Isn't this the case with any Python development in general? Once you start building at scale you'll be forced to use Cython extensions and other non-native python code.
No this isn't generally true for Python, and I'm not sure why you'd be forced to use Cython for things at scale. Unless you have some particular type of software in mind perhaps?
Webservices. May be its fine for couple of hundred users, but when there are thousands of concurrent users with heavy I/O I've been forced to replace asyncio with uvloop, replacing coroutine with gevent, implementing pre-fork worker models etc. to get decent performance.
I've since then moved any webservices development to Golang and has been perfect.
I understand there are large scale companies like Instagram which supposedly use Python and I don't detest it. It's just there are better tools for job now, especially for a lean startup and of-course Python has it's advantages like being a good first programming language and large library ecosystem.
Dynamic types aren’t exactly great, but Python is generally really good at getting things done. I probably wouldn’t use it if you had millions of concurrent users instead of the thousands we do, but for most projects it will work just fine even when the projects grow in size.
You answered it:
> It did a great job of pretending to be an efficient language by having libraries pawn off the heavy lifting to companion C implementations.
That's a feature.