from collections import Counter
import cPickle as pickle
import matplotlib.pyplot as plt
import numpy as np
import praw


def collect_data():
    print("Connecting to Reddit...")
    reddit = praw.Reddit(client_id='aaaaa',
                         client_secret='bbbbb',
                         password='ccccc',
                         user_agent='ddddd',
                         username='eeeee')
    print("Connected.")
    print("-----")

    submissions_counter = Counter()
    comments_counter = Counter()

    counter = 0
    for submission in reddit.subreddit('korea').submissions(start=1483228800,
                                                            end=1510364058):
        print(counter)
        counter += 1
        print(submission.title)
        submissions_counter[submission.author] += 1

        submission.comments.replace_more(limit=30)
        for comment in submission.comments.list():
            comments_counter[comment.author] += 1

    pickle.dump(submissions_counter, open("submissions.p", "wb"))
    pickle.dump(comments_counter, open("comments.p", "wb"))


def load_data():
    submissions_counter = pickle.load(open("submissions.p", "rb"))
    comments_counter = pickle.load(open("comments.p", "rb"))
    return submissions_counter, comments_counter


def make_graph(names, comments):
    pos = np.arange(500) * 20
    plt.figure(figsize=(15, 200))
    plt.barh(pos, comments, height=10, align='center')
    plt.yticks(pos, names)
    plt.xlabel("Number of comments")
    plt.tight_layout()
    plt.ylim([-20, 10000])
    plt.gca().invert_yaxis()
    for i, v in enumerate(comments):
        plt.text(v + 5, i * 20 + 2, str(v),
                 color='blue', fontweight='bold')
    plt.savefig('submission.png')

s, c = load_data()
c_most = c.most_common(500)
a = {x: c[x] for x in c if c[x] >= 30}
i = 0
for each in a:
    i += 1
print(i)