Source code for aiocache.lock

import asyncio
import uuid

from typing import Type, Union, Any

from aiocache.base import BaseCache

[docs]class RedLock: """ Implementation of `Redlock <>`_ with a single instance because aiocache is focused on single instance cache. This locking has some limitations and shouldn't be used in situations where consistency is critical. Those locks are aimed for performance reasons where failing on locking from time to time is acceptable. TLDR: do NOT use this if you need real resource exclusion. Couple of considerations with the implementation: - If the lease expires and there are calls waiting, all of them will pass (blocking just happens for the first time). - When a new call arrives, it will wait always at most lease time. This means that the call could end up blocked longer than needed in case the lease from the blocker expires. Backend specific implementation: - Redis implements correctly the redlock algorithm. It sets the key if it doesn't exist. To release, it checks the value is the same as the instance trying to release and if it is, it removes the lock. If not it will do nothing - Memcached follows the same approach with a difference. Due to memcached lacking a way to execute the operation get and delete commands atomically, any client is able to release the lock. This is a limitation that can't be fixed without introducing race conditions. - Memory implementation is not distributed, it will only apply to the process running. Say you have 4 processes running APIs with aiocache, the locking will apply only per process (still useful to reduce load per process). Example usage:: from aiocache import RedisCache from aiocache.lock import RedLock cache = RedisCache() async with RedLock(cache, 'key', lease=1): # Calls will wait here result = await cache.get('key') if result is not None: return result result = await super_expensive_function() await cache.set('key', result) In the example, first call will start computing the ``super_expensive_function`` while consecutive calls will block at most 1 second. If the blocking lasts for more than 1 second, the calls will proceed to also calculate the result of ``super_expensive_function``. """ _EVENTS = {} def __init__(self, client: Type[BaseCache], key: str, lease: Union[int, float]): self.client = client self.key = self.client._build_key(key + '-lock') = lease self._value = "" async def __aenter__(self): return await self._acquire() async def _acquire(self): self._value = str(uuid.uuid4()) try: await self.client._add( self.key, self._value, RedLock._EVENTS[self.key] = asyncio.Event() except ValueError: await self._wait_for_release() async def _wait_for_release(self): try: await asyncio.wait_for( RedLock._EVENTS[self.key].wait(), except asyncio.TimeoutError: pass except KeyError: # lock was released when wait_for was rescheduled pass async def __aexit__(self, exc_type, exc_value, traceback): return await self._release() async def _release(self): removed = await self.client._redlock_release(self.key, self._value) if removed: RedLock._EVENTS.pop(self.key).set() return removed
[docs]class OptimisticLock: """ Implementation of `optimistic lock <>`_ Optimistic locking assumes multiple transactions can happen at the same time and they will only fail if before finish, conflicting modifications with other transactions are found, producing a roll back. Finding a conflict will end up raising an `aiocache.lock.OptimisticLockError` exception. A conflict happens when the value at the storage is different from the one we retrieved when the lock started. Example usage:: cache = RedisCache() # The value stored in 'key' will be checked here async with OptimisticLock(cache, 'key') as lock: result = await super_expensive_call() await lock.cas(result) If any other call sets the value of ``key`` before the ``lock.cas`` is called, an :class:`aiocache.lock.OptimisticLockError` will be raised. A way to make the same call crash would be to change the value inside the lock like:: cache = RedisCache() # The value stored in 'key' will be checked here async with OptimisticLock(cache, 'key') as lock: result = await super_expensive_call() await cache.set('random_value') # This will make the `lock.cas` call fail await lock.cas(result) If the lock is created with an unexisting key, there will never be conflicts. """ def __init__(self, client: Type[BaseCache], key: str): self.client = client self.key = key self.ns_key = self.client._build_key(key) self._token = None async def __aenter__(self): return await self._acquire() async def _acquire(self): self._token = await self.client._gets(self.ns_key) return self async def __aexit__(self, exc_type, exc_value, traceback): pass
[docs] async def cas(self, value: Any, **kwargs) -> True: """ Checks and sets the specified value for the locked key. If the value has changed since the lock was created, it will raise an :class:`aiocache.lock.OptimisticLockError` exception. :raises: :class:`aiocache.lock.OptimisticLockError` """ success = await self.client.set(self.key, value, _cas_token=self._token, **kwargs) if not success: raise OptimisticLockError("Value has changed since the lock started") return True
class OptimisticLockError(Exception): """ Raised when a conflict is found during an optimistic lock """