PyPy Python Implementation: Difference between revisions
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* (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/PyPy Retrieved:2020-2-6. | * (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/PyPy Retrieved:2020-2-6. | ||
** '''PyPy''' is an alternative implementation of the [[Python (programming language)|Python]] programming language to [[CPython]] (which is the standard implementation). PyPy often runs faster than CPython because PyPy is a [[Just-in-time compilation|just-in-time compiler]] while CPython is an [[interpreter (computing)|interpreter]] | ** '''PyPy''' is an alternative implementation of the [[Python (programming language)|Python]] programming language to [[CPython]] (which is the standard implementation). PyPy often runs faster than CPython because PyPy is a [[Just-in-time compilation|just-in-time compiler]] while CPython is an [[interpreter (computing)|interpreter]] . Most Python code runs well on PyPy except for code that depends on CPython extensions, which either doesn't work or incurs some overhead when run in PyPy. Internally, PyPy uses a technique known as meta-tracing, which transforms an interpreter into a [[Tracing just-in-time compilation|tracing just-in-time compiler]]. Since interpreters are usually easier to write than compilers, but run slower, this technique can make it easier to produce efficient implementations of programming languages. PyPy's meta-tracing toolchain is called [[#RPython|RPython]]. | ||
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Latest revision as of 02:39, 4 November 2024
A PyPy Python Implementation is a Python implementation that ...
- …
- Counter-Example(s):
- See: RPython, PyPI, Python Language, CPython, Just-in-Time Compilation, Interpreter (Computing), Tracing Just-in-Time Compilation.
References
2020
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/PyPy Retrieved:2020-2-6.
- PyPy is an alternative implementation of the Python programming language to CPython (which is the standard implementation). PyPy often runs faster than CPython because PyPy is a just-in-time compiler while CPython is an interpreter . Most Python code runs well on PyPy except for code that depends on CPython extensions, which either doesn't work or incurs some overhead when run in PyPy. Internally, PyPy uses a technique known as meta-tracing, which transforms an interpreter into a tracing just-in-time compiler. Since interpreters are usually easier to write than compilers, but run slower, this technique can make it easier to produce efficient implementations of programming languages. PyPy's meta-tracing toolchain is called RPython.