Pcc13

13/zambam5/directors.py

@@ -0,0 +1,70 @@
+# python3.11
+from collections import defaultdict, namedtuple
+import csv
+from urllib.request import urlretrieve
+
+# Note to start: in python 3.11 csv.DectReader rows are dicts, not OrderedDicts
+
+MOVIES_FILE = "movie_metadata.csv"
+MINIMUM_MOVIES = 4
+MINIMUM_YEAR = 1960
+
+Movie = namedtuple("Movie", "title year score")
+
+
+def get_directors_from_csv() -> defaultdict:
+    """
+    Organize the data from the provided csv in a convenient way
+    No movies before 1960
+    Remove superflous data
+    Some entries do not have years provided, so we use try-except to ignore those
+    """
+    directors = defaultdict(list)
+    # a dict with directors as keys and a list of data for each of their movies as values
+    with open(MOVIES_FILE, encoding="utf-8") as csvfile:
+        reader = csv.DictReader(csvfile)
+        for row in reader:
+            try:
+                year = int(row["title_year"])
+                if year >= MINIMUM_YEAR:
+                    title = row["movie_title"].replace("\xa0", "").replace("\xc2", "")
+                    score = float(row["imdb_score"])
+                    movie = Movie(title, year, score)
+                    directors[row["director_name"]].append(movie)
+            except ValueError:
+                continue
+    return directors
+
+
+def get_director_average_scores(directors: defaultdict) -> dict:
+    """
+    Return dict of directors and their average imbd scores
+    """
+    director_averages = dict()
+    for director, movies in directors.items():
+        number_of_movies = len(movies)
+        total_score = sum([movie.score for movie in movies])
+        director_averages[director] = round(total_score / number_of_movies, 1)
+    return director_averages
+
+
+def print_top_directors(directors: defaultdict) -> None:
+    """
+    Print the top 20 directors as directed in the challenge
+    """
+    averages = get_director_average_scores(directors)
+    averages_filtered = dict()
+    for director, movies in directors.items():
+        if len(movies) >= MINIMUM_MOVIES:
+            averages_filtered[director] = averages[director]
+    directors_sorted = sorted(averages_filtered, key=lambda x: -averages_filtered[x])
+    for counter, director in enumerate(directors_sorted[:20], 1):
+        print(f"{counter:02}. {director:<52} {averages[director]}")
+        print("-" * 60)
+        for movie in directors[director]:
+            print(f"{movie.year}] {movie.title:<50} {movie.score}")
+        print(" ")
+
+
+directors = get_directors_from_csv()
+print_top_directors(directors)