Source filenames from linguist language.yml

[silverwind]

Is there an existing issue for this?

• I have searched the existing issues

What problem does this feature solve?

Chroma's language metadata is somewhat lacking.

What feature do you propose?

Linguist's languages.yml is probably the most up to date data on programming languages filenames on the internet.

I think one solution could be to embed either the whole file or just the relevant parts of it into the module via go:embed during a build process and then use it as the single authorative source for chroma's lexer-from-filename detection.

[alecthomas]

Sorry, I have no idea what this issue is asking for?

[alecthomas]

Are you suggesting using it for file extension detection, or something else?

I think the issue is that the mapping from Linguist file types to Chroma file types won't be 1:1

[silverwind]

Take for example the json lexer, Chroma only knows 2 filename for it:

chroma/lexers/embedded/json.xml

Lines 5 to 6 in e9292e6

	<filename>*.json</filename>
	<filename>*.avsc</filename>

Linguist knows 17 extensions and 15 filenames:

https://github.com/github-linguist/linguist/blob/559a6426942abcae16b6d6b328147476432bf6cb/lib/linguist/languages.yml#L3159-L3193

This rich data from the linguist file could for example be extracted from the linguist file and written into chroma lexer's .xml and .go files so chroma ends up with much better filename-based language detection in lexers.Match. But overall I think it might be better to just reduce and embed the linguist file in a build script that runs before each release.

Yes, it won't be a 1:1 mapping but the data extraction could be made best-effort where we map linguist name to chroma lexer name.

[silverwind]

Not sure how you would feel about an additional dependency, but there is also https://github.com/go-enry/go-enry which offers various ways to detect a language based on filename or content (think bash scripts with no file extension). As far as I know, it is based on a somewhat-regularily updated dataset sourced from linguist. All that's left to do for chroma would be to map the detected language to a lexer.