normalize_reddit_comment_scores.py

import arrow
import praw
import collections

import argparse
import logging

parser = argparse.ArgumentParser(description='Manage relative comment ranking.')
parser.add_argument("-v", "--verbose", help="enable logging", action="store_true")

args = parser.parse_args()
if args.verbose:
    logging.basicConfig(level=logging.INFO)

reddit = praw.Reddit(client_id='51SqtrEzmCTnuA',
                     client_secret='xehsxI2Sm81wHZpSa_PcmKcv5_k',
                     user_agent='me-on-reddit')

def get_comment_score_distibution( subreddit, weeks_in_past=25 ):
    scores = []
    end = arrow.utcnow()
    start = end.replace(weeks=-weeks_in_past)
    submissions = reddit.subreddit(subreddit).submissions(start.timestamp, end.timestamp)

    for s in submissions:
        submissions.replace_more() # expand comment sub-trees
        for c in s.comments:
            scores.append(c.score)
        logging.info('Submission completed.')

    return collections.Counter(scores)


def percentile_rank( score, scores_and_their_frequencies ):
    less_than = 0
    N = len(scores_and_their_frequencies)
    for s in scores_and_their_frequencies:
        if s < score:
            less_than_count += scores_and_their_frequencies[s]
        elif s == score:
            equal_count = scores_and_their_frequencies[score]

    return ((less_than_count + (0.5 * equal_count)) / N ) * 100

if __name__ == '__main__':
    d = get_comment_score_distibution('samharris', weeks_in_past=2)
    print(d)