Strongly disagree. Python’s adoption is primarily driven by how easy it is to get started (barring some nasties in datetime, typing, and ofcourse the package manager).

Python is plenty fast for most automation tasks.

You are talking past the point I am making. No doubt Python has excellent adoption because the language is incredibly idiomatic and easy to understand -- thus why it is my favorite language. Python is great in all of the ways you just stated but it could be better and I am saying that speed for CPU bound tasks is the way it could be better. I am so tired of binning Python in favor of golang the moment latency becomes important, I would like to use it all the time.

Python is fast enough for many tasks, including number crunching for which it excels (as long as you are using the right libraries).

Projects like Cython allow to tweak without too much effort the parts of a program that need an extra-boost.

Last but not least, there have been discussions in the Python community in the last weeks of ways to speed up considerably the default (CPython) implementation.

Hopefully, all of this will bear some fruits in the next 2-5 years. Guido will probably help from his new position at Microsoft.

Only because libraries have to use C bindings to make it fast enough. I don't think Python performance is good enough when I have to stop writing in the language that we are benchmarking to get good results.

> discussions in the Python community in the last weeks of ways to speed up CPython

This piqued my interest. I found this, by Mark Shannon: https://mail.python.org/archives/list/[email protected]/...

Is that what you mean?

Python's biggest hurdle is it's lack of good tooling.

Try building a Unix app, with data in standard Unix locations(bin, shared, lib, etc) and you'll find that you have to write custom code.

And Google searches don't help :(