[scarygliders]

cx_Freeze is still very effective for distribution - I use it all the time to produce a standalone version of my software and then I use Inno Setup to create an installer package for my customers.

As Loic states, Nuitka works differently from cx_Freeze in that Nuitka takes your Python source, compiles that to C++, then compiles the C++, whereas cx_Freeeze creates Python bytecode which is subsequently run by the included Python interpreter.

The result should be that the same Python code should run much faster in the form created by Nuitka, than the result created by cx_Freeze.

[falcolas]

> The result should be that the same Python code should run much faster in the form created by Nuitka

How do you figure? Python's slowness is not due to it's lack of compilation, it's due to its dynamic nature and all of the runtime lookups.

Past efforts to compile python down to bytecode have not resulted in speedups. Unladen Swallow is one such failed example. PyPy gets around this by analyzing the actual running code and is only able to speed up a subset of all of Python.

[scarygliders]

I think you misunderstand what Nuitka is doing...

It is not compiling down to Python bytecode.

It is compiling to an operational-equivalent C++ source code.

Then it is compiling that C++ code to executable object code.

[Lofkin]

Nuitka is already faster than Cpython and it seems a majority of the speed work has yet to be done.