway is that simply visualizing the AST of a procedural language doesn't do much in reducing the complexity and just makes it harder to read or edit long programs.
In contrast, visualizing data flow graphs can have real utility.
Also, the general question is who is the target audience: It seems pretty obvious to me that programmers who live and breathe code wouldn't be very enthusiastic about visual programming. But that might be different for other professions that don't have that kind of coding expertise.
Also, a lot of programming skill is about keeping the logical abstractions and runtime state in your head that your code will create - not so much reading what is on the screen. That's far easier if you have written the code yourself than if you have to get familiar with existing code.
Thanks to agents, the second case is becoming the dominating situation now, so clever visualizations that help you make sense of existing code and its runtime state might be in demand in the future.
Later systems added to this by being programmable with structured text.
The first time I came across a system that was programmed entirely with relays I was completely blown away by what was possible. And also by how heavy, noisy and power-hungry it was for a portable device.