You can go to several dozen of languages from Python to get better and far more easier performance without having to go to C. C can have performance, but you have to pay with it.
and came to almost the same conclusion in that most of the macro use in that book is in the syntactic sugar or performance optimization category. If I didn't have a lot of projects in the queue and people demanding my time I'd try coding up the ATN and Prolog examples in Python (sorta kinda did the "CLOS" example in that I built a strange kind of meta-object facility that made "objects" backed by RDF triples)
to conclude I could create something that people who think "Java Sux" and "Common Lisp Sux" would really hate. If I went forward on that it would be to try "code golf not counting POM file size" by dividing ferocity into layers (like that ferocity0 which is enough to write a code generator that can stub the whole stdlib) so I could use metaprogramming to fight back against the bulkification you get from writing Java as typed S-expressions. (I'm pretty sure type erasure can be dealt with if you aren't interested in JDK 10+ features like var and switch expressions, on the other hand a system like that doesn't have to be able to code generate syntactic sugar sorts of structures because ferocity is all about being able to write syntatic sugar)
Ad-hoc, informally specified and bug-ridden (Greenspun's tenth rule applies very much to Python).
I'm not criticizing the article, which humorously draws Dr.Strangelove analogies to these techniques. What I don't understand is that this sort thing has been popular for over 20 years in the Python space.
