LRU cache with Redis

lru_cache_redis.py

# https://github.com/python/cpython/blob/master/Lib/functools.py
from collections import namedtuple
from functools import partial
import pickle
from my_redis import Client

WRAPPER_ASSIGNMENTS = ('__module__', '__name__', '__qualname__', '__doc__',
                       '__annotations__')
WRAPPER_UPDATES = ('__dict__',)
def update_wrapper(wrapper,
                   wrapped,
                   assigned = WRAPPER_ASSIGNMENTS,
                   updated = WRAPPER_UPDATES):
    """Update a wrapper function to look like the wrapped function
       wrapper is the function to be updated
       wrapped is the original function
       assigned is a tuple naming the attributes assigned directly
       from the wrapped function to the wrapper function (defaults to
       functools.WRAPPER_ASSIGNMENTS)
       updated is a tuple naming the attributes of the wrapper that
       are updated with the corresponding attribute from the wrapped
       function (defaults to functools.WRAPPER_UPDATES)
    """
    for attr in assigned:
        try:
            value = getattr(wrapped, attr)
        except AttributeError:
            pass
        else:
            setattr(wrapper, attr, value)
    for attr in updated:
        getattr(wrapper, attr).update(getattr(wrapped, attr, {}))
    # Issue #17482: set __wrapped__ last so we don't inadvertently copy it
    # from the wrapped function when updating __dict__
    wrapper.__wrapped__ = wrapped
    # Return the wrapper so this can be used as a decorator via partial()
    return wrapper

def wraps(wrapped,
          assigned = WRAPPER_ASSIGNMENTS,
          updated = WRAPPER_UPDATES):
    """Decorator factory to apply update_wrapper() to a wrapper function
       Returns a decorator that invokes update_wrapper() with the decorated
       function as the wrapper argument and the arguments to wraps() as the
       remaining arguments. Default arguments are as for update_wrapper().
       This is a convenience function to simplify applying partial() to
       update_wrapper().
    """
    return partial(update_wrapper, wrapped=wrapped,
                   assigned=assigned, updated=updated)

_CacheInfo = namedtuple("CacheInfo", ["hits", "misses", "maxsize", "currsize"])

class _HashedSeq(list):
    """ This class guarantees that hash() will be called no more than once
        per element.  This is important because the lru_cache() will hash
        the key multiple times on a cache miss.
    """

    __slots__ = 'hashvalue'

    def __init__(self, tup, hash=hash):
        self[:] = tup
        self.hashvalue = hash(tup)

    def __hash__(self):
        return self.hashvalue

def _make_key(args, kwds, typed,
             kwd_mark = (object(),),
             fasttypes = {int, str},
             tuple=tuple, type=type, len=len):
    """Make a cache key from optionally typed positional and keyword arguments
    The key is constructed in a way that is flat as possible rather than
    as a nested structure that would take more memory.
    If there is only a single argument and its data type is known to cache
    its hash value, then that argument is returned without a wrapper.  This
    saves space and improves lookup speed.
    """
    # All of code below relies on kwds preserving the order input by the user.
    # Formerly, we sorted() the kwds before looping.  The new way is *much*
    # faster; however, it means that f(x=1, y=2) will now be treated as a
    # distinct call from f(y=2, x=1) which will be cached separately.
    key = args
    if kwds:
        key += kwd_mark
        for item in kwds.items():
            key += item
    if typed:
        key += tuple(type(v) for v in args)
        if kwds:
            key += tuple(type(v) for v in kwds.values())
    elif len(key) == 1 and type(key[0]) in fasttypes:
        return key[0]
    return _HashedSeq(key)

def lru_cache_redis(maxsize=128, typed=False, redis_conn=None):
    """Least-recently-used cache decorator.
    If *maxsize* is set to None, the LRU features are disabled and the cache
    can grow without bound.
    If *typed* is True, arguments of different types will be cached separately.
    For example, f(3.0) and f(3) will be treated as distinct calls with
    distinct results.
    Arguments to the cached function must be hashable.
    View the cache statistics named tuple (hits, misses, maxsize, currsize)
    with f.cache_info().  Clear the cache and statistics with f.cache_clear().
    Access the underlying function with f.__wrapped__.
    See:  http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used
    """

    # Users should only access the lru_cache through its public API:
    #       cache_info, cache_clear, and f.__wrapped__
    # The internals of the lru_cache are encapsulated for thread safety and
    # to allow the implementation to change (including a possible C version).

    if isinstance(maxsize, int):
        # Negative maxsize is treated as 0
        if maxsize < 0:
            maxsize = 0
    elif callable(maxsize) and isinstance(typed, bool):
        # The user_function was passed in directly via the maxsize argument
        user_function, maxsize = maxsize, 128
        wrapper = _lru_cache_wrapper2(user_function, maxsize, typed, _CacheInfo, redis_conn)
        return update_wrapper(wrapper, user_function)
    elif maxsize is not None:
        raise TypeError(
            'Expected first argument to be an integer, a callable, or None')

    def decorating_function(user_function):
        wrapper = _lru_cache_wrapper2(user_function, maxsize, typed, _CacheInfo, redis_conn)
        return update_wrapper(wrapper, user_function)

    return decorating_function

def _lru_cache_wrapper_redis(user_function, maxsize, typed, _CacheInfo, redis_conn):
    make_key = _make_key         # build a key from the function arguments

    cache = redis_conn.conn
    hash_key = "lru_hash:" + user_function.__name__
    list_key = "lru_list:" + user_function.__name__

    if maxsize == 0:

        def wrapper(*args, **kwds):
            # No caching -- just a statistics update
            result = user_function(*args, **kwds)
            return result

    elif maxsize is None:

        def wrapper(*args, **kwds):
            # Simple caching without ordering or size limit
            key = make_key(args, kwds, typed)
            result = cache.hget(hash_key, key)
            print('result', result)
            if result:
                return pickle.loads(result)
            result = user_function(*args, **kwds)
            tmp = pickle.dumps(result)
            cache.hset(hash_key, key, tmp)
            return result

    else:

        def wrapper(*args, **kwds):
            key = make_key(args, kwds, typed)
            def first_update():
                link = cache.hget(hash_key, key)
                if link:
                    cache.lrem(list_key, 1, link)
                    cache.lpush(list_key, link)
                    result = pickle.loads(link)
                    return result
            redis_conn.dlm.exec_func(user_function.__name__, first_update)
            result = user_function(*args, **kwds)
            def second_update():
                if key in cache:
                    pass
                elif cache.llen(list_key) >= maxsize:
                    cache.hdel(hash_key, key)
                    cache.rpop(list_key)
                else:
                    tmp = pickle.dumps(result)
                    cache.hset(hash_key, key, tmp)
                    cache.lpush(list_key, cache.hget(hash_key, key))
            redis_conn.dlm.exec_func(user_function.__name__, second_update)
            return result

    def cache_info():
        """Report cache statistics"""
        def sub():
            return cache.llen(list_key)
        return redis_conn.dlm.exec_func(user_function.__name__, sub)

    def cache_clear():
        """Clear the cache and cache statistics"""
        def sub():
            cache.ltrim(list_key, 0 ,0)
            cache.hdel(hash_key, "*")
        redis_conn.dlm.exec_func(user_function.__name__, sub)

    wrapper.cache_info = cache_info
    wrapper.cache_clear = cache_clear
    return wrapper