forked from MarseyWorld/MarseyWorld
203 lines
8.3 KiB
Python
203 lines
8.3 KiB
Python
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from sqlalchemy import Column, func
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from flask import g
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from files.helpers.config.const import *
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from .badges import Badge
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from .emoji import *
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from .user import User
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from .userblock import UserBlock
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from .votes import Vote, CommentVote
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from .casino_game import CasinoGame
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from .post import Post
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from files.__main__ import cache
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class Leaderboard:
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"""
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Represents an request-context leaderboard. None of this is persisted yet,
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although this is probably a good idea to do at some point.
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"""
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all_users = None
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v_position = 0
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v_value = None
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v_appears_in_ranking = False
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user_func = None
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value_func = None
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def __init__(self, header_name, table_header_name, html_id, table_column_name,
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user_relative_url, query_function, criteria, v, value_func, users, limit=LEADERBOARD_LIMIT, desc=True):
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self.header_name = header_name
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self.table_header_name = table_header_name
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self.html_id = html_id
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self.table_column_name = table_column_name
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self.user_relative_url = user_relative_url
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self.limit = limit
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lb = query_function(criteria, v, users, limit, desc)
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self.all_users = lb[0]
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self.v_position = lb[1]
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self.v_value = lb[2]
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self.v_appears_in_ranking = self.v_position and self.v_position <= len(self.all_users)
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if value_func:
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self.user_func = lambda u:u
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self.value_func = value_func
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self.v_value = value_func(v)
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else:
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self.user_func = lambda u:u[0]
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self.value_func = lambda u: u[1] or 0
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self.desc = desc
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@classmethod
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def get_simple_lb(cls, order_by, v, users, limit, desc):
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leaderboard = users.order_by(order_by.desc()).limit(limit).all()
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position = None
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if v not in leaderboard:
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sq = g.db.query(User.id, func.rank().over(order_by=order_by.desc()).label("rank")).subquery()
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position = g.db.query(sq.c.id, sq.c.rank).filter(sq.c.id == v.id).limit(1).one()[1]
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return (leaderboard, position, None)
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@classmethod
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def count_and_label(cls, criteria):
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return func.count(criteria).label("count")
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@classmethod
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def sum_and_label(cls, criteria):
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return func.sum(criteria).label("sum")
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@classmethod
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def avg_and_label(cls, criteria1, criteria2):
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return (func.sum(criteria1)/func.count(criteria2)).label("avg")
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@classmethod
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def rank_filtered_rank_label_by_desc(cls, criteria):
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return func.rank().over(order_by=func.count(criteria).desc()).label("rank")
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@classmethod
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def rank_filtered_rank_label_by_desc_sum(cls, criteria):
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return func.rank().over(order_by=func.sum(criteria).desc()).label("rank")
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@classmethod
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def rank_filtered_rank_label_by_asc_sum(cls, criteria):
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return func.rank().over(order_by=func.sum(criteria).asc()).label("rank")
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@classmethod
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def rank_filtered_rank_label_by_desc_avg(cls, criteria1, criteria2):
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return func.rank().over(order_by=-func.sum(criteria1)/func.count(criteria2)).label("rank")
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@classmethod
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def get_badge_emoji_lb(cls, lb_criteria, v, users, limit, desc):
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sq = g.db.query(lb_criteria, cls.count_and_label(lb_criteria), cls.rank_filtered_rank_label_by_desc(lb_criteria))
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if lb_criteria == Emoji.author_id:
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sq = sq.filter(Emoji.kind.in_(["Marsey", "Platy", "Wolf", "Capy", "Carp", "Marsey Flags", "Marsey Alphabet"]))
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sq = sq.group_by(lb_criteria).subquery()
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sq_criteria = None
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if lb_criteria == Badge.user_id:
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sq_criteria = User.id == sq.c.user_id
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elif lb_criteria == Emoji.author_id:
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sq_criteria = User.id == sq.c.author_id
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else:
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raise ValueError("This leaderboard function only supports Badge.user_id and Emoji.author_id")
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leaderboard = g.db.query(User, sq.c.count).join(sq, sq_criteria).order_by(sq.c.count.desc())
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position = g.db.query(User.id, sq.c.rank, sq.c.count).join(sq, sq_criteria).filter(User.id == v.id).one_or_none()
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if position: position = (position[1], position[2])
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else: position = (leaderboard.count() + 1, 0)
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leaderboard = leaderboard.limit(limit).all()
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return (leaderboard, position[0], position[1])
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@classmethod
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def get_winnings_lb(cls, lb_criteria, v, users, limit, desc):
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if lb_criteria != CasinoGame.winnings:
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raise ValueError("This leaderboard function only supports CasinoGame.user_id")
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if desc: fn = cls.rank_filtered_rank_label_by_desc_sum
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else: fn = cls.rank_filtered_rank_label_by_asc_sum
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sq = g.db.query(CasinoGame.user_id, cls.sum_and_label(lb_criteria), fn(lb_criteria))
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sq = sq.group_by(CasinoGame.user_id).subquery()
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sq_criteria = User.id == sq.c.user_id
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if desc: order = sq.c.sum.desc()
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else: order = sq.c.sum
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leaderboard = g.db.query(User, sq.c.sum).join(sq, sq_criteria).order_by(order)
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position = g.db.query(User.id, sq.c.rank, sq.c.sum).join(sq, sq_criteria).filter(User.id == v.id).one_or_none()
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if position: position = (position[1], position[2])
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else: position = (leaderboard.count() + 1, 0)
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leaderboard = leaderboard.limit(limit).all()
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return (leaderboard, position[0], position[1])
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@classmethod
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def get_blockers_lb(cls, lb_criteria, v, users, limit, desc):
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if lb_criteria != UserBlock.target_id:
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raise ValueError("This leaderboard function only supports UserBlock.target_id")
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sq = g.db.query(lb_criteria, cls.count_and_label(lb_criteria)).group_by(lb_criteria).subquery()
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leaderboard = g.db.query(User, sq.c.count).join(User, User.id == sq.c.target_id).order_by(sq.c.count.desc())
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sq = g.db.query(lb_criteria, cls.count_and_label(lb_criteria), cls.rank_filtered_rank_label_by_desc(lb_criteria)).group_by(lb_criteria).subquery()
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position = g.db.query(sq.c.rank, sq.c.count).join(User, User.id == sq.c.target_id).filter(sq.c.target_id == v.id).limit(1).one_or_none()
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if not position: position = (leaderboard.count() + 1, 0)
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leaderboard = leaderboard.limit(limit).all()
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return (leaderboard, position[0], position[1])
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@classmethod
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def get_hat_lb(cls, lb_criteria, v, users, limit, desc):
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leaderboard = g.db.query(User, func.count(lb_criteria)).join(lb_criteria).group_by(User).order_by(func.count(lb_criteria).desc())
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sq = g.db.query(User.id, cls.count_and_label(lb_criteria), cls.rank_filtered_rank_label_by_desc(lb_criteria)).join(lb_criteria).group_by(User).subquery()
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position = g.db.query(sq.c.rank, sq.c.count).filter(sq.c.id == v.id).limit(1).one_or_none()
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if not position: position = (leaderboard.count() + 1, 0)
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leaderboard = leaderboard.limit(limit).all()
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return (leaderboard, position[0], position[1])
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@classmethod
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def get_upvotes_lb(cls, lb_criteria, v, users, limit, desc):
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users13 = cache.get("users13") or []
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users13_1 = cache.get("users13_1") or []
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users13_2 = cache.get("users13_2") or []
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users13_accs = g.db.query(User).filter(User.id.in_(users13_1)).all()
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users13_accs = sorted(users13_accs, key=lambda x: users13_1.index(x.id))
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users13_accs = tuple(zip(users13_accs, users13_2))
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try:
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pos13 = [x[0] for x in users13].index(v.id)
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pos13 = (pos13+1, users13[pos13][1])
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except: pos13 = (len(users13)+1, 0)
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return (users13_accs, pos13[0], pos13[1])
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@classmethod
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def get_downvotes_lb(cls, lb_criteria, v, users, limit, desc):
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users9 = cache.get("users9") or []
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users9_1 = cache.get("users9_1") or []
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users9_2 = cache.get("users9_2") or []
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users9_accs = g.db.query(User).filter(User.id.in_(users9_1)).all()
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users9_accs = sorted(users9_accs, key=lambda x: users9_1.index(x.id))
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users9_accs = tuple(zip(users9_accs, users9_2))
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try:
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pos9 = [x[0] for x in users9].index(v.id)
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pos9 = (pos9+1, users9[pos9][1])
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except: pos9 = (len(users9)+1, 0)
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return (users9_accs, pos9[0], pos9[1])
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@classmethod
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def get_avg_upvotes_lb(cls, lb_criteria, v, users, limit, desc):
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if lb_criteria == Post:
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minimum = 10
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else:
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minimum = 100
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sq = g.db.query(lb_criteria.author_id, cls.avg_and_label(lb_criteria.upvotes, lb_criteria.author_id)).filter_by(deleted_utc=0).group_by(lb_criteria.author_id).having(func.count(lb_criteria.author_id) >= minimum).subquery()
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leaderboard = g.db.query(User, sq.c.avg).join(User, User.id == sq.c.author_id).order_by(sq.c.avg.desc())
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sq = g.db.query(lb_criteria.author_id, cls.avg_and_label(lb_criteria.upvotes, lb_criteria.author_id), cls.rank_filtered_rank_label_by_desc_avg(lb_criteria.upvotes, lb_criteria.author_id)).filter_by(deleted_utc=0).group_by(lb_criteria.author_id).having(func.count(lb_criteria.author_id) >= minimum).subquery()
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position = g.db.query(sq.c.rank, sq.c.avg).join(User, User.id == sq.c.author_id).filter(sq.c.author_id == v.id).limit(1).one_or_none()
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if not position: position = (leaderboard.count() + 1, 0)
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leaderboard = leaderboard.limit(limit).all()
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return (leaderboard, position[0], position[1])
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