Hi Ryan, I'm not sure this completely answers your question, but the JIT does let you tell it when a class is statically known: https://bitbucket.org/pypy/pypy/src/061674dab6430beb1645f43449fc114a09d58834/rpython/rlib/jit.py?at=default#cl-979so this may help you.
In general RPython (and the JIT), are designed for dynamically typed languages, but "semi-statically" may be the same as dynamic for all intents and purposes (I'm not sure). Alex On Sat, Oct 26, 2013 at 4:58 PM, Ryan Gonzalez <rym...@gmail.com> wrote: > Hello, > > I am in need of a little assistance. I am thinking of writing a language > in RPython. Now, here is what I want: > > -Polymorphism(C++) without pointers, i.e., Derived can be implicitly cast > to Base > > I am thinking of picking RPython because of the JIT. However, I am worried > about the speed. I know the JIT PyPy generates is fast, but if it's the > same speed as PyPy itself, someone would easily pick PyPy or Topaz or the > like. > > My question is: For a somewhat statically-typed language like I am > planning, are there any extra optimizations I could add to make the JIT > work faster? Since the variables have types, I was thinking there might be > a way to make it work faster. > > Thanks in advance! > > -- > Ryan > > _______________________________________________ > pypy-dev mailing list > pypy-dev@python.org > https://mail.python.org/mailman/listinfo/pypy-dev > > -- "I disapprove of what you say, but I will defend to the death your right to say it." -- Evelyn Beatrice Hall (summarizing Voltaire) "The people's good is the highest law." -- Cicero GPG Key fingerprint: 125F 5C67 DFE9 4084
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