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Psyco

From Wikipedia, the free encyclopedia
Just-in-time compiler for Python
Not to be confused with Psycho (disambiguation).
Psyco
Developer(s) Armin Rigo, Christian Tismer
Final release
1.6 / December 16, 2007; 17 years ago (2007年12月16日)
Repository
Written inC, Python
Operating system Cross-platform
Platform 32-bit x86 only
Type Just-in-time compiler
License MIT License
Websitepsyco.sourceforge.net

Psyco is an unmaintained specializing just-in-time compiler for pre-2.7 Python originally developed by Armin Rigo and further maintained and developed by Christian Tismer. Development ceased in December, 2011.[1]

Psyco ran on BSD-derived operating systems, Linux, Mac OS X and Microsoft Windows using 32-bit Intel-compatible processors. Psyco was written in C and generated only 32-bit x86-based code.

Although Tismer announced on 17 July 2009 that work was being done on a second version of Psyco,[2] a further announcement declared the project "unmaintained and dead" on 12 March 2012 and pointed visitors to PyPy instead.[3] Unlike Psyco, PyPy incorporates an interpreter and a compiler that can generate C, improving its cross-platform compatibility over Psyco.

Speed enhancement

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This section's factual accuracy may be compromised due to out-of-date information. Please help update this article to reflect recent events or newly available information. (September 2018)

Psyco can noticeably speed up CPU-bound applications. The actual performance depends greatly on the application and varies from a slight slowdown to a 100x speedup.[4] [5] [6] [7] The average speed improvement is typically in the 1.5-4x range, making Python performance close to languages such as Smalltalk and Scheme, but still slower than compiled languages such as Fortran, C or some other JIT languages like C# and Java.[8]

Psyco also advertises its ease of use: the simplest Psyco optimization involves adding only two lines to the top of a script:[9]

import psyco
psyco.full()

These commands will import the psyco module, and have Psyco optimize the entire script. This approach is best suited to shorter scripts, but demonstrates the minimal amount of work needed to begin applying Psyco optimizations to an existing program.

See also

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References

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  1. ^ "psyco / Commits". Bitbucket. Armin Rigo.
  2. ^ Tismer, Christian (17 July 2009). "[pypy-dev] ANN: psyco V2". pypy-dev mailing list.
  3. ^ "Psyco Homepage".
  4. ^ "Python Psyco benchmarks". Archived from the original on 2008年06月06日. Retrieved 2008年04月24日.
  5. ^ "Python Psyco Homepage at sourceforge" . Retrieved 2009年03月04日.
  6. ^ "A beginners guide to using Python for performance computing at scipy.org". Archived from the original on 2009年03月11日. Retrieved 2009年03月04日.
  7. ^ "Charming Python: Make Python run as fast as C with Psyco". IBM . Retrieved 2009年03月04日.
  8. ^ "Boxplot Summary". Archived from the original on 2011年06月03日. Retrieved 2009年10月16日.
  9. ^ Rigo, Armin. "Quick examples". The Ultimate Psyco Guide. Retrieved 3 June 2011.
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