"In a numerics heavy application it's like that all fast paths will trigger somewhere, but those will likely be better off using numpy or numba. For a text heavy application such as a web server, only few fast paths will trigger and so the various checks only add overhead."

Hum, I disagree. See benchmark results in other messages. Examples:

### django_v2 ###
Min: 2.682884 -> 2.633110: 1.02x faster

### unpickle_list ###
Min: 1.333952 -> 1.212805: 1.10x faster

These benchmarks are not written for numeric, but are more "general" benchmarks. int is just a core feature of Python, simply used everywhere, as the str type.