old_contents: from __future__ import print_function, division
  import io_utils
  import scraper
  import praw
  import pandas as pd
  from config import Config
  
  options = Config()
  reddit = praw.Reddit(user_agent = options.user_agent)
  
  new_posts = reddit.get_subreddit(options.network_hub).get_new(limit=options.post_limit)
  
  def get_new_authors(post_generator, author_list=None):
      """Basic syntax to gather a list of post and comment authors
      gathered from new posts on the target subreddit
  
      To Do:
      - More structured data processing
      - Maybe flatten the comment tree?
      """
  
      if not author_list:
          author_list = []
  
      for post in post_generator:
          author_list.append(post.author.name)
          for comment in post.comments:
              author_list.append(comment.author.name)
  
      author_df = pd.DataFrame({'user_name': author_list, 'highest_post_id': ""})
      author_df = author_df.drop_duplicates('user_name')
      print('%d new authors found!' % (len(author_df.user_name)))
      return author_df
  
  def get_user_comments(username):
      # I'm fairly positive this doesn't actually work
      user_comments = user.get_submitted(limit=10)
  
new_contents: from __future__ import print_function, division
  import time
  import io_utils
  import scraper
  import praw
  import pandas as pd
  from config import Config
  
  options = Config()
  reddit = praw.Reddit(user_agent = options.user_agent)
  
  new_posts = reddit.get_subreddit(options.network_hub).get_new(limit=options.post_limit)
  
  def get_new_authors(reddit_post_generator, author_list=None):
      """Basic syntax to gather a list of post and comment authors
      gathered from new posts on the target subreddit
  
      To Do:
      - More structured data processing
      - Maybe flatten the comment tree?
      """
  
      if not author_list:
          author_list = []
  
      for post in reddit_post_generator:
          author_list.append(post.author.name)
          for comment in post.comments:
              author_list.append(comment.author.name)
  
      author_df = pd.DataFrame({'user_name': author_list, 'highest_post_id': ""})
      author_df = author_df.drop_duplicates('user_name')
      print('%d new authors found!' % (len(author_df.user_name)))
      return author_df
  
  def comment_parser(reddit_comment_object):
  
      post_timestamp = reddit_comment_object.created_utc
      score = reddit_comment_object.score
      ups = reddit_comment_object.ups
      downs = reddit_comment_object.downs
      post_body = reddit_comment_object.body
      link_title = reddit_comment_object.link_title
      link_id = reddit_comment_object.link_id
      link_author = reddit_comment_object.link_author
      subreddit = reddit_comment_object.subreddit.display_name
  
      return post_timestamp, score, ups, downs, post_body, link_title, link_id, link_author, subreddit
  
  
  def get_user_comments(reddit_user_object, comment_dataframe=None):
  
      user_name = reddit_user_object.name
      user_comments = reddit_user_object.get_comments(limit=1000) # Due to reddit's caching, 1000 is the absolute max
  
      if not comment_dataframe:
          comment_dataframe = pd.DataFrame(columns=[
          'user_name',
          'post_timestamp',
          'score',
          'ups',
          'downs',
          'post_body',
          'link_title',
          'link_id',
          'link_author',
          'subreddit',
          'timestamp'
          ])
  
      for comment in user_comments:
          post_timestamp, score, ups, downs, post_body, link_title, link_id, link_author, subreddit = comment_parser(comment)
          comment_dataframe = comment_dataframe.append({
          'user_name': user_name,
          'post_timestamp': post_timestamp,
          'score': score,
          'ups': ups,
          'downs': downs,
          'post_body': post_body,
          'link_title': link_title,
          'link_id': link_id,
          'link_author': link_author,
          'subreddit': subreddit,
          'timestamp': time.time()}, ignore_index=True)
  
      return comment_dataframe
  
subject: comment parsing