I'll say python isn't any more dynamic than ruby and groovy, and they have fairly stable and usable static compile target release/ports [1]. Python has a few [2] attempts, but none of them is close to stable or really useful.

[1] https://crystal-lang.org/

http://groovy-lang.org/releasenotes/groovy-2.0.html

[2] https://github.com/shedskin/shedskin

https://github.com/codeblazer-io/blazescript

https://github.com/serge-sans-paille/pythran

[Cython] is a programming language that makes writing C extensions for the Python language as easy as Python itself. It aims to become a superset of the [Python] language which gives it high-level, object-oriented, functional, and dynamic programming. Its main feature on top of these is support for optional static type declarations as part of the language. The source code gets translated into optimized C/C++ code and compiled as Python extension modules. This allows for both very fast program execution and tight integration with external C libraries, while keeping up the high programmer productivity for which the Python language is well known.

The primary Python execution environment is commonly referred to as CPython, as it is written in C. Other major implementations use Java (Jython [Jython]), C# (IronPython [IronPython]) and Python itself (PyPy [PyPy]). Written in C, CPython has been conducive to wrapping many external libraries that interface through the C language. It has, however, remained non trivial to write the necessary glue code in C, especially for programmers who are more fluent in a high-level language like Python than in a close-to-the-metal language like C.

Originally based on the well-known Pyrex [Pyrex], the Cython project has approached this problem by means of a source code compiler that translates Python code to equivalent C code. This code is executed within the CPython runtime environment, but at the speed of compiled C and with the ability to call directly into C libraries. At the same time, it keeps the original interface of the Python source code, which makes it directly usable from Python code. These two-fold characteristics enable Cython’s two major use cases: extending the CPython interpreter with fast binary modules, and interfacing Python code with external C libraries.

While Cython can compile (most) regular Python code, the generated C code usually gains major (and sometime impressive) speed improvements from optional static type declarations for both Python and C types. These allow Cython to assign C semantics to parts of the code, and to translate them into very efficient C code. Type declarations can therefore be used for two purposes: for moving code sections from dynamic Python semantics into static-and-fast C semantics, but also for directly manipulating types defined in external libraries. Cython thus merges the two worlds into a very broadly applicable programming language.

    def primes(int kmax):
        cdef int n, k, i
        cdef int p[1000]
        result = []
        if kmax > 1000:
            kmax = 1000
        k = 0
        n = 2
        while k < kmax:
            i = 0
            while i < k and n % p[i] != 0:
                i = i + 1
            if i == k:
                p[k] = n
                k = k + 1
                result.append(n)
            n = n + 1
        return result

http://cython.readthedocs.io/en/latest/src/tutorial/cython_t...