import sqlalchemy as sa
import sqlalchemy.sql.functions as func
import time
+from collections import namedtuple
from pyramid.response import Response
from pyramid.url import current_route_url
from sqlalchemy import desc, distinct
return [{'status':'not implemented'}]
+def get_games_played(player_id):
+ """
+ Provides a breakdown by gametype of the games played by player_id.
+
+ Returns a list of namedtuples with the following members:
+ - game_type_cd
+ - games
+ - wins
+ - losses
+ - win_pct
+
+ The list itself is ordered by the number of games played
+ """
+ GamesPlayed = namedtuple('GamesPlayed', ['game_type_cd', 'games', 'wins',
+ 'losses', 'win_pct'])
+
+ raw_games_played = DBSession.query('game_type_cd', 'wins', 'losses').\
+ from_statement(
+ "SELECT game_type_cd, "
+ "SUM(win) wins, "
+ "SUM(loss) losses "
+ "FROM (SELECT g.game_id, "
+ "g.game_type_cd, "
+ "CASE "
+ "WHEN g.winner = pgs.team THEN 1 "
+ "WHEN pgs.rank = 1 THEN 1 "
+ "ELSE 0 "
+ "END win, "
+ "CASE "
+ "WHEN g.winner = pgs.team THEN 0 "
+ "WHEN pgs.rank = 1 THEN 0 "
+ "ELSE 1 "
+ "END loss "
+ "FROM games g, "
+ "player_game_stats pgs "
+ "WHERE g.game_id = pgs.game_id "
+ "AND pgs.player_id = :player_id) win_loss "
+ "GROUP BY game_type_cd "
+ ).params(player_id=player_id).all()
+
+ games_played = []
+ overall_games = 0
+ overall_wins = 0
+ overall_losses = 0
+ for row in raw_games_played:
+ games = row.wins + row.losses
+ overall_games += games
+ overall_wins += row.wins
+ overall_losses += row.losses
+ win_pct = float(row.wins)/games
+
+ games_played.append(GamesPlayed(row.game_type_cd, games, row.wins,
+ row.losses, win_pct))
+
+ try:
+ overall_win_pct = float(overall_wins)/overall_games
+ except:
+ overall_win_pct = 0.0
+
+ games_played.append(GamesPlayed('overall', overall_games, overall_wins,
+ overall_losses, overall_win_pct))
+
+ # sort the resulting list by # of games played
+ games_played = sorted(games_played, key=lambda x:x.games)
+ games_played.reverse()
+ return games_played
+
+
+def get_overall_stats(player_id):
+ """
+ Provides a breakdown of stats by gametype played by player_id.
+
+ Returns a dictionary of namedtuples with the following members:
+ - total_kills
+ - total_deaths
+ - k_d_ratio
+ - last_played (last time the player played the game type)
+ - total_playing_time (total amount of time played the game type)
+ - total_pickups (ctf only)
+ - total_captures (ctf only)
+ - cap_ratio (ctf only)
+ - total_carrier_frags (ctf only)
+ - game_type_cd
+
+ The key to the dictionary is the game type code. There is also an
+ "overall" game_type_cd which sums the totals and computes the total ratios.
+ """
+ OverallStats = namedtuple('OverallStats', ['total_kills', 'total_deaths',
+ 'k_d_ratio', 'last_played', 'total_playing_time', 'total_pickups',
+ 'total_captures', 'cap_ratio', 'total_carrier_frags', 'game_type_cd'])
+
+ raw_stats = DBSession.query('game_type_cd', 'total_kills',
+ 'total_deaths', 'last_played', 'total_playing_time',
+ 'total_pickups', 'total_captures', 'total_carrier_frags').\
+ from_statement(
+ "SELECT g.game_type_cd, "
+ "Sum(pgs.kills) total_kills, "
+ "Sum(pgs.deaths) total_deaths, "
+ "Max(pgs.create_dt) last_played, "
+ "Sum(pgs.alivetime) total_playing_time, "
+ "Sum(pgs.pickups) total_pickups, "
+ "Sum(pgs.captures) total_captures, "
+ "Sum(pgs.carrier_frags) total_carrier_frags "
+ "FROM games g, "
+ "player_game_stats pgs "
+ "WHERE g.game_id = pgs.game_id "
+ "AND pgs.player_id = :player_id "
+ "GROUP BY g.game_type_cd "
+ ).params(player_id=player_id).all()
+
+ # to be indexed by game_type_cd
+ overall_stats = {}
+
+ # sums for the "overall" game type (which is fake)
+ overall_kills = 0
+ overall_deaths = 0
+ overall_last_played = None
+ overall_playing_time = datetime.timedelta(seconds=0)
+ overall_carrier_frags = 0
+
+ for row in raw_stats:
+ # running totals or mins
+ overall_kills += row.total_kills or 0
+ overall_deaths += row.total_deaths or 0
+
+ if overall_last_played is None or row.last_played > overall_last_played:
+ overall_last_played = row.last_played
+
+ overall_playing_time += row.total_playing_time
+
+ # individual gametype ratio calculations
+ try:
+ k_d_ratio = float(row.total_kills)/row.total_deaths
+ except:
+ k_d_ratio = None
+
+ try:
+ cap_ratio = float(row.total_pickups)/row.total_captures
+ except:
+ cap_ratio = None
+
+ overall_carrier_frags += row.total_carrier_frags or 0
+
+ # everything else is untouched or "raw"
+ os = OverallStats(total_kills=row.total_kills,
+ total_deaths=row.total_deaths,
+ k_d_ratio=k_d_ratio,
+ last_played=row.last_played,
+ total_playing_time=row.total_playing_time,
+ total_pickups=row.total_pickups,
+ total_captures=row.total_captures,
+ cap_ratio=cap_ratio,
+ total_carrier_frags=row.total_carrier_frags,
+ game_type_cd=row.game_type_cd)
+
+ overall_stats[row.game_type_cd] = os
+
+ # and lastly, the overall stuff
+ try:
+ overall_k_d_ratio = float(overall_kills)/overall_deaths
+ except:
+ overall_k_d_ratio = None
+
+ os = OverallStats(total_kills=overall_kills,
+ total_deaths=overall_deaths,
+ k_d_ratio=overall_k_d_ratio,
+ last_played=overall_last_played,
+ total_playing_time=overall_playing_time,
+ total_pickups=None,
+ total_captures=None,
+ cap_ratio=None,
+ total_carrier_frags=overall_carrier_frags,
+ game_type_cd='overall')
+
+ overall_stats['overall'] = os
+
+ return overall_stats
+
+
+def get_fav_maps(player_id, game_type_cd=None):
+ """
+ Provides a breakdown of favorite maps by gametype.
+
+ Returns a dictionary of namedtuples with the following members:
+ - game_type_cd
+ - map_name (map name)
+ - map_id
+ - times_played
+
+ The favorite map is defined as the map you've played the most
+ for the given game_type_cd.
+
+ The key to the dictionary is the game type code. There is also an
+ "overall" game_type_cd which is the overall favorite map. This is
+ defined as the favorite map of the game type you've played the
+ most. The input parameter game_type_cd is for this.
+ """
+ raw_favs = DBSession.query('game_type_cd', 'map_name',
+ 'map_id', 'times_played').\
+ from_statement(
+ "SELECT game_type_cd, "
+ "name map_name, "
+ "map_id, "
+ "times_played "
+ "FROM (SELECT g.game_type_cd, "
+ "m.name, "
+ "m.map_id, "
+ "Count(*) times_played, "
+ "Row_number() "
+ "OVER ( "
+ "partition BY g.game_type_cd "
+ "ORDER BY Count(*) DESC, m.map_id ASC) rank "
+ "FROM games g, "
+ "player_game_stats pgs, "
+ "maps m "
+ "WHERE g.game_id = pgs.game_id "
+ "AND g.map_id = m.map_id "
+ "AND pgs.player_id = :player_id "
+ "GROUP BY g.game_type_cd, "
+ "m.map_id, "
+ "m.name) most_played "
+ "WHERE rank = 1 "
+ "ORDER BY times_played desc "
+ ).params(player_id=player_id).all()
+
+ fav_maps = {}
+ overall_fav = None
+ for row in raw_favs:
+ # if we aren't given a favorite game_type_cd
+ # then the overall favorite is the one we've
+ # played the most
+ if overall_fav is None:
+ fav_maps['overall'] = row
+ overall_fav = row.game_type_cd
+
+ # otherwise it is the favorite map from the
+ # favorite game_type_cd (provided as a param)
+ # and we'll overwrite the first dict entry
+ if game_type_cd == row.game_type_cd:
+ fav_maps['overall'] = row
+
+ fav_maps[row.game_type_cd] = row
+
+ return fav_maps
+
+
+def get_ranks(player_id):
+ """
+ Provides a breakdown of the player's ranks by game type.
+
+ Returns a dictionary of namedtuples with the following members:
+ - game_type_cd
+ - rank
+ - max_rank
+
+ The key to the dictionary is the game type code. There is also an
+ "overall" game_type_cd which is the overall best rank.
+ """
+ raw_ranks = DBSession.query("game_type_cd", "rank", "max_rank").\
+ from_statement(
+ "select pr.game_type_cd, pr.rank, overall.max_rank "
+ "from player_ranks pr, "
+ "(select game_type_cd, max(rank) max_rank "
+ "from player_ranks "
+ "group by game_type_cd) overall "
+ "where pr.game_type_cd = overall.game_type_cd "
+ "and player_id = :player_id "
+ "order by rank").\
+ params(player_id=player_id).all()
+
+ ranks = {}
+ found_top_rank = False
+ for row in raw_ranks:
+ if not found_top_rank:
+ ranks['overall'] = row
+ found_top_rank = True
+
+ ranks[row.game_type_cd] = row
+
+ return ranks;
+
+
+def get_elos(player_id):
+ """
+ Provides a breakdown of the player's elos by game type.
+
+ Returns a dictionary of namedtuples with the following members:
+ - player_id
+ - game_type_cd
+ - games
+ - elo
+
+ The key to the dictionary is the game type code. There is also an
+ "overall" game_type_cd which is the overall best rank.
+ """
+ raw_elos = DBSession.query(PlayerElo).filter_by(player_id=player_id).\
+ order_by(PlayerElo.elo.desc()).all()
+
+ elos = {}
+ found_max_elo = False
+ for row in raw_elos:
+ if not found_max_elo:
+ elos['overall'] = row
+ found_max_elo = True
+
+ elos[row.game_type_cd] = row
+
+ return elos
+
+
+def get_recent_games(player_id):
+ """
+ Provides a list of recent games.
+
+ Returns the full PlayerGameStat, Game, Server, Map
+ objects for all recent games.
+ """
+ # recent games table, all data
+ recent_games = DBSession.query(PlayerGameStat, Game, Server, Map).\
+ filter(PlayerGameStat.player_id == player_id).\
+ filter(PlayerGameStat.game_id == Game.game_id).\
+ filter(Game.server_id == Server.server_id).\
+ filter(Game.map_id == Map.map_id).\
+ order_by(Game.game_id.desc())[0:10]
+
+ return recent_games
+
+
+def get_recent_weapons(player_id):
+ """
+ Returns the weapons that have been used in the past 90 days
+ and also used in 5 games or more.
+ """
+ cutoff = datetime.datetime.utcnow() - datetime.timedelta(days=90)
+ recent_weapons = []
+ for weapon in DBSession.query(PlayerWeaponStat.weapon_cd, func.count()).\
+ filter(PlayerWeaponStat.player_id == player_id).\
+ filter(PlayerWeaponStat.create_dt > cutoff).\
+ group_by(PlayerWeaponStat.weapon_cd).\
+ having(func.count() > 4).\
+ all():
+ recent_weapons.append(weapon[0])
+
+ return recent_weapons
+
+
def _get_games_played(player_id):
"""
Provides a breakdown by gametype of the games played by player_id.
return total_stats
-def _get_fav_map(player_id):
+def _get_fav_maps(player_id):
"""
Get the player's favorite map. The favorite map is defined
- as the map that he or she has played the most in the past
- 90 days.
-
- Returns a dictionary with keys for the map's name and id.
+ as the map that he or she has played the most with game
+ types considered separate. This is to say that if a person
+ plays dm and duel on stormkeep with 25 games in each mode,
+ final_rage could still be the favorite map overall if it has
+ 26 dm games.
+
+ Returns a dictionary with entries for each played game type.
+ Each game type ditionary value contained a nested dictionary
+ with the following keys:
+ id = the favorite map id
+ name = the favorite map's name
+ times_played = the number of times the map was played in that mode
+
+ Note also that there's a superficial "overall" game type that is
+ meant to hold the top map overall. It'll be a dupe of one of the
+ other game types' nested dictionary.
"""
- # 90 day window
- back_then = datetime.datetime.utcnow() - datetime.timedelta(days=90)
-
- raw_fav_map = DBSession.query(Map.name, Map.map_id).\
- filter(Game.game_id == PlayerGameStat.game_id).\
- filter(Game.map_id == Map.map_id).\
- filter(PlayerGameStat.player_id == player_id).\
- filter(PlayerGameStat.create_dt > back_then).\
- group_by(Map.name, Map.map_id).\
- order_by(func.count().desc()).\
- limit(1).one()
-
- fav_map = {}
- fav_map['name'] = raw_fav_map[0]
- fav_map['id'] = raw_fav_map[1]
-
- return fav_map
+ fav_maps = {}
+ for (game_type_cd, name, map_id, times_played) in DBSession.\
+ query("game_type_cd", "name", "map_id", "times_played").\
+ from_statement(
+ "SELECT game_type_cd, "
+ "name, "
+ "map_id, "
+ "times_played "
+ "FROM (SELECT g.game_type_cd, "
+ "m.name, "
+ "m.map_id, "
+ "count(*) times_played, "
+ "row_number() "
+ "over ( "
+ "PARTITION BY g.game_type_cd "
+ "ORDER BY Count(*) DESC, m.map_id ASC) rank "
+ "FROM games g, "
+ "player_game_stats pgs, "
+ "maps m "
+ "WHERE g.game_id = pgs.game_id "
+ "AND g.map_id = m.map_id "
+ "AND pgs.player_id = :player_id "
+ "GROUP BY g.game_type_cd, "
+ "m.map_id, "
+ "m.name) most_played "
+ "WHERE rank = 1"
+ ).params(player_id=player_id).all():
+ fav_map_detail = {}
+ fav_map_detail['name'] = name
+ fav_map_detail['map_id'] = map_id
+ fav_map_detail['times_played'] = times_played
+ fav_maps[game_type_cd] = fav_map_detail
+
+ max_played = 0
+ overall = {}
+ for fav_map_detail in fav_maps.values():
+ if fav_map_detail['times_played'] > max_played:
+ max_played = fav_map_detail['times_played']
+ overall = fav_map_detail
+
+ fav_maps['overall'] = overall
+
+ return fav_maps
def _get_rank(player_id):
player = DBSession.query(Player).filter_by(player_id=player_id).\
filter(Player.active_ind == True).one()
- # games played, alivetime, wins, kills, deaths
- total_stats = _get_total_stats(player.player_id)
-
- # games breakdown - N games played (X ctf, Y dm) etc
- (total_games, games_breakdown) = _get_games_played(player.player_id)
-
- # favorite map from the past 90 days
- try:
- fav_map = _get_fav_map(player.player_id)
- except:
- fav_map = None
-
- # friendly display of elo information and preliminary status
- elos = DBSession.query(PlayerElo).filter_by(player_id=player_id).\
- filter(PlayerElo.game_type_cd.in_(['ctf','duel','dm'])).\
- order_by(PlayerElo.elo.desc()).all()
-
- elos_display = []
- for elo in elos:
- if elo.games > 32:
- str = "{0} ({1})"
- else:
- str = "{0}* ({1})"
-
- elos_display.append(str.format(round(elo.elo, 3),
- elo.game_type_cd))
-
- # get current rank information
- ranks = _get_rank(player_id)
- ranks_display = ', '.join(["{1} of {2} ({0})".format(gtc, rank,
- max_rank) for gtc, rank, max_rank in ranks])
-
-
- # which weapons have been used in the past 90 days
- # and also, used in 5 games or more?
- back_then = datetime.datetime.utcnow() - datetime.timedelta(days=90)
- recent_weapons = []
- for weapon in DBSession.query(PlayerWeaponStat.weapon_cd, func.count()).\
- filter(PlayerWeaponStat.player_id == player_id).\
- filter(PlayerWeaponStat.create_dt > back_then).\
- group_by(PlayerWeaponStat.weapon_cd).\
- having(func.count() > 4).\
- all():
- recent_weapons.append(weapon[0])
-
- # recent games table, all data
- recent_games = DBSession.query(PlayerGameStat, Game, Server, Map).\
- filter(PlayerGameStat.player_id == player_id).\
- filter(PlayerGameStat.game_id == Game.game_id).\
- filter(Game.server_id == Server.server_id).\
- filter(Game.map_id == Map.map_id).\
- order_by(Game.game_id.desc())[0:10]
+ games_played = get_games_played(player_id)
+ overall_stats = get_overall_stats(player_id)
+ fav_maps = get_fav_maps(player_id)
+ elos = get_elos(player_id)
+ ranks = get_ranks(player_id)
+ recent_games = get_recent_games(player_id)
+ recent_weapons = get_recent_weapons(player_id)
except Exception as e:
- player = None
- elos_display = None
- total_stats = None
- recent_games = None
- total_games = None
- games_breakdown = None
+ player = None
+ games_played = None
+ overall_stats = None
+ fav_maps = None
+ elos = None
+ ranks = None
+ recent_games = None
recent_weapons = []
- fav_map = None
- ranks_display = None;
return {'player':player,
- 'elos_display':elos_display,
+ 'games_played':games_played,
+ 'overall_stats':overall_stats,
+ 'fav_maps':fav_maps,
+ 'elos':elos,
+ 'ranks':ranks,
'recent_games':recent_games,
- 'total_stats':total_stats,
- 'total_games':total_games,
- 'games_breakdown':games_breakdown,
- 'recent_weapons':recent_weapons,
- 'fav_map':fav_map,
- 'ranks_display':ranks_display,
+ 'recent_weapons':recent_weapons
}
"""
Provides detailed information on a specific player
"""
- return player_info_data(request)
+ player_info = player_info_data(request)
+
+ player = player_info['player']
+ games_played = player_info['games_played']
+ overall_stats = player_info['overall_stats']
+ fav_maps = player_info['fav_maps']
+ elos = player_info['elos']
+ ranks = player_info['ranks']
+ recent_games = player_info['recent_games']
+ recent_weapons = player_info['recent_weapons']
+
+ # holds all of the tab content data
+ stat_strings = {}
+ for g in games_played:
+ stat_strings[g.game_type_cd] = []
+
+ # last seen, playing time
+ for k,v in overall_stats.iteritems():
+ stat_strings[k].append({'Last Played':v.last_played})
+ stat_strings[k].\
+ append({'Playing Time':v.total_playing_time})
+
+ # games played, win ratio
+ for g in games_played:
+ stat_strings[g.game_type_cd].append({'Games Played':g.games})
+ stat_strings[g.game_type_cd].\
+ append({'Win Pct':'{0} ({1} wins, {2} losses'.\
+ format(g.win_pct, g.wins, g.losses)})
+
+ # kill ratio
+ for k,v in overall_stats.iteritems():
+ stat_strings[k].\
+ append({'Kill Ratio':'{0} ({1} kills, {2} deaths)'.\
+ format(v.k_d_ratio, v.total_kills, v.total_deaths)})
+
+ # favorite maps
+ for k,v in fav_maps.iteritems():
+ stat_strings[k].append({'Favorite Map':v.map_name})
+
+ # elos
+ for k,v in elos.iteritems():
+ try:
+ stat_strings[k].append({'Elo':v.elo})
+ except:
+ pass
+
+ # ranks
+ for k,v in ranks.iteritems():
+ try:
+ stat_strings[k].append({'Rank':'{0} of {1}'.\
+ format(v.rank, v.max_rank)})
+ except:
+ pass
+
+ print stat_strings
+
+ return player_info
def player_info_json(request):
projects / xonotic / xonstat.git / commitdiff