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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.
Numba is an open-source JIT compiler that translates a subset of Python and NumPy into fast machine code using LLVM, via the llvmlite Python package.It offers a range of options for parallelising Python code for CPUs and GPUs, often with only minor code changes.
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
CPython can be defined as both an interpreter and a compiler as it compiles Python code into bytecode before interpreting it. It has a foreign function interface with several languages, including C, in which one must explicitly write bindings in a language other than Python.
The default can be overridden (e.g. in source code comment) to Python 3 (or 2) syntax. Since Python 3 syntax has changed in recent versions, Cython may not be up to date with the latest additions. Cython has "native support for most of the C++ language" and "compiles almost all existing Python code". [7] Cython 3.0.0 was released on 17 July ...
It's a free compiler, though it also has commercial add-ons (e.g. for hiding source code). Numba is used from Python, as a tool (enabled by adding a decorator to relevant Python code), a JIT compiler that translates a subset of Python and NumPy code into fast machine code. Pythran compiles a subset of Python 3 to C++ . [165]
Snakemake is a Python-driven implementation for compiling and running bioinformatics workflows. [ 34 ] POSIX includes standardization of the basic features and operation of the Make utility, and is implemented with varying degrees of compatibility with Unix-based versions of Make.
These problems can be avoided by distributing both the input files and the generated code. Most people will compile using the generated code, no different from any other software package, but anyone who wants to modify the parser component can modify the input files first and re-generate the generated files before compiling.