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Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...
Python compiler may refer to: Python, a native code compiler for CMU Common Lisp One of several compiler implementations for the Python programming language: see Python implementations
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 (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.
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 ...
CircuitPython [5] is an open-source derivative of the MicroPython programming language targeted toward students and beginners. Development of CircuitPython is supported by Adafruit Industries. It is a software implementation of the Python 3 programming language, written in C. [3] It has been ported to run on several modern microcontrollers.
It is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language.Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software.
Compiler analysis is the prerequisite for any compiler optimization, and they tightly work together. For example, dependence analysis is crucial for loop transformation. The scope of compiler analysis and optimizations vary greatly; their scope may range from operating within a basic block, to whole procedures, or even the whole program. There ...