2022-06-07 12:31:24 +00:00
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from flask import g
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import time
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import calendar
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import matplotlib.pyplot as plt
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2023-07-10 13:29:36 +00:00
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from sqlalchemy.sql import func
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2022-06-07 12:31:24 +00:00
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from files.classes.user import User
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2023-06-07 23:26:32 +00:00
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from files.classes.post import Post
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2022-06-07 12:31:24 +00:00
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from files.classes.comment import Comment
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2022-06-10 09:47:41 +00:00
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from files.classes.votes import Vote, CommentVote
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2023-03-18 13:34:04 +00:00
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from files.classes.emoji import *
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2022-06-10 09:47:41 +00:00
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from files.classes.award import AwardRelationship
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2022-12-11 23:44:34 +00:00
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from files.helpers.config.const import *
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def generate_charts_task(site):
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chart(kind='daily', site=site)
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2022-06-07 12:31:24 +00:00
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chart(kind='weekly', site=site)
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def chart(kind, site):
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now = time.gmtime()
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midnight_this_morning = time.struct_time((
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now.tm_year, now.tm_mon, now.tm_mday,
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0, 0, 0,
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now.tm_wday, now.tm_yday, 0))
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today_cutoff = calendar.timegm(midnight_this_morning)
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2023-05-13 02:00:31 +00:00
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num_of_weeks = 30
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2023-05-05 21:45:25 +00:00
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2023-05-04 21:25:19 +00:00
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chart_width = int(num_of_weeks/0.7)
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2022-06-07 12:31:24 +00:00
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if kind == 'daily':
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day_cutoffs = [today_cutoff - 86400 * i for i in range(num_of_weeks)][1:]
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else:
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day_cutoffs = [today_cutoff - 86400 * 7 * i for i in range(num_of_weeks)][1:]
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day_cutoffs.insert(0, calendar.timegm(now))
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2023-05-04 21:25:19 +00:00
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daily_times = [time.strftime('%Y-%m-%d', time.gmtime(day_cutoffs[i + 1]))
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for i in range(len(day_cutoffs) - 1)][::-1]
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2023-03-16 06:27:58 +00:00
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daily_signups = [g.db.query(User).filter(
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2023-01-01 11:36:20 +00:00
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User.created_utc < day_cutoffs[i],
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User.created_utc > day_cutoffs[i + 1]).count()
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2022-06-07 12:31:24 +00:00
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for i in range(len(day_cutoffs) - 1)][::-1]
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2023-06-07 23:26:32 +00:00
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post_stats = [g.db.query(Post).filter(
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Post.created_utc < day_cutoffs[i],
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Post.created_utc > day_cutoffs[i + 1],
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Post.is_banned == False).count()
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2022-06-07 12:31:24 +00:00
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for i in range(len(day_cutoffs) - 1)][::-1]
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2023-03-16 06:27:58 +00:00
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comment_stats = [g.db.query(Comment).filter(
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Comment.created_utc < day_cutoffs[i],
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Comment.created_utc > day_cutoffs[i + 1],
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Comment.is_banned == False,
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Comment.author_id != AUTOJANNY_ID).count()
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2022-06-07 12:31:24 +00:00
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for i in range(len(day_cutoffs) - 1)][::-1]
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2023-05-04 21:25:19 +00:00
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plt.rcParams['figure.figsize'] = (chart_width, chart_width)
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2023-05-04 21:25:19 +00:00
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signup_chart = plt.subplot2grid((chart_width, chart_width), (0, 0), rowspan=6, colspan=chart_width)
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posts_chart = plt.subplot2grid((chart_width, chart_width), (10, 0), rowspan=6, colspan=chart_width)
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comments_chart = plt.subplot2grid((chart_width, chart_width), (20, 0), rowspan=6, colspan=chart_width)
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2022-06-07 12:31:24 +00:00
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signup_chart.grid(), posts_chart.grid(), comments_chart.grid()
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2022-09-04 23:15:37 +00:00
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signup_chart.plot(daily_times, daily_signups, color='red')
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posts_chart.plot(daily_times, post_stats, color='blue')
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comments_chart.plot(daily_times, comment_stats, color='purple')
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2022-06-07 12:31:24 +00:00
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signup_chart.set_ylim(ymin=0)
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posts_chart.set_ylim(ymin=0)
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comments_chart.set_ylim(ymin=0)
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signup_chart.set_ylabel("Signups")
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posts_chart.set_ylabel("Posts")
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comments_chart.set_ylabel("Comments")
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comments_chart.set_xlabel("Time (UTC) YYYY-MM-DD")
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2022-06-07 12:31:24 +00:00
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file = chart_path(kind, site)
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2022-10-23 15:46:03 +00:00
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plt.savefig(file, bbox_inches='tight')
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2022-06-07 12:31:24 +00:00
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plt.clf()
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return file
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def chart_path(kind, site):
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return f'/{site}_{kind}.png'
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2022-06-10 09:47:41 +00:00
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2023-03-25 20:57:27 +00:00
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def stats():
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2022-11-06 00:14:58 +00:00
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now = time.time()
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day = int(now) - 86400
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week = int(now) - 604800
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posters = g.db.query(Post.author_id).distinct(Post.author_id).filter(Post.created_utc > week).all()
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commenters = g.db.query(Comment.author_id).distinct(Comment.author_id).filter(Comment.created_utc > week).all()
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voters = g.db.query(Vote.user_id).distinct(Vote.user_id).filter(Vote.created_utc > week).all()
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commentvoters = g.db.query(CommentVote.user_id).distinct(CommentVote.user_id).filter(CommentVote.created_utc > week).all()
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active_users = set(posters) | set(commenters) | set(voters) | set(commentvoters)
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stats = {
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2022-12-26 02:45:55 +00:00
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"time": int(time.time()),
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"marseys": "{:,}".format(g.db.query(Emoji).filter(Emoji.kind=="Marsey", Emoji.submitter_id==None).count()),
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"users": "{:,}".format(g.db.query(User).count()),
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"private users": "{:,}".format(g.db.query(User).filter_by(is_private=True).count()),
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"banned users": "{:,}".format(g.db.query(User).filter(User.is_banned != None).count()),
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"verified email users": "{:,}".format(g.db.query(User).filter_by(is_activated=True).count()),
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"coins in circulation": "{:,}".format(g.db.query(func.sum(User.coins)).scalar()),
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"total shop sales": "{:,}".format(g.db.query(func.sum(User.coins_spent)).scalar()),
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"signups last 24h": "{:,}".format(g.db.query(User).filter(User.created_utc > day).count()),
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"total posts": "{:,}".format(g.db.query(Post).count()),
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"posting users": "{:,}".format(g.db.query(Post.author_id).distinct().count()),
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"listed posts": "{:,}".format(g.db.query(Post).filter_by(is_banned=False).filter(Post.deleted_utc == 0).count()),
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"removed posts (by admins)": "{:,}".format(g.db.query(Post).filter_by(is_banned=True).count()),
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"deleted posts (by author)": "{:,}".format(g.db.query(Post).filter(Post.deleted_utc > 0).count()),
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"posts last 24h": "{:,}".format(g.db.query(Post).filter(Post.created_utc > day).count()),
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"total comments": "{:,}".format(g.db.query(Comment).filter(Comment.author_id != AUTOJANNY_ID).count()),
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"commenting users": "{:,}".format(g.db.query(Comment.author_id).distinct().count()),
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"removed comments (by admins)": "{:,}".format(g.db.query(Comment).filter_by(is_banned=True).count()),
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"deleted comments (by author)": "{:,}".format(g.db.query(Comment).filter(Comment.deleted_utc > 0).count()),
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"comments last 24h": "{:,}".format(g.db.query(Comment).filter(Comment.created_utc > day, Comment.author_id != AUTOJANNY_ID).count()),
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"post votes": "{:,}".format(g.db.query(Vote).count()),
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"comment votes": "{:,}".format(g.db.query(CommentVote).count()),
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"total upvotes": "{:,}".format(g.db.query(Vote).filter_by(vote_type=1).count() + g.db.query(CommentVote).filter_by(vote_type=1).count()),
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"total downvotes": "{:,}".format(g.db.query(Vote).filter_by(vote_type=-1).count() + g.db.query(CommentVote).filter_by(vote_type=-1).count()),
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"total awards": "{:,}".format(g.db.query(AwardRelationship).count()),
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2023-06-07 23:26:32 +00:00
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"awards given": "{:,}".format(g.db.query(AwardRelationship).filter(or_(AwardRelationship.post_id != None, AwardRelationship.comment_id != None)).count()),
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2022-11-02 05:06:01 +00:00
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"users who posted, commented, or voted in the past 7 days": "{:,}".format(len(active_users)),
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2023-03-16 06:27:58 +00:00
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"users online in the past 7 days": "{:,}".format(g.db.query(User).filter(User.last_active > week).count()),
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2022-06-10 09:47:41 +00:00
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}
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2022-08-01 19:37:57 +00:00
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if SITE_NAME == 'rDrama' or FEATURES['HOUSES']:
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stats2 = {
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2023-06-26 15:05:27 +00:00
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"House Furry members": "{:,}".format(g.db.query(User).filter(User.house.like('Furry%')).count()),
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"House Femboy members": "{:,}".format(g.db.query(User).filter(User.house.like('Femboy%')).count()),
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"House Vampire members": "{:,}".format(g.db.query(User).filter(User.house.like('Vampire%')).count()),
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"House Racist members": "{:,}".format(g.db.query(User).filter(User.house.like('Racist%')).count()),
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"House Edgy members": "{:,}".format(g.db.query(User).filter(User.house.like('Edgy%')).count()),
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"House Furry total truescore": "{:,}".format(g.db.query(func.sum(User.truescore)).filter(User.house.like('Furry%')).scalar() or 0),
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"House Femboy total truescore": "{:,}".format(g.db.query(func.sum(User.truescore)).filter(User.house.like('Femboy%')).scalar() or 0),
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"House Vampire total truescore": "{:,}".format(g.db.query(func.sum(User.truescore)).filter(User.house.like('Vampire%')).scalar() or 0),
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"House Racist total truescore": "{:,}".format(g.db.query(func.sum(User.truescore)).filter(User.house.like('Racist%')).scalar() or 0),
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"House Edgy total truescore": "{:,}".format(g.db.query(func.sum(User.truescore)).filter(User.house.like('Edgy%')).scalar() or 0),
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}
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stats.update(stats2)
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return stats
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