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Nuitka (pronounced as / n juː t k ʌ / [2]) is a source-to-source compiler which compiles Python code to C source code, applying some compile-time optimizations in the process such as constant folding and propagation, built-in call prediction, type inference, and conditional statement execution.
The Python plugin, which links against libpython, and allows one to invoke arbitrary Python scripts from inside the compiler. The aim is to allow GCC plugins to be written in Python. The MELT plugin provides a high-level Lisp-like language to extend GCC. [71] The support of plugins was once a contentious issue in 2007. [72] C++ transactional memory
In 2005, Mingw-w64 was created by OneVision Software under cleanroom software engineering principles, since the original MinGW project was not prompt on updating its code base, including the inclusion of several key new APIs and also much needed 64-bit support.
Cython is written in Python and C and works on Windows, macOS, and Linux, producing C source files compatible with CPython 2.6, 2.7, and 3.3 and later versions. The Cython source code that Cython compiles (to C) can use both Python 2 and Python 3 syntax, defaulting to Python 2 syntax in Cython 0.x and Python 3 syntax in Cython 3.x.
Adhering to an ABI (which may or may not be officially standardized) is usually the job of a compiler, operating system, or library author. However, an application programmer may have to deal with an ABI directly when writing a program in a mix of programming languages, or even compiling a program written in the same language with different ...
Research compilers are mostly not robust or complete enough to handle real, large applications. They are used mostly for fast prototyping new language features and new optimizations in research areas. Open64: A popular research compiler. Open64 merges the open source changes from the PathScale compiler mentioned.
The non-Python library being called to perform the CPU-intensive task is not subject to the GIL and may concurrently execute many threads on multiple processors without restriction. Concurrency of Python code can only be achieved with separate CPython interpreter processes managed by a multitasking operating system .
MicroPython consists of a Python compiler to bytecode and a runtime interpreter of that bytecode. The user is presented with an interactive prompt (the REPL) to execute supported commands immediately. Included are a selection of core Python libraries; MicroPython includes modules which give the programmer access to low-level hardware. [4]