Writing a translator isn't impossible, especially considering that Joel's Intern did it over a summer.
If you want to do one language, it's easy. If you want to do more, it's a little more difficult, but not too much. The hardest part is that, while any turing complete language can do what another turing complete language does, built-in data types can change what a language does phenomenally.
For instance:
word = 'This is not a word'
print word[::-2]
takes a lot of C++ code to duplicate (ok, well you can do it fairly short with some looping constructs, but still).
That's a bit of an aside, I guess.
Have you ever written a tokenizer/parser based on a language grammar? You'll probably want to learn how to do that if you haven't, because that's the main part of this project. What I would do is come up with a basic Turing complete syntax - something fairly similar to Python bytecode. Then you create a lexer/parser that takes a language grammar (perhaps using BNF), and based on the grammar, compiles the language into your intermediate language. Then what you'll want to do is do the reverse - create a parser from your language into target languages based on the grammar.
The most obvious problem I see is that at first you'll probably create horribly inefficient code, especially in more powerful* languages like Python.
But if you do it this way then you'll probably be able to figure out ways to optimize the output as you go along. To summarize:
- read provided grammar
- compile program into intermediate (but also Turing complete) syntax
- compile intermediate program into final language (based on provided grammar)
- ...?
- Profit!(?)
*by powerful I mean that this takes 4 lines:
myinput = raw_input("Enter something: ")
print myinput.replace('a', 'A')
print sum(ord(c) for c in myinput)
print myinput[::-1]
Show me another language that can do something like that in 4 lines, and I'll show you a language that's as powerful as Python.
