Recipe Interface Translation Integration

This module keeps a list of the recipes applied to a site, and a copy of the translatable configuration they shipped. With these, the Interface Translation (Locale) module can download and update the recipes' translations from localize.drupal.org and translate their configuration, the same way it does for modules and themes.

Locale builds its list of translatable projects from the installed modules and themes. Recipes are not extensions, so Locale does not know about them. Their translations exist on localize.drupal.org, but nothing downloads them. After a recipe is applied, its configuration stays in English (or whatever language it shipped in) on a site set up in another language.

How it works

• When a recipe is applied, the module records it, and every recipe it applied, in configuration: the drupal.org project name, the Composer package name, the version and the recipe's name.
• It also keeps a copy of the translatable values of the configuration each recipe shipped, so Locale has an original to compare with after the recipe directory is gone.
• It adds the recorded recipes to Locale's project list. From then on Locale treats them like any other project: it downloads their translations when they are added, when a language is added to the site, and when cron checks for updates, and it translates the configuration they shipped.
• Both records are configuration, so they deploy with the site. The Interface Translation module is optional: a site that adds it later starts with the full list.

What is the overhead of this module?

The module only stores the absolute minimal amount of information it needs to operate. On fresh Drupal CMS installs with the Haven and Dashi site templates, the extra stored data is about 90KB, which is 6-7% of the configuration export, altogether just 0.20% of the resulting database size on a fresh install. In both cases this module exposes roughly 900 translatable strings to interface translation which would otherwise be inaccessible to Drupal.

LLM disclosure

LLM was used to heavily research the problem space, ideate on solutions and implement a complete module with docs and tests. Brilliant ideas were also sourced from @phenaproxima's meatbrain[tm].

The module has further extensive documentation on how it works and why.