chain-ops-python VS monorepo

You don't need pandas to do chaining. It's a one-liner in pure python: https://github.com/tpapastylianou/chain-ops-python

Not to mention, it's a lot more debuggable this way (which is generally the biggest downside to most specialised chaining approaches).

This is great. I will use it with my python chaining approach: https://github.com/tpapastylianou/chain-ops-python

My only grief is that decorator, which forces you to wrap existing functions anyway (same way I had to define lambdas in my example anyway).

Do you have any insight on that?

fixed the capitalization https://github.com/opral/monorepo/commit/6127c6899290b35442c...

Hey there! Have you ever heard about inlang (inlang.com)? Your approach goes in our direction. Great to see so many people fixing the i18n pain! :)

If you want to take a look, here is the website featuring our products: https://inlang.com/

Last time I posted on this Subreddit I was announcing my typesafe i18n library. As luck would have it some people at Inlang saw that post and my project and contacted me to work on ParaglideJS.

I'm from inlang and we have a fully configurable JavaScript i18n library with paraglide-js that might help you. There will be a dedicated adapter of the library for NextJS that is more integrated into the framework. Until then you can look at our NextJS example and set the library up this way.

i am on a 2 year long rabbit hole to solve many i18n problems that devs face https://github.com/inlang/inlang

we are in our third (major) refactor because the problem is so complex and new requirements emerge regularly :/

inlang: localization infrastructure for software and the next git (made by the inlang team and same author of the amazing typesafe-i18n library)

https://www.loom.com/share/85d77004aa4c4bea9752d959c229e577

The irony is that this is not needed anymore. The plugin API simplified the config interface so much that initializing configs only differs by the used plugins and their respective configs.

The only useful thing that chatgpt provides is deriving what files in a filesystem are translation files. But a hardcoded version might be faster and more resilient.

Learning: The GPT hype is ... well hype. The amount of work that went into this feature is insane. The work boils down to software engineering. Sure, tools will emerge that make prompt engineering easier but so does the previous ML hypetrain led to endless nocode machine learning tools. Yet, there is no "disruptive everyone builds ML models" (for GPT "everyone will become a developer") nocode machine learning tool in sight. Maybe signaling that the premise of ML NoCode/GPT of "this works for everything" is not true. Deriving what files are translation files, yep. Deriving an entire config file, maybe not.

[0] https://github.com/inlang/inlang/discussions/408#discussion-4914727

We faced the same issue and build a viscose extension too! https://github.com/inlang/inlang/tree/main/source-code/ide-extension