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Improve the whatsnew article on the lru/lfu cache decorators.

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Raymond Hettinger 2010-08-06 23:23:49 +00:00
parent 7e3b948cfe
commit 86f9613957
1 changed files with 24 additions and 13 deletions
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Doc/whatsnew/3.2.rst
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@ -71,8 +71,8 @@ New, Improved, and Deprecated Modules
save repeated queries to an external resource whenever the results are save repeated queries to an external resource whenever the results are
expected to be the same. expected to be the same.
For example, adding an LFU decorator to a database query function can save For example, adding a caching decorator to a database query function can save
database accesses for the most popular searches:: database accesses for popular searches::
@functools.lfu_cache(maxsize=50) @functools.lfu_cache(maxsize=50)
def get_phone_number(name): def get_phone_number(name):
@ -80,21 +80,32 @@ New, Improved, and Deprecated Modules
c.execute('SELECT phonenumber FROM phonelist WHERE name=?', (name,)) c.execute('SELECT phonenumber FROM phonelist WHERE name=?', (name,))
return c.fetchone()[0] return c.fetchone()[0]
The LFU (least-frequently-used) cache gives best results when the distribution The caches support two strategies for limiting their size to *maxsize*. The
of popular queries tends to remain the same over time. In contrast, the LRU LFU (least-frequently-used) cache works bests when popular queries remain the
(least-recently-used) cache gives best results when the distribution changes same over time. In contrast, the LRU (least-recently-used) cache works best
over time (for example, the most popular news articles change each day as query popularity changes over time (for example, the most popular news
newer articles are added). articles change each day as newer articles are added).
The two caching decorators can be composed (nested) to handle hybrid cases The two caching decorators can be composed (nested) to handle hybrid cases.
that have both long-term access patterns and some short-term access trends.
For example, music searches can reflect both long-term patterns (popular For example, music searches can reflect both long-term patterns (popular
classics) and short-term trends (new releases):: classics) and short-term trends (new releases)::
@functools.lfu_cache(maxsize=500) @functools.lfu_cache(maxsize=500)
@functools.lru_cache(maxsize=100) @functools.lru_cache(maxsize=100)
def find_music(song): def find_lyrics(song):
... query = 'http://www.example.com/songlist/%s' % urllib.quote(song)
page = urllib.urlopen(query).read()
return parse_lyrics(page)
To help with choosing an effective cache size, the wrapped function
is instrumented with two attributes 'hits' and 'misses'::
>>> for song in user_requests:
... find_lyrics(song)
>>> print find_lyrics.hits
4805
>>> print find_lyrics.misses
980
(Contributed by Raymond Hettinger) (Contributed by Raymond Hettinger)