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Using Recursion and a Python Class

00:00 Using Recursion and a Python Class. Your first approach to generating the Fibonacci sequence will use a Python class and recursion. An advantage of using a class over the memoized recursive function you saw earlier is that a class keeps state and behavior together within the same object.

00:20 This is known as encapsulation. In the function example, cache is a completely separate object, so you don’t have control over it. On-screen, you can see the code that implements a class-based solution.

00:36 Line 3 defines the Fibonacci class. Line 4 defines the class initializer, .__init__(). It’s a special method that you can use to initialize your class instances.

00:48 Special methods are sometimes referred to as dunder methods, short for double-underscore (__) methods. Line 5 creates the .cache instance attribute, which means that whenever you create a Fibonacci object, there will be a cache for it.

01:02 This attribute initially contains the first numbers in the Fibonacci sequence. Line 7 defines another special method, .__call__(). This method turns the instances of Fibonacci into callable objects. Lines 9 to 12 validate the value of n by using a conditional statement.

01:22 If n is not a positive integer, then the method raises a ValueError.

01:38 Line 15 defines a conditional statement to check the Fibonacci numbers that were already calculated and are present in the cache. If the number index n is already in the cache, then line 16 returns it.

01:53 Otherwise, line 19 computes the number, and line 20 appends it to the cache so you don’t have to compute it again. Finally, line 22 returns the requested Fibonacci number.

02:11 To try this code, go ahead and save it into Then run this code in your interactive shell in the same directory. Here you create and then call an instance of that Fibonacci class named fibonacci_of.

02:32 The first call uses 5 as an argument and returns 5, which is the sixth Fibonacci number because you’re using zero-based indices.

02:48 This implementation of the Fibonacci sequence algorithm is quite efficient. Once you have an instance of the class, the .cache attribute holds the already-computed numbers from call to call.

03:00 In the next section of the course, you’ll take a deeper dive to visualize what happens when calling this recursive algorithm to get a better understanding of recursion and how memoization makes the algorithm more efficient.

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