Q1

School

Georgia Institute Of Technology *

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Course

6242

Subject

Computer Science

Date

Feb 20, 2024

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Uploaded by ChiefBoar2052

import http.client import json import csv import requests class TMDBAPIUtils: # Do not modify def __init__(self, api_key:str): self.api_key=api_key def get_movie_credits_for_person(self, person_id:str, vote_avg_threshold:float=None)->list: url = f"https://api.themoviedb.org/3/person/{person_id}/movie_credits? api_key={self.api_key}&language=en-US" response = requests.get(url) if response.status_code != 200: return [] # or handle the error as needed credits_data = response.json()['cast'] if vote_avg_threshold is not None: credits_data = [ credit for credit in credits_data if credit.get('vote_average') is not None and credit['vote_average'] >= vote_avg_threshold ] # Restructure the data to include only 'id', 'title', and 'vote_average' credits_data = [ {'id': credit['id'], 'title': credit['title'], 'vote_avg': credit['vote_average']} for credit in credits_data if ('id' in credit and 'title' in credit and 'vote_average' in credit and credit['vote_average'] >= vote_avg_threshold) ] return credits_data def get_movie_cast(self, movie_id: str, limit: int = None, exclude_ids: list = None) -> list: # get the exclude_ids list!!!! # get the exclue_ids!!!!!! # Correct URL with dynamic movie_id url = f"https://api.themoviedb.org/3/movie/{movie_id}/credits? api_key={self.api_key}&language=en-US" response = requests.get(url) if response.status_code != 200: return [] full_cast_data = response.json()['cast'] # Apply exclude_ids filter if exclude_ids: full_cast_data = [member for member in full_cast_data if member['id']

not in exclude_ids] # If limit is specified, apply it if limit is not None: full_cast_data = [member for member in full_cast_data if member['order'] < limit] # Restructure the data to include specified fields cast_data = [ { 'movie_id': movie_id, 'id': member['id'], 'name': member['name'], 'cast_id': member['cast_id'], 'order': member['order'] } for member in full_cast_data ] return cast_data def return_name()->str: """ Return a string containing your GT Username e.g., gburdell3 Do not return your 9 digit GTId """ GTUsername = 'zhong61/zhong87' return GTUsername # You should modify __main__ as you see fit to build/test your graph using the TMDBAPIUtils & Graph classes. # Some boilerplate/sample code is provided for demonstration. We will not call __main__ during grading. class Graph: # Do not modify def __init__(self, with_nodes_file=None, with_edges_file=None): """ Initialize a Graph object. """ self.nodes = [] self.edges = [] if with_nodes_file and with_edges_file: nodes_CSV = csv.reader(open(with_nodes_file)) nodes_CSV = list(nodes_CSV)[1:] self.nodes = [(n[0], n[1]) for n in nodes_CSV] edges_CSV = csv.reader(open(with_edges_file)) edges_CSV = list(edges_CSV)[1:] self.edges = [(e[0], e[1]) for e in edges_CSV] def add_node(self, id: str, name: str) -> None: """ Add a node to the graph if it does not already exist. """ if not any(node[0] == id for node in self.nodes):

self.nodes.append((id, name)) def add_edge(self, source: str, target: str) -> None: """ Add an edge between two nodes if it does not already exist. """ if source != target and (source, target) not in self.edges and (target, source) not in self.edges: self.edges.append((source, target)) def total_nodes(self) -> int: """ Return the total number of nodes in the graph. """ return len(self.nodes) def total_edges(self) -> int: """ Return the total number of edges in the graph. """ return len(self.edges) def max_degree_nodes(self) -> dict: """ Return the node(s) with the highest degree. """ degree_count = {node[0]: 0 for node in self.nodes} for edge in self.edges: degree_count[edge[0]] += 1 degree_count[edge[1]] += 1 max_degree = max(degree_count.values()) return {node: degree for node, degree in degree_count.items() if degree == max_degree} def print_nodes(self): """ Print all nodes. Used for debugging. """ print(self.nodes) def print_edges(self): """ Print all edges. Used for debugging. """ print(self.edges) # Do not modify def write_edges_file(self, path="edges.csv")->None: """ Write all edges out as .csv. """ with open(path, 'w', encoding='utf-8') as edges_file: edges_file.write("source,target\n") for e in self.edges: edges_file.write(f"{e[0]},{e[1]}\n") # Do not modify def write_nodes_file(self, path="nodes.csv")->None:

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""" Write all nodes out as .csv. """ with open(path, 'w', encoding='utf-8') as nodes_file: nodes_file.write("id,name\n") for n in self.nodes: nodes_file.write(f"{n[0]},{n[1]}\n") # comment the original section out: if __name__ == "__main__": person_id = '2975' # Laurence Fishburne actor_name = 'Laurence Fishburne' vote_avg_threshold = 8.0 credit_limit = 3 tmdb_api_utils = TMDBAPIUtils(api_key='14386f6d2560c16967a0141156e72327') graph = Graph() # Define movie IDs to exclude exclude_movie_ids = [] # Example movie IDs to exclude # Add the initial actor graph.add_node(person_id, actor_name) actors_to_process = set([person_id]) # Perform iterations for iteration in range(3): # Including the initial setup and two additional iterations new_actors_to_process = set() print(f"\nIteration {iteration}:") for actor_id in actors_to_process: print(f"Actor ID {actor_id}") movie_credits = tmdb_api_utils.get_movie_credits_for_person(actor_id, vote_avg_threshold) # Filter out the excluded movie IDs filtered_movie_credits = [movie for movie in movie_credits if movie['id'] not in exclude_movie_ids] for movie in filtered_movie_credits: print(f"- Movie ID: {movie['id']}, Title: {movie['title']}") movie_id = str(movie['id']) cast_data = tmdb_api_utils.get_movie_cast(movie_id, credit_limit) for cast_member in cast_data: cast_member_id = str(cast_member['id']) if cast_member_id != actor_id: print(f" -- Cast Member ID: {cast_member_id}, Name: {cast_member['name']}") if cast_member_id not in [node[0] for node in graph.nodes]: graph.add_node(cast_member_id, cast_member['name']) new_actors_to_process.add(cast_member_id) if not any(edge in [(actor_id, cast_member_id), (cast_member_id, actor_id)] for edge in graph.edges): graph.add_edge(actor_id, cast_member_id) actors_to_process = new_actors_to_process

# Print and write final graph print("\nFinal Nodes:") for node in graph.nodes: print(f"{node[0]}, {node[1]}") print("\nFinal Edges:") for edge in graph.edges: print(f"{edge[0]}, {edge[1]}") graph.write_edges_file() graph.write_nodes_file()

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