My personal suspicion is that the secret sauce is simply to have a sufficient budget to hire an army of code quality engineers. I could be wrong, though.
The first one is a big productivity booster as it shows you bugs before you commit them.
Here's a post about this, not exactly new but still describing the general principles very well: https://instagram-engineering.com/static-analysis-at-scale-a...
Nah, asyncio on uvloop is plenty fast.
That being said, my personal experience suggests that both are really hard in Python, and not independent.
Sadly, all the attempts I've had with static analysis in Python screamed that while the language and tools make a valiant effort at supporting a reasonable set of annotations, 8-9 years after PEP 484, the libraries are simply not yet ready for it (not even, in many cases, the standard library).
Unit tests, staging environment, effective log aggregation are all important tools, of course.
When people are hyper critical of Python I feel it’s typically they haven’t seen real professional Python before and just throw scripts around… if you work with some hardened Python pros you pick up the tricks really quickly and it’s very enlightening.
I’ve always struggled to find all of those tricks in one online resource personally.
The biggest pain with it is of course refactoring. It's tedious, but I think still comes out ahead in terms of productivity for high level stuff.
You have years of experience but couldn't point to anything in particular?
Heck, I like python and I can complain about dynamic typing issues in for loops, or that they are adding features like generators/decorators that make code more difficult to understand, which goes against the zen of python.
(But I still think python is great)
Those features are 20ish years old which made the word "adding" seem a little weird. Interestingly the Zen of Python itself is not much older than generators.
My questions remain, though.