Pick something slightly esoteric (eg Haskell) and the quality of public code is very high, because you only have enthusiasts writing it. Choose something taught in schools (Python) and you are going to find 10,000 traveling salesmen homework problems and Django todo applications.

Not sure how you thread the needle on the quality vs quantity dynamic.

As much as I love Python, JavaScript (including TypeScript) is probably more popular.

there is a relationship there, but there is also a relationship to the safety of the language and the guard rails in place.

it's a lot harder to experience an agent telling you with certainty that something incomplete is totally finished if there is a comprehensive test suite, a hard failing compiler, a strict type system, etc.

LLMs like to produce a lot of JS and python that silently fails in a graceful way -- why is that? because those languages support that kind of a failure.

when using something like go/rust the LLMs are more likely to re-iterate rather than declaring a victory when they get a strict compiler barking in their face, refusing to output.

There is definitely a relationship. But I personally believe that once the training corpus reaches a certain scale, the returns exhibit diminishing marginal effects, to the point that multiplying the data volume cannot surpass something essential inherent in language design. (Asked an LLM to help me with the translation, so forgive my expression)