Go actually lets you work at a quite high level, much like C# or Java (and the performance is in the same ballpark). I think a better question to ask is: why is Python so slow?
From what I remember - even leaving aside core language speed - the idioms of certain languages lead people to write slow data structures and algorithms. You can write (much) faster Python but it might start to look un-Pythonic.
But of course there is the counter-argument - if your web framework is your bottleneck then you're doing something weird. Personally I don't work on high-traffic sites and I'll choose expressivity over speed any day.
I don't think it's weird that the web server could be a bottleneck in a web application (even if it is a database-driven app, as most are).
Of course, if you're making an internal CRUD app that two people are going to use, it's unlikely to matter which stack you use.
> if you're making an internal CRUD app that two people are going to use
I know you're exaggerating for comic effect but still. You can run sites that have millions of visits a day on a $20/month VPS and still not have to worry about performance - unless you're doing something completely resistant to caching. I don't personally know anyone that has to handle more traffic than that but if you believed the general chatter on HN then that segment of the market doesn't even exist. Going from 30 servers to 2? I might be able to cut my overall hosting bill by a few hundred dollars a year but it's not top of my list of concerns.
FWIW, these cases don't come down to raw rq/s performance, but are more due to RAM usage.
So for '1 + 1', you can't just output some fast x86 instruction and inline it. You'll usually need to jump to where the python vm will do 'a + b' in C. You're having to do a bunch of redundant work at a higher level to emulate the CPU (sorta).
That's why you have JIT compilers that will read '1 + 1' and compile the appropriate machine code, store that in an executable memory region and jump to it. First time might be slow, but after that it's pretty fast. Because you need to jump to the dynamically generated code, you usually compile whole functions at a time.
This topic is super complicated but also super interested but I tried to simplify it a bit here.
A lot of the slowness in Python probably comes from the many memory allocations all over the place. Go gives you a lot of control over allocations even though it is a garbage collected language.
These slides posted by another commenter has some good points about why Python is so slow: https://speakerdeck.com/alex/why-python-ruby-and-javascript-...
Interestingly, there was actually a talk at PyCon US 2016 about using Go's http server in Python via C. https://www.youtube.com/watch?v=CkDwb5koRTc
http://magic.io/blog/uvloop-blazing-fast-python-networking/
This is almost exactly on par with golang's net/http for a simple echo server, yet it is written in python.