Cython VS SWIG

The approach that I favour is to use Cython. The nice thing with this approach is that your code is still written as (almost) Python, but so long as you define all required types correctly it will automatically create the C extension for you. Early versions of Cython required using Cython specific typing (Python didn't have type hints when Cython was created), but it can now use Python's type hints.

and again, everything that was released after using an older version of cython.

Just for reference,

* Nuitka[0] "is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11."

* Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles.

* Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... makes writing C extensions for Python as easy as Python itself."

* Numba[3] "is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code."

* Pyston[4] "is a performance-optimizing JIT for Python, and is drop-in compatible with ... CPython 3.8.12"

[0] https://github.com/Nuitka/Nuitka

[1] https://www.pypy.org/

[2] https://cython.org/

[3] https://numba.pydata.org/

[4] https://github.com/pyston/pyston

Profile and optimize the hotspots with cython (or whatever the cool kids are using these days... It's been a while.)

JIT essentially means generating machine code for the language on the fly, either during loading of the interpreter (method JIT), or by profiling and optimizing hotspots (tracing JIT). The language itself can be statically or dynamically typed. You could also compile a dynamic language ahead of time, for example, cython.

Cython - - embed demo

How is this any different than a mature tool such as SWIG (https://www.swig.org/)?

I've used SWIG extensively with Python to call C code and import C headers for testing/tooling purposes.

For pure C, CGO. For C++ they are likely creating shims with Swig: https://www.swig.org/

I mostly write in C and C++ so for language bindings I use Swig a lot. Say Im creating a machine learning library in C++, its very easy to create a Python API that can call the C++ classes and methods using Swig. iirc, I am using the same swig interface file to create bindings for Python, OCaml, R and even Fortran. Feel free to DM me if you got any more questions or anything!

Swig can make c++ types and functions available to python.

The likes of SWIG is often used to link C library-like code to 11-ish other widely used languages.

Maybe you could use swig to create a wrapper for Java.

But, you might find these links interesting: * https://github.com/swig/swig/issues/918 * https://github.com/kaby76/swigged.llvm