The TL;DR ...
Nuitka is a Python compiler written in Python.
It is fully compatible with Python2 (2.6, 2.7) and Python3 (3.3 - 3.9).
You feed Nuitka your Python app, it does a lot of clever things, and spits out an executable or extension module.
Nuitka is distributed under the Apache license.
Okay I'm hooked! Tell me more!
Right now Nuitka is a good replacement for the Python interpreter. It compiles every language construct in all relevant CPython versions, and even the irrelevant ones like 2.6 and 3.3. It translates Python into a C program that then is linked against libpython to execute exactly like CPython. It is extremely compatible.
Nuitka is already slightly faster than CPython, but there is work to be done to include as many C optimizations as possible. We currently get a 312% speedup in pystone, which is a good start. (source: Nuitka version 0.6.0 with Python 2.7.)
In the future Nuitka will be able to use type inferencing based on whole
program analysis. It will apply that information in order to perform as
many calculations as possible in C, using C native types, without
Nuitka will also be able to integrate
ctypes bindings, but without
the usual speed penalty. The compiled program can call the C library
directly, avoiding run-time overhead.
And finally, you will be able to use a
hints module to inform Nuitka
about type information.
Now vs. Future, or, The Plan
These are the milestones and priorities for Nuitka's development.
Total feature parity with Python. Understand all language constructs, and behave exactly like CPython.
Create the most efficient native C code possible. The goal is to make basic Python object handling as fast as possible.
Implement constant propagation. Determine as many values and useful constraints as possible at compile time, and create extremely efficient code for the compiler.
Make intelligent type inferences. Detect and use special case handling for strings, integers, and lists in the compiled program.
Add interfacing with C code to allow Nuitka to turn Python
ctypesbindings into efficient C bindings.
Provide a hints module with a useful Python implementation so the compiler can learn about intended types directly from the programmer.
Where are we now?
Milestone 1, feature parity, has been achieved for Python 2.6, 2.7, and 3.3 up to 3.9. This part of Nuitka is already mature, but every new Python release has lots of new features to add!
Milestone 2 is always a work in progress, but it has been quite successful. Nuitka can already produce code that is more than 2 times faster than CPython. These gains are nowhere near the best gains possible, but they are solid improvements and will improve further.
Milestone 3, constant folding and propagation, is already in place, and some control flow optimizations are also applied - but this is just the start. Constant folding will see big gains as the type inferencing matures and more variables are opened up to become constants.
For milestone 4 the first steps are in place achieve type inferencing. The results are encouraging, but it will need a lot more work before this can be made the default approach. Remember that this is still Python, Nuitka cannot be guaranteed to perfectly guess type information.
We have yet to start on milestones 5 and 6. There is still quite a way to go until we hit the "future".
In the meantime you can find its latest version here.