1 files changed, 60 insertions, 0 deletions
diff --git a/users/wpcarro/scratch/data_structures_and_algorithms/memo.py b/users/wpcarro/scratch/data_structures_and_algorithms/memo.py
new file mode 100644
index 000000000000..44ea93e1bd49
--- /dev/null
+++ b/users/wpcarro/scratch/data_structures_and_algorithms/memo.py
@@ -0,0 +1,60 @@
+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)]