blocks|key|1238813|text|在Python3.2中，您可以使用functools库中的装饰器@lru_cache。这是一个最近使用的缓存，所以其中的项没有过期时间，但作为一个快速的技巧，它非常有用。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1238814|from+functools+import+lru_cache

@lru_cache(maxsize=256)
def+f(x):
++return+x*x

for+x+in+range(20):
++print+f(x)
for+x+in+range(20):
++print+f(x)|code-block|syntax|javascript|1238815|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.python.org/3.4/library/functools.html#functools.lru_cache^0|W|A|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@$A|R|B|S|1|T]]|C|$]]|$1|D|3|E|5|F|7|U|8|@]|9|@]|C|$G|H]]|$1|I|3|-4|5|6|7|V|8|@]|9|@]|C|$]]]|J|$K|$5|L|M|N|C|$O|P]]]]

From Python 3.2 you can use the decorator <a href="http://docs.python.org/3.4/library/functools.html#functools.lru_cache" rel="noreferrer">@lru_cache</a> from the functools library.
It's a Last Recently Used cache, so there is no expiration time for the items in it, but as a fast hack it's very useful.

<pre><code>from functools import lru_cache

@lru_cache(maxsize=256)
def f(x):
 return x*x

for x in range(20):
 print f(x)
for x in range(20):
 print f(x)
</code></pre>

blocks|key|1238268|text|您还可以查看一下Memoize+decorator。你也许可以让它做你想做的事情，而不需要太多的修改。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1238269|entityMap|0|LINK|mutability|MUTABLE|url|http://wiki.python.org/moin/PythonDecoratorLibrary#Memoize^0|8|H|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

You might also take a look at the <a href="http://wiki.python.org/moin/PythonDecoratorLibrary#Memoize" rel="noreferrer">Memoize decorator</a>. You could probably get it to do what you want without too much modification.

blocks|key|1453677|text|还没有人提到过搁置。https://docs.python.org/2/library/shelve.html|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1453678|它不是memcached，但看起来简单得多，可能符合您的需要。|1453679|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.python.org/2/library/shelve.html^0|A|19|0|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]]|C|$]]|$1|D|3|E|5|6|7|R|8|@]|9|@]|C|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]]]

No one has mentioned shelve yet. <a href="https://docs.python.org/2/library/shelve.html">https://docs.python.org/2/library/shelve.html</a>

It isn't memcached, but looks much simpler and might fit your need.

blocks|key|1238215|text|我认为the+python+memcached+API是最流行的工具，但我自己还没有用过它，也不确定它是否支持你需要的特性。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1238216|entityMap|0|LINK|mutability|MUTABLE|url|http://www.tummy.com/Community/software/python-memcached/^0|3|O|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

I think <a href="http://www.tummy.com/Community/software/python-memcached/" rel="noreferrer">the python memcached API</a> is the prevalent tool, but I haven't used it myself and am not sure whether it supports the features you need.

blocks|key|1238225|text|import+time

class+CachedItem(object):
++++def+__init__(self,+key,+value,+duration=60):
++++++++self.key+=+key
++++++++self.value+=+value
++++++++self.duration+=+duration
++++++++self.timeStamp+=+time.time()

++++def+__repr__(self):
++++++++return+'<CachedItem+{%25s:%25s}+expires+at:+%25s>'+%25+(self.key,+self.value,+time.time()+%2B+self.duration)

class+CachedDict(dict):

++++def+get(self,+key,+fn,+duration):
++++++++if+key+not+in+self+\
++++++++++++or+self[key].timeStamp+%2B+self[key].duration+<+time.time():
++++++++++++++++print+'adding+new+value'
++++++++++++++++o+=+fn(key)
++++++++++++++++self[key]+=+CachedItem(key,+o,+duration)
++++++++else:
++++++++++++print+'loading+from+cache'

++++++++return+self[key].value



if+__name__+==+'__main__':

++++fn+=+lambda+key:+'value+of+%25s++is+None'+%25+key

++++ci+=+CachedItem('a',+12)
++++print+ci+
++++cd+=+CachedDict()
++++print+cd.get('a',+fn,+5)
++++time.sleep(2)
++++print+cd.get('a',+fn,+6)
++++print+cd.get('b',+fn,+6)
++++time.sleep(2)
++++print+cd.get('a',+fn,+7)
++++print+cd.get('b',+fn,+7)|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|1238226|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

<pre><code>import time

class CachedItem(object):
 def __init__(self, key, value, duration=60):
 self.key = key
 self.value = value
 self.duration = duration
 self.timeStamp = time.time()

 def __repr__(self):
 return '&lt;CachedItem {%s:%s} expires at: %s&gt;' % (self.key, self.value, time.time() + self.duration)

class CachedDict(dict):

 def get(self, key, fn, duration):
 if key not in self \
 or self[key].timeStamp + self[key].duration &lt; time.time():
 print 'adding new value'
 o = fn(key)
 self[key] = CachedItem(key, o, duration)
 else:
 print 'loading from cache'

 return self[key].value



if __name__ == '__main__':

 fn = lambda key: 'value of %s is None' % key

 ci = CachedItem('a', 12)
 print ci 
 cd = CachedDict()
 print cd.get('a', fn, 5)
 time.sleep(2)
 print cd.get('a', fn, 6)
 print cd.get('b', fn, 6)
 time.sleep(2)
 print cd.get('a', fn, 7)
 print cd.get('b', fn, 7)
</code></pre>

blocks|key|1238698|text|你可以使用我对这个问题的简单解决方案。它真的很简单，没有什么花哨的东西：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1238699|class+MemCache(dict):
++++def+__init__(self,+fn):
++++++++dict.__init__(self)
++++++++self.__fn+=+fn

++++def+__getitem__(self,+item):
++++++++if+item+not+in+self:
++++++++++++dict.__setitem__(self,+item,+self.__fn(item))
++++++++return+dict.__getitem__(self,+item)

mc+=+MemCache(lambda+x:+x*x)

for+x+in+xrange(10):
++++print+mc[x]

for+x+in+xrange(10):
++++print+mc[x]|code-block|syntax|javascript|1238700|它确实缺乏过期功能，但您可以通过在MemCache+c-tor中指定特定规则来轻松扩展它。|1238701|希望代码足够自解释，但如果不是这样，只需提及，缓存将被传递一个转换函数作为其c-tor参数之一。它依次用于生成关于输入的缓存输出。|1238702|希望能有所帮助|1238703|entityMap^0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|O|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|P|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|Q|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|R|8|@]|9|@]|A|$]]|$1|K|3|L|5|6|7|S|8|@]|9|@]|A|$]]|$1|M|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|N|$]]

You can use my simple solution to the problem. It is really straightforward, nothing fancy:

<pre><code>class MemCache(dict):
 def __init__(self, fn):
 dict.__init__(self)
 self.__fn = fn

 def __getitem__(self, item):
 if item not in self:
 dict.__setitem__(self, item, self.__fn(item))
 return dict.__getitem__(self, item)

mc = MemCache(lambda x: x*x)

for x in xrange(10):
 print mc[x]

for x in xrange(10):
 print mc[x]
</code></pre>

It indeed lacks expiration funcionality, but you can easily extend it with specifying a particular rule in MemCache c-tor.

Hope code is enough self-explanatory, but if not, just to mention, that cache is being passed a translation function as one of its c-tor params. It's used in turn to generate cached output regarding the input.

Hope it helps

blocks|key|1453411|text|尝试redis，它是应用程序以原子方式共享数据的最干净和最简单的解决方案之一，或者如果你有一些web服务器平台的话。它非常容易设置，您将需要一个python+redis客户端http://pypi.python.org/pypi/redis|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1453412|entityMap|0|LINK|mutability|MUTABLE|url|http://pypi.python.org/pypi/redis^0|2F|X|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Try redis, it is one of the cleanest and easiest solutions for applications to share data in a atomic way or if you have got some web server platform. Its very easy to setup, you will need a python redis client <a href="http://pypi.python.org/pypi/redis" rel="noreferrer">http://pypi.python.org/pypi/redis</a>

blocks|key|1238345|text|在pypi上查看gocept.cache，管理超时。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1238346|entityMap|0|LINK|mutability|MUTABLE|url|https://pypi.org/project/gocept.cache/^0|8|C|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Look at <a href="https://pypi.org/project/gocept.cache/" rel="nofollow noreferrer">gocept.cache</a> on pypi, manage timeout.

blocks|key|1453729|text|这个project的目标是为人类提供“缓存”(虽然似乎还不为人所知)。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1453730|来自项目页面的一些信息：|1453731|安装|1453732|pip安装缓存|1453733|用法：|1453734|import+pylibmc
from+cache+import+Cache

backend+=+pylibmc.Client(["127.0.0.1"])

cache+=+Cache(backend)

@cache("mykey")
def+some_expensive_method():
++++sleep(10)
++++return+42

#+writes+42+to+the+cache
some_expensive_method()

#+reads+42+from+the+cache
some_expensive_method()

#+re-calculates+and+writes+42+to+the+cache
some_expensive_method.refresh()

#+get+the+cached+value+or+throw+an+error
#+(unless+default=+was+passed+to+@cache(...))
some_expensive_method.cached()|code-block|syntax|javascript|1453735|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/jneen/python-cache^0|2|7|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@]|9|@$A|Z|B|10|1|11]]|C|$]]|$1|D|3|E|5|6|7|12|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|13|8|@]|9|@]|C|$]]|$1|H|3|I|5|6|7|14|8|@]|9|@]|C|$]]|$1|J|3|K|5|6|7|15|8|@]|9|@]|C|$]]|$1|L|3|M|5|N|7|16|8|@]|9|@]|C|$O|P]]|$1|Q|3|-4|5|6|7|17|8|@]|9|@]|C|$]]]|R|$S|$5|T|U|V|C|$W|X]]]]

This <a href="https://github.com/jneen/python-cache" rel="nofollow noreferrer">project</a> aims to provide &quot;Caching for humans&quot;
(seems like it's fairly unknown though) 
Some info from the project page:
<h3>Installation</h3>
pip install cache
<h3>Usage:</h3>
<pre><code>import pylibmc
from cache import Cache

backend = pylibmc.Client([&quot;127.0.0.1&quot;])

cache = Cache(backend)

@cache(&quot;mykey&quot;)
def some_expensive_method():
 sleep(10)
 return 42

# writes 42 to the cache
some_expensive_method()

# reads 42 from the cache
some_expensive_method()

# re-calculates and writes 42 to the cache
some_expensive_method.refresh()

# get the cached value or throw an error
# (unless default= was passed to @cache(...))
some_expensive_method.cached()
</code></pre>

blocks|key|1453183|text|看看bda.cache+http://pypi.python.org/pypi/bda.cache+-使用ZCA，并使用zope和bfg进行测试。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1453184|entityMap|0|LINK|mutability|MUTABLE|url|http://pypi.python.org/pypi/bda.cache^0|C|11|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Look at bda.cache <a href="http://pypi.python.org/pypi/bda.cache" rel="nofollow noreferrer">http://pypi.python.org/pypi/bda.cache</a> - uses ZCA and is tested with zope and bfg.

blocks|key|1453751|text|ExpiringDict是另一种选择：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1453752|https://pypi.org/project/expiringdict/|offset|length|1453753|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|12|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|N|8|@]|9|@$D|O|E|P|1|Q]]|A|$]]|$1|F|3|-4|5|6|7|R|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|C]]]]

ExpiringDict is another option:
<a href="https://pypi.org/project/expiringdict/" rel="nofollow noreferrer">https://pypi.org/project/expiringdict/</a>

blocks|key|1238765|text|keyring是最好的python缓存库。您可以使用|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1238766|keyring.set_password("service","jsonkey",json_res)

json_res=+keyring.get_password("service","jsonkey")

json_res=+keyring.core.delete_password("service","jsonkey")|code-block|syntax|javascript|1238767|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

keyring is the best python caching library. You can use

<pre><code>keyring.set_password("service","jsonkey",json_res)

json_res= keyring.get_password("service","jsonkey")

json_res= keyring.core.delete_password("service","jsonkey")
</code></pre>

I'm looking for a Python caching library but can't find anything so far. I need a simple <code>dict</code>-like interface where I can set keys and their expiration and get them back cached. Sort of something like:

<pre><code>cache.get(myfunction, duration=300)
</code></pre>

which will give me the item from the cache if it exists or call the function and store it if it doesn't or has expired. Does anyone know something like this?

Is there a Python caching library?

服务器

Python

我正在寻找一个Python缓存库，但到目前为止什么也找不到。我需要一个简单的dict-like接口，我可以在其中设置键和它们的到期时间，并将它们缓存回来。类似这样的东西：cache.get(myfunction, duration=300)如果它存在，它将从缓存中给出它，或者如果它不存在或已经过期，则调用函数并存储它。有人知道这样的事情吗？

问有没有Python缓存库？
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