forked from bton/matekasse
197 lines
7 KiB
Python
197 lines
7 KiB
Python
import re
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import typing as _t
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from time import time
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from cachelib.base import BaseCache
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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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- ``libmc``
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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`. A timeout of
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0 indicates that the cache never expires.
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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__(
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self,
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servers: _t.Any = None,
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default_timeout: int = 300,
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key_prefix: _t.Optional[str] = None,
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):
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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 = key_prefix
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def _normalize_key(self, key: str) -> str:
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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: _t.Optional[int]) -> int:
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timeout = BaseCache._normalize_timeout(self, timeout)
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if timeout > 0:
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timeout = int(time()) + timeout
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return timeout
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def get(self, key: str) -> _t.Any:
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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: str) -> _t.Dict[str, _t.Any]:
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key_mapping = {}
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for key in keys:
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encoded_key = self._normalize_key(key)
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if _test_memcached_key(key):
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key_mapping[encoded_key] = key
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_keys = list(key_mapping)
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d = rv = self._client.get_multi(_keys) # type: _t.Dict[str, _t.Any]
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if self.key_prefix:
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rv = {}
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for key, value in d.items():
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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: str, value: _t.Any, timeout: _t.Optional[int] = None) -> bool:
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key = self._normalize_key(key)
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timeout = self._normalize_timeout(timeout)
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return bool(self._client.add(key, value, timeout))
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def set(
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self, key: str, value: _t.Any, timeout: _t.Optional[int] = None
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) -> _t.Optional[bool]:
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key = self._normalize_key(key)
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timeout = self._normalize_timeout(timeout)
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return bool(self._client.set(key, value, timeout))
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def get_many(self, *keys: str) -> _t.List[_t.Any]:
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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(
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self, mapping: _t.Dict[str, _t.Any], timeout: _t.Optional[int] = None
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) -> _t.List[_t.Any]:
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new_mapping = {}
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for key, value in mapping.items():
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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(
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new_mapping, timeout
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) # type: _t.List[_t.Any]
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k_normkey = zip(mapping.keys(), new_mapping.keys()) # noqa: B905
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return [k for k, nkey in k_normkey if nkey not in failed_keys]
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def delete(self, key: str) -> bool:
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key = self._normalize_key(key)
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if _test_memcached_key(key):
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return bool(self._client.delete(key))
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return False
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def delete_many(self, *keys: str) -> _t.List[_t.Any]:
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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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self._client.delete_multi(new_keys)
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return [k for k in new_keys if not self.has(k)]
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def has(self, key: str) -> bool:
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key = self._normalize_key(key)
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if _test_memcached_key(key):
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return bool(self._client.append(key, ""))
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return False
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def clear(self) -> bool:
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return bool(self._client.flush_all())
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def inc(self, key: str, delta: int = 1) -> _t.Optional[int]:
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key = self._normalize_key(key)
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value = (self._client.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: str, delta: int = 1) -> _t.Optional[int]:
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key = self._normalize_key(key)
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value = (self._client.get(key) or 0) - delta
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return value if self.set(key, value) else None
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def import_preferred_memcache_lib(self, servers: _t.Any) -> _t.Any:
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"""Returns an initialized memcache client. Used by the constructor."""
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try:
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import pylibmc # type: ignore
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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 # type: ignore
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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 # type: ignore
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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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try:
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import libmc # type: ignore
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except ImportError:
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pass
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else:
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return libmc.Client(servers)
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