Is it feasible to compile Python to machine code?

As @Greg Hewgill says it, there are good reasons why this is not always possible. However, certain kinds of code (like very algorithmic code) can be turned into "real" machine code.

There are several options:

• Use Psyco, which emits machine code dynamically. You should choose carefully which methods/functions to convert, though.
• Use Cython, which is a Python-like language that is compiled into a Python C extension
• Use PyPy, which has a translator from RPython (a restricted subset of Python that does not support some of the most "dynamic" features of Python) to C or LLVM.
  • PyPy is still highly experimental
  • not all extensions will be present

After that, you can use one of the existing packages (freeze, Py2exe, PyInstaller) to put everything into one binary.

All in all: there is no general answer for your question. If you have Python code that is performance-critical, try to use as much builtin functionality as possible (or ask a "How do I make my Python code faster" question). If that doesn't help, try to identify the code and port it to C (or Cython) and use the extension.

Try ShedSkin Python-to-C++ compiler, but it is far from perfect. Also there is Psyco - Python JIT if only speedup is needed. But IMHO this is not worth the effort. For speed-critical parts of code best solution would be to write them as C/C++ extensions.

Nuitka is a Python to C++ compiler that links against libpython. It appears to be a relatively new project. The author claims a speed improvement over CPython on the pystone benchmark.