Can I memoize a Python generator?

Question

I have a function called runquery that makes calls to a database and then yields the rows, one by one. I wrote a memoize decorator (or more accurately, I just stole

Answer 1

Similar to the other answers, but simpler if you know that f is a generator:

def memoized_generator(f):
    cache = {}
    @functools.wraps(f)
    def wrapper(*args, **kwargs):
        k = args, frozenset(kwargs.items())
        it = cache[k] if k in cache else f(*args, **kwargs)
        cache[k], result = itertools.tee(it)
        return result
    return wrapper

Answer 2

from itertools import tee

sequence, memoized_sequence = tee (sequence, 2)

Done.

It is easier for generators because the standard lib has this "tee" method!

Answer 3

Yes. There's a decorator posted here. Take note that as the poster says, you lose some of the benefit of lazy evaluation.

def memoize(func):
    def inner(arg):
        if isinstance(arg, list):
            # Make arg immutable
            arg = tuple(arg)
        if arg in inner.cache:
            print "Using cache for %s" % repr(arg)
            for i in inner.cache[arg]:
                yield i
        else:
            print "Building new for %s" % repr(arg)
            temp = []
            for i in func(arg):
                temp.append(i)
                yield i
            inner.cache[arg] = temp
    inner.cache = {}
    return inner


@memoize
def gen(x):
    if not x:
        yield 0
        return

    for i in xrange(len(x)):
        for a in gen(x[i + 1:]):
            yield a + x[0]


print "Round 1"
for a in gen([2, 3, 4, 5]):
    print a

print
print "Round 2"
for a in gen([2, 3, 4, 5]):
    print a

Answer 4

I realise this is somewhat of an old question, but for those who want a full solution: here's one, based on jsbueno's suggestion:

from itertools import tee
from types import GeneratorType

Tee = tee([], 1)[0].__class__

def memoized(f):
    cache={}
    def ret(*args):
        if args not in cache:
            cache[args]=f(*args)
        if isinstance(cache[args], (GeneratorType, Tee)):
            # the original can't be used any more,
            # so we need to change the cache as well
            cache[args], r = tee(cache[args])
            return r
        return cache[args]
    return ret