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The Mojo programming language was created by Modular Inc, which was founded by Chris Lattner, the original architect of the Swift programming language and LLVM, and Tim Davis, a former Google employee. [22] Intention behind Mojo is to bridge the gap between Python’s ease of use and the fast performance required for cutting-edge AI ...
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. The Python → 11l → C++ transpiler [166] compiles a subset of Python 3 to C++ . Specialized: MyHDL is a Python-based hardware description language (HDL), that converts MyHDL code to Verilog or VHDL code.
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.
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.
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.
A source-to-source translator, source-to-source compiler (S2S compiler), transcompiler, or transpiler [1] [2] [3] is a type of translator that takes the source code of a program written in a programming language as its input and produces an equivalent source code in the same or a different programming language.
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 ...