Numba is a great technology, but I find it still a little disappointing. The way I see it is this. Python is not a particularly fast language, but has evolved

Numba is a great technology, but I find it still a little disappointing. The way I see it is this. Python is not a particularly fast language, but has evolved a big ecosystem of scientific libraries. Now people are running into the language limitations, hence the development of various tools to compile parts of Python - either AOT or JIT - with PyPy, Numba, Cython, Numexpr and so on. The problem is that all these tools (save from PyPy, which is just a different interpreter) introduce their ow sublanguage, slightly incompatible from one another. For instance, both Numba and Cython have to infer types, but their type systems are not equal. Nim does not have the reach of Python ecosystem, but it is a solid language, that manages to combine well the speed of C and the simplicity and flexibility of Python. I would rather start from a solid foundation and add libraries on top of it gradually, rather than start from a developed ecosystem and add a host of tools that try to fix the inherent limitations of the platform. Hence, in the short term it is great that the projects created by Continuum exist, but eventually I would like to have something a little more consistent