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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] RPython can be compiled to C, and is used to build the PyPy interpreter of Python.
CPython is the reference implementation of the Python programming language. Written in C and Python, CPython is the default and most widely used implementation of the Python language. CPython can be defined as both an interpreter and a compiler as it compiles Python code into bytecode before interpreting it.
Nuitka – a source-to-source compiler which compiles Python code to C/C++ executables, or source code. Numba – NumPy aware LLVM -based JIT compiler Pyjs – a framework (based on Google Web Toolkit (GWT) concept) for developing client-side Python-based web applications, including a stand-alone Python-to-JavaScript compiler, an Ajax framework ...
30 Python compilers and interpreters. ... Download QR code; Print/export Download as PDF; Printable version; In other projects Wikidata item; Appearance. move to ...
Cython (/ ˈ s aɪ θ ɒ n /) is a superset of the programming language Python, which allows developers to write Python code (with optional, C-inspired syntax extensions) that yields performance comparable to that of C. [5] [6] Cython is a compiled language that is typically used to generate CPython extension modules.
PyPy (/ ˈ p aɪ p aɪ /) is an implementation of the Python programming language. [2] PyPy often runs faster than the standard implementation CPython because PyPy uses a just-in-time compiler. [3] Most Python code runs well on PyPy except for code that depends on CPython extensions, which either does not work or incurs some overhead when run ...
Python compiler may refer to: Python, a native code compiler for CMU Common Lisp; One of several compiler implementations for the Python programming language: ...
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.