5 import sqlalchemy as sa
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6 import sqlalchemy.sql.functions as func
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8 from pyramid.response import Response
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9 from pyramid.url import current_route_url
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10 from sqlalchemy import desc
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11 from webhelpers.paginate import Page, PageURL
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12 from xonstat.models import *
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13 from xonstat.util import page_url
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15 log = logging.getLogger(__name__)
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18 def player_index(request):
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20 Provides a list of all the current players.
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22 if 'page' in request.matchdict:
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23 current_page = int(request.matchdict['page'])
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28 player_q = DBSession.query(Player).\
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29 filter(Player.player_id > 2).\
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30 filter(Player.active_ind == True).\
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31 filter(sa.not_(Player.nick.like('Anonymous Player%'))).\
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32 order_by(Player.player_id.desc())
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34 players = Page(player_q, current_page, items_per_page=10, url=page_url)
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36 last_linked_page = current_page + 4
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37 if last_linked_page > players.last_page:
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38 last_linked_page = players.last_page
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40 pages_to_link = range(current_page+1, last_linked_page+1)
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42 except Exception as e:
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46 return {'players':players,
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47 'pages_to_link':pages_to_link,
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51 def get_games_played(player_id):
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53 Provides a breakdown by gametype of the games played by player_id.
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55 Returns a tuple containing (total_games, games_breakdown), where
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56 total_games is the absolute number of games played by player_id
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57 and games_breakdown is an array containing (game_type_cd, # games)
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59 games_played = DBSession.query(Game.game_type_cd, func.count()).\
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60 filter(Game.game_id == PlayerGameStat.game_id).\
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61 filter(PlayerGameStat.player_id == player_id).\
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62 group_by(Game.game_type_cd).\
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63 order_by(func.count().desc()).all()
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66 for (game_type_cd, games) in games_played:
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69 return (total, games_played)
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72 # TODO: should probably factor the above function into this one such that
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73 # total_stats['ctf_games'] is the count of CTF games and so on...
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74 def get_total_stats(player_id):
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76 Provides aggregated stats by player_id.
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78 Returns a dict with the keys 'kills', 'deaths', 'alivetime'.
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80 kills = how many kills a player has over all games
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81 deaths = how many deaths a player has over all games
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82 alivetime = how long a player has played over all games
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84 If any of the above are None, they are set to 0.
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87 (total_stats['kills'], total_stats['deaths'], total_stats['alivetime']) = DBSession.\
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88 query("total_kills", "total_deaths", "total_alivetime").\
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90 "select sum(kills) total_kills, "
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91 "sum(deaths) total_deaths, "
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92 "sum(alivetime) total_alivetime "
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93 "from player_game_stats "
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94 "where player_id=:player_id"
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95 ).params(player_id=player_id).one()
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97 (total_stats['wins'],) = DBSession.\
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98 query("total_wins").\
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100 "select count(*) total_wins "
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101 "from games g, player_game_stats pgs "
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102 "where g.game_id = pgs.game_id "
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103 "and player_id=:player_id "
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104 "and (g.winner = pgs.team or pgs.rank = 1)"
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105 ).params(player_id=player_id).one()
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107 for (key,value) in total_stats.items():
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109 total_stats[key] = 0
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114 def get_accuracy_stats(player_id, weapon_cd, games):
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116 Provides accuracy for weapon_cd by player_id for the past N games.
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118 # Reaching back 90 days should give us an accurate enough average
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119 # We then multiply this out for the number of data points (games) to
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120 # create parameters for a flot graph
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122 raw_avg = DBSession.query(func.sum(PlayerWeaponStat.hit),
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123 func.sum(PlayerWeaponStat.fired)).\
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124 filter(PlayerWeaponStat.player_id == player_id).\
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125 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
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128 avg = round(float(raw_avg[0])/raw_avg[1]*100, 2)
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130 # Determine the raw accuracy (hit, fired) numbers for $games games
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131 # This is then enumerated to create parameters for a flot graph
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132 raw_accs = DBSession.query(PlayerWeaponStat.game_id,
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133 PlayerWeaponStat.hit, PlayerWeaponStat.fired).\
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134 filter(PlayerWeaponStat.player_id == player_id).\
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135 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
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136 order_by(PlayerWeaponStat.game_id.desc()).\
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140 # they come out in opposite order, so flip them in the right direction
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144 for i in range(len(raw_accs)):
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145 accs.append((raw_accs[i][0], round(float(raw_accs[i][1])/raw_accs[i][2]*100, 2)))
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153 def player_info(request):
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155 Provides detailed information on a specific player
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157 player_id = int(request.matchdict['id'])
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162 player = DBSession.query(Player).filter_by(player_id=player_id).\
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163 filter(Player.active_ind == True).one()
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165 # games played, alivetime, wins, kills, deaths
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166 total_stats = get_total_stats(player.player_id)
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168 # games breakdown - N games played (X ctf, Y dm) etc
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169 (total_games, games_breakdown) = get_games_played(player.player_id)
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172 # friendly display of elo information and preliminary status
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173 elos = DBSession.query(PlayerElo).filter_by(player_id=player_id).\
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174 filter(PlayerElo.game_type_cd.in_(['ctf','duel','dm'])).\
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175 order_by(PlayerElo.elo.desc()).all()
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184 elos_display.append(str.format(round(elo.elo, 3),
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187 # data for the accuracy graph, which is converted into a JSON array for
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189 (avg, accs) = get_accuracy_stats(player_id, 'nex', 20)
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191 avg = json.dumps(avg)
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192 accs = json.dumps(accs)
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195 # recent games table, all data
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196 recent_games = DBSession.query(PlayerGameStat, Game, Server, Map).\
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197 filter(PlayerGameStat.player_id == player_id).\
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198 filter(PlayerGameStat.game_id == Game.game_id).\
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199 filter(Game.server_id == Server.server_id).\
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200 filter(Game.map_id == Map.map_id).\
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201 order_by(Game.game_id.desc())[0:10]
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203 except Exception as e:
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205 elos_display = None
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207 recent_games = None
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209 games_breakdown = None
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213 return {'player':player,
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214 'elos_display':elos_display,
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215 'recent_games':recent_games,
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216 'total_stats':total_stats,
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217 'total_games':total_games,
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218 'games_breakdown':games_breakdown,
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224 def player_game_index(request):
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226 Provides an index of the games in which a particular
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227 player was involved. This is ordered by game_id, with
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228 the most recent game_ids first. Paginated.
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230 player_id = request.matchdict['player_id']
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232 if 'page' in request.matchdict:
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233 current_page = request.matchdict['page']
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238 games_q = DBSession.query(Game, Server, Map).\
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239 filter(PlayerGameStat.game_id == Game.game_id).\
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240 filter(PlayerGameStat.player_id == player_id).\
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241 filter(Game.server_id == Server.server_id).\
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242 filter(Game.map_id == Map.map_id).\
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243 order_by(Game.game_id.desc())
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245 games = Page(games_q, current_page, url=page_url)
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248 for (game, server, map) in games:
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249 pgstats[game.game_id] = DBSession.query(PlayerGameStat).\
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250 filter(PlayerGameStat.game_id == game.game_id).\
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251 order_by(PlayerGameStat.rank).\
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252 order_by(PlayerGameStat.score).all()
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254 except Exception as e:
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258 return {'player_id':player_id,
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262 def player_accuracy(request):
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264 Provides a JSON response representing the accuracy for the given weapon.
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267 weapon = which weapon to display accuracy for. Valid values are 'nex',
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268 'shotgun', 'uzi', and 'minstanex'.
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269 games = over how many games to display accuracy. Can be up to 50.
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271 player_id = request.matchdict['id']
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272 allowed_weapons = ['nex', 'shotgun', 'uzi', 'minstanex']
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276 if request.params.has_key('weapon'):
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277 if request.params['weapon'] in allowed_weapons:
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278 weapon_cd = request.params['weapon']
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280 if request.params.has_key('games'):
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282 games = request.params['games']
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291 (avg, accs) = get_accuracy_stats(player_id, weapon_cd, games)
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294 'player_id':player_id,
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295 'player_url':request.route_url('player_info', id=player_id),
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296 'weapon':weapon_cd,
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