What is Memoization?

In this lesson, we will learn about a result storing technique used in top-down dynamic programming.

We'll cover the following

We saw in the last chapter what we mean by the top-down approach. It essentially means that we start looking at the problem as a whole, then break it down into smaller and smaller units, and then evaluate those units that produce the answer to our original problem. Recursion acts as a natural way to write a top-down dynamic algorithm. The process of storing evaluated results in the top-down approach is called memoization.


No, we did not make a typo, its memoization, without an r. Memoization is defined as:

The act of storing results of costly function call, and retrieving them from the store when needed again to avoid re-evaluation.

The way to memoize

The most typical way to memoize results is by using hashtables. Hashtables are arrays that can be indexed using variable types other than integers. As we have already seen, we may need to store results against strings, floats, and even objects. Hashtables allow us to do all of this quite easily. The only condition for using hashtables is that keys should be unique. In Python, we can use the dictionary data structure as a hash table. The dictionary allows us to store data in the form of key-value pairs in an unordered collection of data values. The code snippet below shows the usage of a dictionary in Python.

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