GenderEval.py

from collections import Counter
import praw
import time

female_indicators = ["I", "me", "my", "mine", "myself", "you", "your", "yours", "yourself", "she", "her", "hers",
                     "herself"]
male_indicators = ["we", "us", "they", "them", "he", "him", "his", "himself"]


def calculate_gender(comment_text):
    # What I'm doing here is called list comprehension. 
    # They're like one line for loops that create a list with the results.
    # Here's the breakdown: [(resulting item placed in list) (for statement) (condition)]
    word_list = comment_text.split()
    matched_female_words = [word for word in word_list if word in female_indicators]
    matched_male_words = [word for word in word_list if word in male_indicators]
    # Now we have lists of all the words matching each set of indicators, now we return their lengths
    return len(matched_female_words), len(matched_male_words)


def get_gender_numbers(target_user):
    user_comments = target_user.get_comments(sort="new", limit=10)
    gender_counter = Counter(female=0, male=0)
    for comment in user_comments:
        text = comment.body
        female, male = calculate_gender(text)
        gender_counter.update(female=female, male=male)  # increases female and male by the appropriate amounts
    return gender_counter


def main():
    now = time.time()
    r = praw.Reddit("Reddit User Demographics by /u/MusaTheRedGuard {}".format(now))

    username = input("Enter your reddit username: ")
    user = r.get_redditor(username)
    counter = get_gender_numbers(user)
    decision = 'female' if counter['female'] >= counter['male'] else 'male'

    print("The user {username} has {female_words} female comments and {male_words} male comments\n"
          "Therefore the user is likely {decision}.".format(username=username, female_words=counter['female'],
                                                             male_words=counter['male'], decision=decision))


if __name__ == '__main__':
    main()