tvl-depot/scratch/data_structures_and_algorithms/memo.py

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import time
import random
from heapq import heappush, heappop
class Memo(object):
def __init__(self, size=1):
"""
Create a key-value data-structure that will never exceed `size`
members. Memo evicts the least-recently-accessed elements from itself
before adding inserting new key-value pairs.
"""
if size <= 0:
raise Exception("We do not support an empty memo")
self.xs = {}
self.heap = [(0, None)] * size
def contains(self, k):
"""
Return true if key `k` exists in the Memo.
"""
return k in self.xs
def get(self, k):
"""
Return the memoized item at key `k`.
"""
# "touch" the element in the heap
return self.xs[k]
def set(self, k, v):
"""
Memoize value `v` at key `k`.
"""
_, to_evict = heappop(self.heap)
if to_evict != None:
del self.xs[to_evict]
heappush(self.heap, (time.time(), k))
self.xs[k] = v
memo = Memo(size=10)
def f(x):
"""
Compute some mysterious, expensive function.
"""
if memo.contains(x):
print("Hit.\t\tf({})".format(x))
return memo.get(x)
else:
print("Computing...\tf({})".format(x))
time.sleep(0.25)
res = random.randint(0, 10)
memo.set(x, res)
return res
[f(random.randint(0, 10)) for _ in range(10)]