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Degrees

(CS50:AI project)

Background

According to the Six Degrees of Kevin Bacon game, anyone in the Hollywood film industry can be connected to Kevin Bacon within six steps, where each step consists of finding a film that two actors both starred in.

In this problem, we’re interested in finding the shortest path between any two actors by choosing a sequence of movies that connects them. For example, the shortest path between Jennifer Lawrence and Tom Hanks is 2: Jennifer Lawrence is connected to Kevin Bacon by both starring in “X-Men: First Class,” and Kevin Bacon is connected to Tom Hanks by both starring in “Apollo 13.”

We can frame this as a search problem: our states are people. Our actions are movies, which take us from one actor to another (it’s true that a movie could take us to multiple different actors, but that’s okay for this problem). Our initial state and goal state are defined by the two people we’re trying to connect. By using breadth-first search, we can find the shortest path from one actor to another.

Understanding

The distribution code contains two sets of CSV data files: one set in the large directory the and one set in the small directory. Each contains files with the same names, and the same structure, but small is a much smaller dataset for ease of testing and experimentation.

Each dataset consists of three CSV files.

Open up small/people.csv. You’ll see that each person has a unique id, corresponding with their id in IMDb’s database. They also have a name, and a birth year.

Next, open up small/movies.csv. You’ll see here that each movie also has a unique id, in addition to a title and the year in which the movie was released.

Now, open up small/stars.csv. This file establishes a relationship between the people in people.csv and the movies in movies.csv. Each row is a pair of a person_id value and movie_id value. The first row (ignoring the header), for example, states that the person with id 102 starred in the movie with id 104257. Checking that against people.csv and movies.csv, you’ll find that this line is saying that Kevin Bacon starred in the movie “A Few Good Men.”

Next, take a look at degrees.py. At the top, several data structures are defined to store information from the CSV files. The names dictionary is a way to look up a person by their name: it maps names to a set of corresponding ids (because it’s possible that multiple actors have the same name). The people dictionary maps each person’s id to another dictionary with values for the person’s name, birth year, and the set of all the movies they have starred in. And the movies dictionary maps each movie’s id to another dictionary with values for that movie’s title, release year, and the set of all the movie’s stars. The load_data function loads data from the CSV files into these data structures.

The main function in this program first loads data into memory (the directory from which the data is loaded can be specified by a command-line argument). Then, the function prompts the user to type in two names. The person_id_for_name function retrieves the id for any person (and handles prompting the user to clarify, in the event that multiple people have the same name). The function then calls the shortest_path function to compute the shortest path between the two people, and prints out the path.

Example

python degrees.py large
Loading data...
Data loaded.
Name: Emma Watson
Name: Jennifer Lawrence
3 degrees of separation.
1: Emma Watson and Brendan Gleeson starred in Harry Potter and the Order of the Phoenix
2: Brendan Gleeson and Michael Fassbender starred in Trespass Against Us
3: Michael Fassbender and Jennifer Lawrence starred in X-Men: First Class

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