def main(json_file, genre_file):
# Load the points file from CSV
genres = load_points_file(genre_file)
keywords = set(g.keyword for g in genres)
results = {}
for book in load_json(json_file): # Loads the json as a stream/iterable
hits = count_keyword_hits(keywords, book['description'])
results[book['title']] = calc_genre_fit(genres, hits)
print_results(results) # Print at the end for alphabetical sort
def test_calc_genre_fit():
"""
{'ran': 1, 'boy': 1, 'dog': 3, 'barked': 1}
canine average -> 'dog': 6 + 'barked': 8 + 'ran': 4 = 18 / 3 = 6
human average -> 'boy': 6 + 'ran': 4 = 10 / 2 = 5
Three unique keyword hits for DOG keywords: 3x10 = 30
Two unique keyword hits for HUMAN keywords: 2x5 = 10
No hits for BIRD: 0
{'canine': 30, 'human': 10, 'bird': 0}
"""
keywords = set(g.keyword for g in GENRES)
hits = count_keyword_hits(keywords, TEST_TEXT)
res = calc_genre_fit(GENRES, hits)
assert res['canine'] == 30
assert res['human'] == 10
assert res['bird'] == 0
