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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.
CPython is the reference implementation of Python. It is written in C, meeting the C89 standard (Python 3.11 uses C11 [136]) with several select C99 features. CPython includes its own C extensions, but third-party extensions are not limited to older C versions—e.g. they can be implemented with C11 or C++.
Notable programming sources use terms like C-style, C-like, a dialect of C, having C-like syntax. The term curly bracket programming language denotes a language that shares C's block syntax. [1] [2] C-family languages have features like: Code block delimited by curly braces ({}), a.k.a. braces, a.k.a. curly brackets; Semicolon (;) statement ...
A consequence of C's wide availability and efficiency is that compilers, libraries and interpreters of other programming languages are often implemented in C. [47] For example, the reference implementations of Python, [48] Perl, [49] Ruby, [50] and PHP [51] are written in C.
Annotated Python-like code is compiled to C and then automatically wrapped in interface code, producing extension modules that can be loaded and used by regular Python code using the import statement, but with significantly less computational overhead at run time. Cython also facilitates wrapping independent C or C++ code into python-importable ...
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 ...
More generally, Python 2.x specifies the built-in file objects as being “implemented using C's stdio package," [48] and frequent reference is made to C standard library behaviors; the available operations (open, read, write, etc.) are expected to have the same behavior as the corresponding C functions (fopen, fread, fwrite, etc.).
NumPy targets the CPython reference implementation of Python, which is a non-optimizing bytecode interpreter. Mathematical algorithms written for this version of Python often run much slower than compiled equivalents due to the absence of compiler optimization.