714 lines
24 KiB
Python
714 lines
24 KiB
Python
# -*- coding: utf-8 -*-
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"""
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werkzeug.contrib.cache
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~~~~~~~~~~~~~~~~~~~~~~
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The main problem with dynamic Web sites is, well, they're dynamic. Each
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time a user requests a page, the webserver executes a lot of code, queries
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the database, renders templates until the visitor gets the page he sees.
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This is a lot more expensive than just loading a file from the file system
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and sending it to the visitor.
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For most Web applications, this overhead isn't a big deal but once it
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becomes, you will be glad to have a cache system in place.
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How Caching Works
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=================
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Caching is pretty simple. Basically you have a cache object lurking around
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somewhere that is connected to a remote cache or the file system or
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something else. When the request comes in you check if the current page
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is already in the cache and if so, you're returning it from the cache.
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Otherwise you generate the page and put it into the cache. (Or a fragment
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of the page, you don't have to cache the full thing)
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Here is a simple example of how to cache a sidebar for a template::
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def get_sidebar(user):
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identifier = 'sidebar_for/user%d' % user.id
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value = cache.get(identifier)
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if value is not None:
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return value
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value = generate_sidebar_for(user=user)
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cache.set(identifier, value, timeout=60 * 5)
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return value
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Creating a Cache Object
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=======================
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To create a cache object you just import the cache system of your choice
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from the cache module and instantiate it. Then you can start working
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with that object:
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>>> from werkzeug.contrib.cache import SimpleCache
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>>> c = SimpleCache()
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>>> c.set("foo", "value")
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>>> c.get("foo")
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'value'
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>>> c.get("missing") is None
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True
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Please keep in mind that you have to create the cache and put it somewhere
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you have access to it (either as a module global you can import or you just
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put it into your WSGI application).
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:copyright: (c) 2014 by the Werkzeug Team, see AUTHORS for more details.
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:license: BSD, see LICENSE for more details.
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"""
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import os
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import re
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import errno
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import tempfile
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from hashlib import md5
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from time import time
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try:
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import cPickle as pickle
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except ImportError: # pragma: no cover
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import pickle
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from werkzeug._compat import iteritems, string_types, text_type, \
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integer_types, to_native
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from werkzeug.posixemulation import rename
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def _items(mappingorseq):
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"""Wrapper for efficient iteration over mappings represented by dicts
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or sequences::
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>>> for k, v in _items((i, i*i) for i in xrange(5)):
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... assert k*k == v
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>>> for k, v in _items(dict((i, i*i) for i in xrange(5))):
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... assert k*k == v
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"""
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if hasattr(mappingorseq, 'items'):
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return iteritems(mappingorseq)
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return mappingorseq
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class BaseCache(object):
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"""Baseclass for the cache systems. All the cache systems implement this
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API or a superset of it.
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:param default_timeout: the default timeout (in seconds) that is used if no
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timeout is specified on :meth:`set`.
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"""
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def __init__(self, default_timeout=300):
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self.default_timeout = default_timeout
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def get(self, key):
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"""Look up key in the cache and return the value for it.
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:param key: the key to be looked up.
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:returns: The value if it exists and is readable, else ``None``.
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"""
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return None
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def delete(self, key):
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"""Delete `key` from the cache.
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:param key: the key to delete.
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:returns: Whether the key existed and has been deleted.
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:rtype: boolean
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"""
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return True
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def get_many(self, *keys):
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"""Returns a list of values for the given keys.
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For each key a item in the list is created::
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foo, bar = cache.get_many("foo", "bar")
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Has the same error handling as :meth:`get`.
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:param keys: The function accepts multiple keys as positional
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arguments.
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"""
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return map(self.get, keys)
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def get_dict(self, *keys):
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"""Like :meth:`get_many` but return a dict::
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d = cache.get_dict("foo", "bar")
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foo = d["foo"]
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bar = d["bar"]
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:param keys: The function accepts multiple keys as positional
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arguments.
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"""
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return dict(zip(keys, self.get_many(*keys)))
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def set(self, key, value, timeout=None):
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"""Add a new key/value to the cache (overwrites value, if key already
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exists in the cache).
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:param key: the key to set
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:param value: the value for the key
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:param timeout: the cache timeout for the key (if not specified,
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it uses the default timeout).
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:returns: ``True`` if key has been updated, ``False`` for backend
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errors. Pickling errors, however, will raise a subclass of
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``pickle.PickleError``.
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:rtype: boolean
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"""
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return True
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def add(self, key, value, timeout=None):
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"""Works like :meth:`set` but does not overwrite the values of already
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existing keys.
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:param key: the key to set
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:param value: the value for the key
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:param timeout: the cache timeout for the key or the default
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timeout if not specified.
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:returns: Same as :meth:`set`, but also ``False`` for already
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existing keys.
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:rtype: boolean
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"""
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return True
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def set_many(self, mapping, timeout=None):
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"""Sets multiple keys and values from a mapping.
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:param mapping: a mapping with the keys/values to set.
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:param timeout: the cache timeout for the key (if not specified,
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it uses the default timeout).
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:returns: Whether all given keys have been set.
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:rtype: boolean
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"""
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rv = True
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for key, value in _items(mapping):
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if not self.set(key, value, timeout):
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rv = False
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return rv
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def delete_many(self, *keys):
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"""Deletes multiple keys at once.
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:param keys: The function accepts multiple keys as positional
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arguments.
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:returns: Whether all given keys have been deleted.
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:rtype: boolean
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"""
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return all(self.delete(key) for key in keys)
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def clear(self):
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"""Clears the cache. Keep in mind that not all caches support
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completely clearing the cache.
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:returns: Whether the cache has been cleared.
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:rtype: boolean
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"""
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return True
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def inc(self, key, delta=1):
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"""Increments the value of a key by `delta`. If the key does
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not yet exist it is initialized with `delta`.
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For supporting caches this is an atomic operation.
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:param key: the key to increment.
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:param delta: the delta to add.
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:returns: The new value or ``None`` for backend errors.
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"""
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value = (self.get(key) or 0) + delta
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return value if self.set(key, value) else None
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def dec(self, key, delta=1):
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"""Decrements the value of a key by `delta`. If the key does
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not yet exist it is initialized with `-delta`.
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For supporting caches this is an atomic operation.
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:param key: the key to increment.
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:param delta: the delta to subtract.
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:returns: The new value or `None` for backend errors.
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"""
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value = (self.get(key) or 0) - delta
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return value if self.set(key, value) else None
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class NullCache(BaseCache):
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"""A cache that doesn't cache. This can be useful for unit testing.
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:param default_timeout: a dummy parameter that is ignored but exists
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for API compatibility with other caches.
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"""
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class SimpleCache(BaseCache):
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"""Simple memory cache for single process environments. This class exists
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mainly for the development server and is not 100% thread safe. It tries
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to use as many atomic operations as possible and no locks for simplicity
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but it could happen under heavy load that keys are added multiple times.
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:param threshold: the maximum number of items the cache stores before
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it starts deleting some.
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:param default_timeout: the default timeout that is used if no timeout is
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specified on :meth:`~BaseCache.set`.
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"""
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def __init__(self, threshold=500, default_timeout=300):
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BaseCache.__init__(self, default_timeout)
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self._cache = {}
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self.clear = self._cache.clear
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self._threshold = threshold
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def _prune(self):
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if len(self._cache) > self._threshold:
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now = time()
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toremove = []
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for idx, (key, (expires, _)) in enumerate(self._cache.items()):
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if expires <= now or idx % 3 == 0:
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toremove.append(key)
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for key in toremove:
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self._cache.pop(key, None)
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def get(self, key):
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try:
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expires, value = self._cache[key]
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if expires > time():
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return pickle.loads(value)
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except (KeyError, pickle.PickleError):
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return None
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def set(self, key, value, timeout=None):
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if timeout is None:
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timeout = self.default_timeout
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self._prune()
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self._cache[key] = (time() + timeout, pickle.dumps(value,
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pickle.HIGHEST_PROTOCOL))
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return True
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def add(self, key, value, timeout=None):
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if timeout is None:
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timeout = self.default_timeout
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self._prune()
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item = (time() + timeout, pickle.dumps(value,
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pickle.HIGHEST_PROTOCOL))
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if key in self._cache:
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return False
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self._cache.setdefault(key, item)
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return True
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def delete(self, key):
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return self._cache.pop(key, None) is not None
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_test_memcached_key = re.compile(r'[^\x00-\x21\xff]{1,250}$').match
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class MemcachedCache(BaseCache):
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"""A cache that uses memcached as backend.
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The first argument can either be an object that resembles the API of a
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:class:`memcache.Client` or a tuple/list of server addresses. In the
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event that a tuple/list is passed, Werkzeug tries to import the best
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available memcache library.
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This cache looks into the following packages/modules to find bindings for
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memcached:
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- ``pylibmc``
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- ``google.appengine.api.memcached``
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- ``memcached``
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Implementation notes: This cache backend works around some limitations in
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memcached to simplify the interface. For example unicode keys are encoded
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to utf-8 on the fly. Methods such as :meth:`~BaseCache.get_dict` return
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the keys in the same format as passed. Furthermore all get methods
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silently ignore key errors to not cause problems when untrusted user data
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is passed to the get methods which is often the case in web applications.
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:param servers: a list or tuple of server addresses or alternatively
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a :class:`memcache.Client` or a compatible client.
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:param default_timeout: the default timeout that is used if no timeout is
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specified on :meth:`~BaseCache.set`.
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:param key_prefix: a prefix that is added before all keys. This makes it
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possible to use the same memcached server for different
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applications. Keep in mind that
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:meth:`~BaseCache.clear` will also clear keys with a
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different prefix.
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"""
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def __init__(self, servers=None, default_timeout=300, key_prefix=None):
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BaseCache.__init__(self, default_timeout)
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if servers is None or isinstance(servers, (list, tuple)):
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if servers is None:
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servers = ['127.0.0.1:11211']
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self._client = self.import_preferred_memcache_lib(servers)
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if self._client is None:
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raise RuntimeError('no memcache module found')
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else:
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# NOTE: servers is actually an already initialized memcache
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# client.
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self._client = servers
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self.key_prefix = to_native(key_prefix)
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def _normalize_key(self, key):
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key = to_native(key, 'utf-8')
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if self.key_prefix:
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key = self.key_prefix + key
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return key
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def _normalize_timeout(self, timeout):
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return int(time()) + timeout
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def get(self, key):
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key = self._normalize_key(key)
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# memcached doesn't support keys longer than that. Because often
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# checks for so long keys can occur because it's tested from user
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# submitted data etc we fail silently for getting.
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if _test_memcached_key(key):
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return self._client.get(key)
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def get_dict(self, *keys):
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key_mapping = {}
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have_encoded_keys = False
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for key in keys:
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encoded_key = self._normalize_key(key)
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if not isinstance(key, str):
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have_encoded_keys = True
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if _test_memcached_key(key):
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key_mapping[encoded_key] = key
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d = rv = self._client.get_multi(key_mapping.keys())
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if have_encoded_keys or self.key_prefix:
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rv = {}
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for key, value in iteritems(d):
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rv[key_mapping[key]] = value
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if len(rv) < len(keys):
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for key in keys:
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if key not in rv:
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rv[key] = None
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return rv
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def add(self, key, value, timeout=None):
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if timeout is None:
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timeout = self.default_timeout
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key = self._normalize_key(key)
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timeout = self._normalize_timeout(timeout)
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return self._client.add(key, value, timeout)
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def set(self, key, value, timeout=None):
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if timeout is None:
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timeout = self.default_timeout
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key = self._normalize_key(key)
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timeout = self._normalize_timeout(timeout)
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return self._client.set(key, value, timeout)
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def get_many(self, *keys):
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d = self.get_dict(*keys)
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return [d[key] for key in keys]
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def set_many(self, mapping, timeout=None):
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if timeout is None:
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timeout = self.default_timeout
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new_mapping = {}
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for key, value in _items(mapping):
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key = self._normalize_key(key)
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new_mapping[key] = value
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timeout = self._normalize_timeout(timeout)
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failed_keys = self._client.set_multi(new_mapping, timeout)
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return not failed_keys
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def delete(self, key):
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key = self._normalize_key(key)
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if _test_memcached_key(key):
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return self._client.delete(key)
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def delete_many(self, *keys):
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new_keys = []
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for key in keys:
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key = self._normalize_key(key)
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if _test_memcached_key(key):
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new_keys.append(key)
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return self._client.delete_multi(new_keys)
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def clear(self):
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return self._client.flush_all()
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def inc(self, key, delta=1):
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key = self._normalize_key(key)
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return self._client.incr(key, delta)
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def dec(self, key, delta=1):
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key = self._normalize_key(key)
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return self._client.decr(key, delta)
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def import_preferred_memcache_lib(self, servers):
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"""Returns an initialized memcache client. Used by the constructor."""
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try:
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import pylibmc
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except ImportError:
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pass
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else:
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return pylibmc.Client(servers)
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try:
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from google.appengine.api import memcache
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except ImportError:
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pass
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else:
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return memcache.Client()
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try:
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import memcache
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except ImportError:
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pass
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else:
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return memcache.Client(servers)
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# backwards compatibility
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GAEMemcachedCache = MemcachedCache
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class RedisCache(BaseCache):
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"""Uses the Redis key-value store as a cache backend.
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The first argument can be either a string denoting address of the Redis
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server or an object resembling an instance of a redis.Redis class.
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Note: Python Redis API already takes care of encoding unicode strings on
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the fly.
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.. versionadded:: 0.7
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.. versionadded:: 0.8
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`key_prefix` was added.
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.. versionchanged:: 0.8
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This cache backend now properly serializes objects.
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.. versionchanged:: 0.8.3
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This cache backend now supports password authentication.
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.. versionchanged:: 0.10
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``**kwargs`` is now passed to the redis object.
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:param host: address of the Redis server or an object which API is
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compatible with the official Python Redis client (redis-py).
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:param port: port number on which Redis server listens for connections.
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:param password: password authentication for the Redis server.
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:param db: db (zero-based numeric index) on Redis Server to connect.
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:param default_timeout: the default timeout that is used if no timeout is
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specified on :meth:`~BaseCache.set`.
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:param key_prefix: A prefix that should be added to all keys.
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Any additional keyword arguments will be passed to ``redis.Redis``.
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"""
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def __init__(self, host='localhost', port=6379, password=None,
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db=0, default_timeout=300, key_prefix=None, **kwargs):
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BaseCache.__init__(self, default_timeout)
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if isinstance(host, string_types):
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try:
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import redis
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except ImportError:
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raise RuntimeError('no redis module found')
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if kwargs.get('decode_responses', None):
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raise ValueError('decode_responses is not supported by '
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'RedisCache.')
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self._client = redis.Redis(host=host, port=port, password=password,
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db=db, **kwargs)
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else:
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self._client = host
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self.key_prefix = key_prefix or ''
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def dump_object(self, value):
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"""Dumps an object into a string for redis. By default it serializes
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integers as regular string and pickle dumps everything else.
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"""
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t = type(value)
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if t in integer_types:
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return str(value).encode('ascii')
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return b'!' + pickle.dumps(value)
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def load_object(self, value):
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"""The reversal of :meth:`dump_object`. This might be callde with
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None.
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"""
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if value is None:
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return None
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if value.startswith(b'!'):
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try:
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return pickle.loads(value[1:])
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except pickle.PickleError:
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return None
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try:
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return int(value)
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except ValueError:
|
|
# before 0.8 we did not have serialization. Still support that.
|
|
return value
|
|
|
|
def get(self, key):
|
|
return self.load_object(self._client.get(self.key_prefix + key))
|
|
|
|
def get_many(self, *keys):
|
|
if self.key_prefix:
|
|
keys = [self.key_prefix + key for key in keys]
|
|
return [self.load_object(x) for x in self._client.mget(keys)]
|
|
|
|
def set(self, key, value, timeout=None):
|
|
if timeout is None:
|
|
timeout = self.default_timeout
|
|
dump = self.dump_object(value)
|
|
return self._client.setex(name=self.key_prefix + key,
|
|
value=dump, time=timeout)
|
|
|
|
def add(self, key, value, timeout=None):
|
|
if timeout is None:
|
|
timeout = self.default_timeout
|
|
dump = self.dump_object(value)
|
|
return (
|
|
self._client.setnx(name=self.key_prefix + key, value=dump) and
|
|
self._client.expire(name=self.key_prefix + key, time=timeout)
|
|
)
|
|
|
|
def set_many(self, mapping, timeout=None):
|
|
if timeout is None:
|
|
timeout = self.default_timeout
|
|
pipe = self._client.pipeline()
|
|
for key, value in _items(mapping):
|
|
dump = self.dump_object(value)
|
|
pipe.setex(name=self.key_prefix + key, value=dump, time=timeout)
|
|
return pipe.execute()
|
|
|
|
def delete(self, key):
|
|
return self._client.delete(self.key_prefix + key)
|
|
|
|
def delete_many(self, *keys):
|
|
if not keys:
|
|
return
|
|
if self.key_prefix:
|
|
keys = [self.key_prefix + key for key in keys]
|
|
return self._client.delete(*keys)
|
|
|
|
def clear(self):
|
|
status = False
|
|
if self.key_prefix:
|
|
keys = self._client.keys(self.key_prefix + '*')
|
|
if keys:
|
|
status = self._client.delete(*keys)
|
|
else:
|
|
status = self._client.flushdb()
|
|
return status
|
|
|
|
def inc(self, key, delta=1):
|
|
return self._client.incr(name=self.key_prefix + key, amount=delta)
|
|
|
|
def dec(self, key, delta=1):
|
|
return self._client.decr(name=self.key_prefix + key, amount=delta)
|
|
|
|
|
|
class FileSystemCache(BaseCache):
|
|
"""A cache that stores the items on the file system. This cache depends
|
|
on being the only user of the `cache_dir`. Make absolutely sure that
|
|
nobody but this cache stores files there or otherwise the cache will
|
|
randomly delete files therein.
|
|
|
|
:param cache_dir: the directory where cache files are stored.
|
|
:param threshold: the maximum number of items the cache stores before
|
|
it starts deleting some.
|
|
:param default_timeout: the default timeout that is used if no timeout is
|
|
specified on :meth:`~BaseCache.set`.
|
|
:param mode: the file mode wanted for the cache files, default 0600
|
|
"""
|
|
|
|
#: used for temporary files by the FileSystemCache
|
|
_fs_transaction_suffix = '.__wz_cache'
|
|
|
|
def __init__(self, cache_dir, threshold=500, default_timeout=300, mode=0o600):
|
|
BaseCache.__init__(self, default_timeout)
|
|
self._path = cache_dir
|
|
self._threshold = threshold
|
|
self._mode = mode
|
|
|
|
try:
|
|
os.makedirs(self._path)
|
|
except OSError as ex:
|
|
if ex.errno != errno.EEXIST:
|
|
raise
|
|
|
|
def _list_dir(self):
|
|
"""return a list of (fully qualified) cache filenames
|
|
"""
|
|
return [os.path.join(self._path, fn) for fn in os.listdir(self._path)
|
|
if not fn.endswith(self._fs_transaction_suffix)]
|
|
|
|
def _prune(self):
|
|
entries = self._list_dir()
|
|
if len(entries) > self._threshold:
|
|
now = time()
|
|
try:
|
|
for idx, fname in enumerate(entries):
|
|
remove = False
|
|
with open(fname, 'rb') as f:
|
|
expires = pickle.load(f)
|
|
remove = expires <= now or idx % 3 == 0
|
|
|
|
if remove:
|
|
os.remove(fname)
|
|
except (IOError, OSError):
|
|
pass
|
|
|
|
def clear(self):
|
|
for fname in self._list_dir():
|
|
try:
|
|
os.remove(fname)
|
|
except (IOError, OSError):
|
|
return False
|
|
return True
|
|
|
|
def _get_filename(self, key):
|
|
if isinstance(key, text_type):
|
|
key = key.encode('utf-8') #XXX unicode review
|
|
hash = md5(key).hexdigest()
|
|
return os.path.join(self._path, hash)
|
|
|
|
def get(self, key):
|
|
filename = self._get_filename(key)
|
|
try:
|
|
with open(filename, 'rb') as f:
|
|
if pickle.load(f) >= time():
|
|
return pickle.load(f)
|
|
else:
|
|
os.remove(filename)
|
|
return None
|
|
except (IOError, OSError, pickle.PickleError):
|
|
return None
|
|
|
|
def add(self, key, value, timeout=None):
|
|
filename = self._get_filename(key)
|
|
if not os.path.exists(filename):
|
|
return self.set(key, value, timeout)
|
|
return False
|
|
|
|
def set(self, key, value, timeout=None):
|
|
if timeout is None:
|
|
timeout = self.default_timeout
|
|
filename = self._get_filename(key)
|
|
self._prune()
|
|
try:
|
|
fd, tmp = tempfile.mkstemp(suffix=self._fs_transaction_suffix,
|
|
dir=self._path)
|
|
with os.fdopen(fd, 'wb') as f:
|
|
pickle.dump(int(time() + timeout), f, 1)
|
|
pickle.dump(value, f, pickle.HIGHEST_PROTOCOL)
|
|
rename(tmp, filename)
|
|
os.chmod(filename, self._mode)
|
|
except (IOError, OSError):
|
|
return False
|
|
else:
|
|
return True
|
|
|
|
def delete(self, key):
|
|
try:
|
|
os.remove(self._get_filename(key))
|
|
except (IOError, OSError):
|
|
return False
|
|
else:
|
|
return True
|