pypy compile

相關問題 & 資訊整理

pypy compile

If you prefer to compile your own PyPy, or if you want to modify it, you will need to obtain a copy of the sources. This can be done either by downloading them ... ,If you prefer to compile your own PyPy, or if you want to modify it, you will need to obtain a copy of the sources. This can be done either by downloading them ... ,The latter passes are based on the compiler package from the standard library of CPython, with various improvements and bug fixes. The bytecode compiler ... ,Compiling PyPy swaps or runs out of memory; How do I compile my own interpreters? Can RPython modules for PyPy be translated independently? Why does ... ,... interpreting Python with PyPy, install a C compiler that is supported by distutils and use Python 2.5 or greater to run PyPy: cd pypy python bin/pyinteractive.py. ,Instead it requires writing small tests in rpython/jit/metainterp/optimizeopt/test/test_* and fixing files there. After that, you can just compile PyPy and things should ... ,It has several advantages and distinct features: Speed: thanks to its Just-in-Time compiler, Python programs often run faster on PyPy. (What is a JIT compiler?) ,PyPy是Armin Rigo開發的,Python語言的動態編譯器,是Psyco的後繼專案。PyPy的目的是,做 ... Tracing the meta-level: PyPy's Tracing JIT Compiler. In Proc. ,The JIT compiler. Various interpreter optimizations that improve performance as well as help save memory. Introducing a new PyPy website at http://pypy.org/ ... ,They can't compile the PyPy interpreter yet, but they're getting there… bugfixes, better performance: As you would expect, performance continues to improve and ...

相關軟體 Python (64-bit) 資訊

Python (64-bit)
Python 64 位是一種動態的面向對象編程語言,可用於多種軟件開發。它提供了與其他語言和工具集成的強大支持,附帶大量的標準庫,並且可以在幾天內學到。許多 Python 程序員報告大幅提高生產力,並認為語言鼓勵開發更高質量,更易維護的代碼。下載用於 PC 的 Python 離線安裝程序設置 64 位 Python 在 Windows,Linux / Unix,Mac OS X,OS / 2,Am... Python (64-bit) 軟體介紹

pypy compile 相關參考資料
Building PyPy from Source — PyPy 2.6.1 documentation

If you prefer to compile your own PyPy, or if you want to modify it, you will need to obtain a copy of the sources. This can be done either by downloading them ...

http://doc.pypy.org

Building PyPy from Source — PyPy documentation

If you prefer to compile your own PyPy, or if you want to modify it, you will need to obtain a copy of the sources. This can be done either by downloading them ...

http://doc.pypy.org

Bytecode Interpreter — PyPy documentation

The latter passes are based on the compiler package from the standard library of CPython, with various improvements and bug fixes. The bytecode compiler ...

http://doc.pypy.org

Frequently Asked Questions — PyPy 2.4.0 documentation

Compiling PyPy swaps or runs out of memory; How do I compile my own interpreters? Can RPython modules for PyPy be translated independently? Why does ...

http://doc.pypy.org

Getting Started with PyPy's Python Interpreter — PyPy 2.4.0 ...

... interpreting Python with PyPy, install a C compiler that is supported by distutils and use Python 2.5 or greater to run PyPy: cd pypy python bin/pyinteractive.py.

http://doc.pypy.org

How to contribute to PyPy — PyPy 2.4.0 documentation

Instead it requires writing small tests in rpython/jit/metainterp/optimizeopt/test/test_* and fixing files there. After that, you can just compile PyPy and things should ...

http://doc.pypy.org

PyPy - Welcome to PyPy

It has several advantages and distinct features: Speed: thanks to its Just-in-Time compiler, Python programs often run faster on PyPy. (What is a JIT compiler?)

https://pypy.org

PyPy - 維基百科,自由的百科全書 - Wikipedia

PyPy是Armin Rigo開發的,Python語言的動態編譯器,是Psyco的後繼專案。PyPy的目的是,做 ... Tracing the meta-level: PyPy's Tracing JIT Compiler. In Proc.

https://zh.wikipedia.org

PyPy 1.2: Just-in-Time Compilation — PyPy documentation

The JIT compiler. Various interpreter optimizations that improve performance as well as help save memory. Introducing a new PyPy website at http://pypy.org/ ...

http://doc.pypy.org

pypy-0.9.0: stackless, new extension compiler — PyPy documentation

They can't compile the PyPy interpreter yet, but they're getting there… bugfixes, better performance: As you would expect, performance continues to improve and ...

https://doc.pypy.org