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stockpyle is simple multi-layered storage and caching API

Project description

Description

stockpyle provides a simple way to set up a series of storage containers for the purposes of creating simple write-through cache storage.

Usage

Simplest script that sets up a two-level cache with memcached and local process memory:

from stockpyle import ChainedStore, MemcacheStore, ProcessMemoryStore

# instantiate the ChainedStore as a write-through cache
pm = ProcessMemoryStore()
mc = MemcacheStore(servers=["localhost:11711"])
store = ChainedStore([pm, mc])

# declare a class that is unique for each (bar,zap) combination
class Foo(object):

    __stockpyle_keys__ = [("bar", "zap")]

    def __init__(self, bar, zap):
        self.bar = bar
        self.zap = zap

# create and save a Foo to the ChainedStore
obj = Foo(bar=444, zap=888)
store.put(obj)

# retrieve a Foo from the store, based on the (bar,zap) combination
# this will hit the local memory cache first, and will avoid memcache
# since the object is already cached there
retrieved_obj = store.get(Foo, {"bar": 444, "zap": 888})

This example isn’t that interesting, since we are using two caches. Let’s do one that supports SQLAlchemy objects:

from stockpyle.stores import ChainedStore, SqlAlchemyStore, MemcacheStore, ProcessMemoryStore

pm = ProcessMemoryStore()
mc = MemcacheStore(servers=["localhost:11711"])
sa = SqlAlchemyStore()
store = ChainedStore([pm, mc, sa])

# store it, this will write it through the cache and into the database
persistent_obj = MySqlAlchemyBackedClass()
store.put(persistent_obj)

Note the ordering in the ChainedStore declaration: the SqlAlchemyStore comes last, since it acts as the final persistence layer. Subsequent ‘get’ requests will attempt process memory, then attempt memcache, and finally check the database.

Want to grab a bunch of objects? Use batch_get:

obj1, obj2, obj3 = store.batch_get(Foo, [
    {"foo": 111, "bar": 777},
    {"foo": 222, "bar": 888},
    {"foo": 333, "bar": 999},
    ])

Want to store a bunch of objects? Use batch_put:

obj1 = Foo(111, 777)
obj2 = Foo(222, 888)
obj3 = Foo(333, 999)
store.batch_put([obj1, obj2, obj3])

Deleting objects is easy (batch deletes coming soon):

store.delete(obj1)

Project details


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