Decode the Coding Interview in Python: Real-World Examples/

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Feature #11: Generate Movie Viewing Orders

Feature #11: Generate Movie Viewing Orders

Implementing the "Generate Movie Viewing Orders" feature for our "Netflix" project.

We'll cover the following...

Description

We want to offer marathons for our viewers. Each marathon will have a fixed set of movies catering to a specific taste. For a given marathon, different viewing orders of the movies will yield different user satisfaction results. We want to experiment (A/B testing) with different viewing orders of the same marathon.

Your task is to generate all the possible permutations of movies in a given marathon.

Let’s look at an example to better understand this:

Solution

To solve this problem, we will use the backtracking approach.

We will assume a backtrack function that takes the index of the first movie to consider as an argument backtrack(first).

  • If the first movie to consider has index n, then that means that the current permutation is done.

  • We will iterate over the marathon from index first to index n - 1.

  • We will place the ith movie first in the permutation, that is, movies[first], movies[i] = movies[i], movies[first].

  • We will proceed to create all the permutations that start from the ith movie: backtrack(first + 1).

  • Now we will backtrack, that is, movies[first], movies[i] = movies[i], movies[first] back.

Let’s look at some illustrations to better understand this:

Note: We are using numbers to represent movies in the following illustration.

Let’s look at the code for this solution:

def backtrack(first,size, movies, output):
    # if all integers are used up
    if first == size:  
        output.append(movies[:])
    for i in range(first, size):
        # place i-th integer first 
        # in the current permutation
        movies[first], movies[i] = movies[i], movies[first]
        # use next integers to complete the permutations
        backtrack(first + 1,size, movies, output)
        # backtrack
        movies[first], movies[i] = movies[i], movies[first]
def generate_permutations(movies):
    
    size = len(movies)
    output = []
    backtrack(0, size, movies, output);
    return output
# Example #1
input = ["Frozen","Dune","Coco"]
output = generate_permutations(input)
print("Output 1: ", output)
# Example #2
input2 = ["Frozen","Dune","Coco","Melificient"]
output = generate_permutations(input2)
print("Output 2: ",output)
# Example #3
input3 = ["Dune","Coco"]
output = generate_permutations(input3)
print("Output 3: " , output)
Generate movie viewing orders

Complexity measures

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