Ir al contenido principal

Hi, I'm Mariano Guerra, below is my blog, if you want to learn more about me and what I do check a summary here: marianoguerra.github.io or find me on twitter @warianoguerra or Mastodon @marianoguerra@hachyderm.io

The proof is in the meta-tracing JIT interpreter

In the previous posts: Make Your Self and Macros and optimizations: it's just a phase I described the design and implementation of a minimal object oriented language with the implementation done in JavaScript.

When we design our language on top of a high level language we may reuse accidentally or on purpose a lot of the host language semantics and make it hard to tell if our design is our own or we are just an alternative syntax on top of the host language.

To make sure the design is sound, to show an alternative way of implementing the language and to get a nice native JIT interpreter I did what anybody would do.

I implemented an interpreter on top of rpython, the toolchain that allows pypy to be a really fast Python interpreter implemented in "Python".

Before you say "you are trying to avoid the problem of using a high level language like JavaScript by using Python?", the quotes around Python are because the language used to implement the interpreter is a restricted subset of Python called rpython, short for "restricted python" which defines itself as: "RPython is everything that our translation toolchain can accept". In the end rpython is a language that looks like a subset of python but restricts programs written with it to be statically typed, it's just that all the types are inferred, you can read more about the restrictions here: RPython Language.

The implementations is in the mclulang/pypyfatt folder, follow the instructions in the readme if you want to build it yourself, if you want to believe me, it does everything fatt.cli.js does, the parsers may have some corner cases between them but I will fix them as I see them.

RPython build output

I came for the meta-tracing JIT compiler, I stayed for the fractals