Concurrency is a pet use case for 99% of projects. Library ecosystem is the primary and dominant factor when choosing general-purpose technologies and Python has it beat.
In a multi core world concurrency and parallelism are no longer pet use cases.
Unfortunately The slowness of python, gil and really bad design choices of Asyncio in python 3 relative to how elegant parallelism and concurrent programming is in Racket, haskell, elixir and erlang make python a non starter for many basic use cases
This is absolutely not true, because most of the industry uses Python for web services and serving web pages is still the same thing as it was 20 years ago. You scale by bringing in more processes.
Multicore concurrency is still a pet use case because high performance is still a minority of applications and async programming is not necessarily faster, per many benchmarks. Most companies will rewrite the high-performance component in the proper manner and continue to do everything else the way they did.
Nobody's writing production Haskell or Erlang for this save maybe a half-dozen companies; it's all C++ or Java, and it represents a very small minority of the code as critical paths are usually tiny slivers of a codebase.
