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-rw-r--r--Doc/whatsnew/3.2.rst37
1 files changed, 24 insertions, 13 deletions
diff --git a/Doc/whatsnew/3.2.rst b/Doc/whatsnew/3.2.rst
index 62fb18f..12d3527 100644
--- a/Doc/whatsnew/3.2.rst
+++ b/Doc/whatsnew/3.2.rst
@@ -71,8 +71,8 @@ New, Improved, and Deprecated Modules
save repeated queries to an external resource whenever the results are
expected to be the same.
- For example, adding an LFU decorator to a database query function can save
- database accesses for the most popular searches::
+ For example, adding a caching decorator to a database query function can save
+ database accesses for popular searches::
@functools.lfu_cache(maxsize=50)
def get_phone_number(name):
@@ -80,21 +80,32 @@ New, Improved, and Deprecated Modules
c.execute('SELECT phonenumber FROM phonelist WHERE name=?', (name,))
return c.fetchone()[0]
- The LFU (least-frequently-used) cache gives best results when the distribution
- of popular queries tends to remain the same over time. In contrast, the LRU
- (least-recently-used) cache gives best results when the distribution changes
- over time (for example, the most popular news articles change each day as
- newer articles are added).
+ The caches support two strategies for limiting their size to *maxsize*. The
+ LFU (least-frequently-used) cache works bests when popular queries remain the
+ same over time. In contrast, the LRU (least-recently-used) cache works best
+ query popularity changes over time (for example, the most popular news
+ articles change each day as newer articles are added).
- 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.
+ The two caching decorators can be composed (nested) to handle hybrid cases.
For example, music searches can reflect both long-term patterns (popular
classics) and short-term trends (new releases)::
- @functools.lfu_cache(maxsize=500)
- @functools.lru_cache(maxsize=100)
- def find_music(song):
- ...
+ @functools.lfu_cache(maxsize=500)
+ @functools.lru_cache(maxsize=100)
+ 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)