python 程序的优化

loughsky

PerformanceTips

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目录

Other Versions

Overview: Optimize what needs optimizing

Choose the Right Data Structure

Sorting

String Concatenation

Loops

Avoiding dots...

Local Variables

Initializing Dictionary Elements

Import Statement Overhead

Data Aggregation

Doing Stuff Less Often

Python is not C

Use xrange instead of range

Re-map Functions at runtime

Profiling Code

Profile Module

Hotshot Module

Trace Module

Visualizing Profiling Result

This page is devoted to various tips and tricks that help improve the performance of your Python programs. Wherever the information comes from someone else, I've tried to identify the source.
Python has changed in some significant ways since I first wrote my "fast python" page in about 1996, which means that some of the orderings will have changed. I migrated it to the Python wiki in hopes others will help maintain it.
Note: You should always test these tips with your application and the version of Python you intend to use and not just blindly accept that one method is faster than another. Good suggestions on profiling your python code are found here (archived version):
http://web.archive.org/web/20060506162444/http://wingware.com/doc/howtos/performance-profiling-python-code

Also new since this was originally written are packages like
Pyrex
,
Psyco
,
Weave
and
PyInline
, which can dramatically improve your application's performance by making it easier to push performance-critical code into C or machine language.
Other Versions

• 
  Russian:
  http://omsk.lug.ru/wacko/PythonHacking/PerfomanceTips
  
  

Overview: Optimize what needs optimizing
You can only know what makes your program slow after first getting the program to give correct results, then running it to see if the correct program is slow.


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