I've been playing with Julia a bit lately, but I haven't had any good reasons to write real code in it yet. I've got to say, a useful Python compatibility layer between the two languages would be <i>awesome</i>. Being able to call SciPy libraries from Julia would make it a <i>lot</i> more interesting to start writing Julia code.
I don't mind writing cython to judiciously optimize my scientific python code when needed, but efforts along these lines, as well as Travis Oliphant's Numba project (<a href="https://github.com/ContinuumIO/numba" rel="nofollow">https://github.com/ContinuumIO/numba</a>) seem like promising alternatives. It's great to see some productive conversations between the Julia and Scipy-dev folks.
> It's a common theme when we scientific Python users talk that we don't
really use Python for the <i>language</i>. We use it for the community and
the libraries.<p>This statement doesn't make sense to me. First, I use Python for scientific/numerical work, and I definitely use it "for the language" - at least, certain aspects of it that are rare elsewhere.<p>Second, the language, community, and libraries are all interdependent. The design of a language <i>strongly</i> influences the tone of its community, as well as the libraries available (both the number and the types).
There is also a project to port parts of Numpy/Scipy to pypy, which would probably give interesting results.<p>The following years are going to be exciting for open-source numerical work. But I fear fragmentation might ruin it for everybody.