You have a good core idea here. You're pretty much killing your project in infancy with the AGPL+donation license model. Meanwhile, some other projects will take the core idea of "language aware differ" and release BSD, and one of those will win, including perhaps making it into git/future version controls.
IMO, you should seek to make this a standard that wins, and hopefully other opportunities that come will be where you make commercial hay. My unsolicited 2c.
I really do care about copyleft and AGPL. It’s a political choice. I specifically chose it because I know from direct experience that big tech is allergic to it.
I actually don’t care about the commercial license. It’s more of an experiment for my own amusement than an actual attempt at building a commercial project.
If it inspires someone to build another one and we still end up with a better differ, I’m ok with that world. As long as the open source community has a better differ.
Note that there already are at least 3 that I am aware of. But they do perform worse on speed and accuracy.
FWIW, there's probably no point in using a copyleft licence if AI is involved[1][2], unless you've got pretty solid proof AI only "assisted" rather than doing the bulk of the work. Otherwise, you don't have copyright on the generated code, and without copyright the licence is meaningless, AFAIK.
This is not to say you can't or shouldn't use AI, but it's important to understand the tradeoffs you're making.
I’m not based in the US so SCOTUS doesn’t set meaningful precedent for my IP.
That said, even under those rules, I would be comfortable arguing before the court that this code has significant human involvement and easily passes the copyright standard.
It’s also why I don’t think someone can just easily create another one and license it under BSD. My code is AI assisted, but all truly important pieces were human made.
> Meanwhile, some other projects will take the core idea of "language aware differ" and release BSD, and one of those will win, including perhaps making it into git/future version controls.
Diffsitter and Difftastic have been around for a while, both MIT, so I doubt it.
You know hebetube, my mother once said "if you have nothing nice to say: don't say it". You saying those things probably aren't going to make them turn over the license. "Project dead before it started" like who writes those kinds of things over someones work they spent time on. I'd love for you to explain your logic.
IMO, you should seek to make this a standard that wins, and hopefully other opportunities that come will be where you make commercial hay. My unsolicited 2c.
I actually don’t care about the commercial license. It’s more of an experiment for my own amusement than an actual attempt at building a commercial project.
If it inspires someone to build another one and we still end up with a better differ, I’m ok with that world. As long as the open source community has a better differ.
Note that there already are at least 3 that I am aware of. But they do perform worse on speed and accuracy.
This is not to say you can't or shouldn't use AI, but it's important to understand the tradeoffs you're making.
[1] https://www.scotusblog.com/cases/thaler-v-perlmutter/ [2] https://www.jenner.com/en/news-insights/client-alerts/us-cop...
That said, even under those rules, I would be comfortable arguing before the court that this code has significant human involvement and easily passes the copyright standard.
It’s also why I don’t think someone can just easily create another one and license it under BSD. My code is AI assisted, but all truly important pieces were human made.
Diffsitter and Difftastic have been around for a while, both MIT, so I doubt it.
In the meantime, I added support for all other non-code file formats. Hence the name change.
It’s quite a big chunk of functionality.
Delta adds color to the standard git diff algorithm.
Omnidiff uses a completely different algorithm.
About a third of diffs are significantly better.
Difftastic only diffs code, which is only 2/3 of all diffs.
When only measured on stuff difftastic supports:
Difftastic is perfect on 64% of diffs and near-perfect on 17% more.
Omnidiff is perfect on 90% of diffs and near-perfect on 5% more.
Speed is
p50 - 35ms difftastic vs 4ms OmniDiff p99 - 637ms vs 420ms
Difftastic wins on license. MIT vs AGPL.
Nobody wants to use AGPL-v3?
https://github.com/ivankovic/omnidiff/blob/main/LICENSE