xonstat/views/player.py

   1 import datetime
   2 import logging
   3 import pyramid.httpexceptions
   4 import sqlalchemy as sa
   5 import sqlalchemy.sql.functions as func
   6 from calendar import timegm
   7 from collections import namedtuple
   8 from webhelpers.paginate import Page
   9 from xonstat.models import *
  10 from xonstat.util import page_url, to_json, pretty_date, datetime_seconds
  11 from xonstat.util import is_cake_day, verify_request
  12 from xonstat.views.helpers import RecentGame, recent_games_q
  13 from urllib import unquote
  14
  15 log = logging.getLogger(__name__)
  16
  17
  18 def player_index_data(request):
  19     if request.params.has_key('page'):
  20         current_page = request.params['page']
  21     else:
  22         current_page = 1
  23
  24     try:
  25         player_q = DBSession.query(Player).\
  26                 filter(Player.player_id > 2).\
  27                 filter(Player.active_ind == True).\
  28                 filter(sa.not_(Player.nick.like('Anonymous Player%'))).\
  29                 order_by(Player.player_id.desc())
  30
  31         players = Page(player_q, current_page, items_per_page=25, url=page_url)
  32
  33     except Exception as e:
  34         players = None
  35         raise e
  36
  37     return {'players':players
  38            }
  39
  40
  41 def player_index(request):
  42     """
  43     Provides a list of all the current players.
  44     """
  45     return player_index_data(request)
  46
  47
  48 def player_index_json(request):
  49     """
  50     Provides a list of all the current players. JSON.
  51     """
  52     return [{'status':'not implemented'}]
  53
  54
  55 def get_games_played(player_id):
  56     """
  57     Provides a breakdown by gametype of the games played by player_id.
  58
  59     Returns a list of namedtuples with the following members:
  60         - game_type_cd
  61         - games
  62         - wins
  63         - losses
  64         - win_pct
  65
  66     The list itself is ordered by the number of games played
  67     """
  68     GamesPlayed = namedtuple('GamesPlayed', ['game_type_cd', 'games', 'wins',
  69         'losses', 'win_pct'])
  70
  71     raw_games_played = DBSession.query('game_type_cd', 'wins', 'losses').\
  72             from_statement(
  73                 "SELECT game_type_cd, "
  74                        "SUM(win) wins, "
  75                        "SUM(loss) losses "
  76                 "FROM   (SELECT g.game_id, "
  77                                "g.game_type_cd, "
  78                                "CASE "
  79                                  "WHEN g.winner = pgs.team THEN 1 "
  80                                  "WHEN pgs.scoreboardpos = 1 THEN 1 "
  81                                  "ELSE 0 "
  82                                "END win, "
  83                                "CASE "
  84                                  "WHEN g.winner = pgs.team THEN 0 "
  85                                  "WHEN pgs.scoreboardpos = 1 THEN 0 "
  86                                  "ELSE 1 "
  87                                "END loss "
  88                         "FROM   games g, "
  89                                "player_game_stats pgs "
  90                         "WHERE  g.game_id = pgs.game_id "
  91                         "AND pgs.player_id = :player_id) win_loss "
  92                 "GROUP  BY game_type_cd "
  93             ).params(player_id=player_id).all()
  94
  95     games_played = []
  96     overall_games = 0
  97     overall_wins = 0
  98     overall_losses = 0
  99     for row in raw_games_played:
 100         games = row.wins + row.losses
 101         overall_games += games
 102         overall_wins += row.wins
 103         overall_losses += row.losses
 104         win_pct = float(row.wins)/games * 100
 105
 106         games_played.append(GamesPlayed(row.game_type_cd, games, row.wins,
 107             row.losses, win_pct))
 108
 109     try:
 110         overall_win_pct = float(overall_wins)/overall_games * 100
 111     except:
 112         overall_win_pct = 0.0
 113
 114     games_played.append(GamesPlayed('overall', overall_games, overall_wins,
 115         overall_losses, overall_win_pct))
 116
 117     # sort the resulting list by # of games played
 118     games_played = sorted(games_played, key=lambda x:x.games)
 119     games_played.reverse()
 120     return games_played
 121
 122
 123 def get_overall_stats(player_id):
 124     """
 125     Provides a breakdown of stats by gametype played by player_id.
 126
 127     Returns a dictionary of namedtuples with the following members:
 128         - total_kills
 129         - total_deaths
 130         - k_d_ratio
 131         - last_played (last time the player played the game type)
 132         - last_played_epoch (same as above, but in seconds since epoch)
 133         - last_played_fuzzy (same as above, but in relative date)
 134         - total_playing_time (total amount of time played the game type)
 135         - total_playing_time_secs (same as the above, but in seconds)
 136         - total_pickups (ctf only)
 137         - total_captures (ctf only)
 138         - cap_ratio (ctf only)
 139         - total_carrier_frags (ctf only)
 140         - game_type_cd
 141         - game_type_descr
 142
 143     The key to the dictionary is the game type code. There is also an
 144     "overall" game_type_cd which sums the totals and computes the total ratios.
 145     """
 146     OverallStats = namedtuple('OverallStats', ['total_kills', 'total_deaths',
 147         'k_d_ratio', 'last_played', 'last_played_epoch', 'last_played_fuzzy',
 148         'total_playing_time', 'total_playing_time_secs', 'total_pickups', 'total_captures', 'cap_ratio',
 149         'total_carrier_frags', 'game_type_cd', 'game_type_descr'])
 150
 151     raw_stats = DBSession.query('game_type_cd', 'game_type_descr',
 152             'total_kills', 'total_deaths', 'last_played', 'total_playing_time',
 153             'total_pickups', 'total_captures', 'total_carrier_frags').\
 154             from_statement(
 155                 "SELECT g.game_type_cd, "
 156                        "gt.descr game_type_descr, "
 157                        "Sum(pgs.kills)         total_kills, "
 158                        "Sum(pgs.deaths)        total_deaths, "
 159                        "Max(pgs.create_dt)     last_played, "
 160                        "Sum(pgs.alivetime)     total_playing_time, "
 161                        "Sum(pgs.pickups)       total_pickups, "
 162                        "Sum(pgs.captures)      total_captures, "
 163                        "Sum(pgs.carrier_frags) total_carrier_frags "
 164                 "FROM   games g, "
 165                        "cd_game_type gt, "
 166                        "player_game_stats pgs "
 167                 "WHERE  g.game_id = pgs.game_id "
 168                   "AND  g.game_type_cd = gt.game_type_cd "
 169                   "AND  pgs.player_id = :player_id "
 170                 "GROUP  BY g.game_type_cd, game_type_descr "
 171                 "UNION "
 172                 "SELECT 'overall'              game_type_cd, "
 173                        "'Overall'              game_type_descr, "
 174                        "Sum(pgs.kills)         total_kills, "
 175                        "Sum(pgs.deaths)        total_deaths, "
 176                        "Max(pgs.create_dt)     last_played, "
 177                        "Sum(pgs.alivetime)     total_playing_time, "
 178                        "Sum(pgs.pickups)       total_pickups, "
 179                        "Sum(pgs.captures)      total_captures, "
 180                        "Sum(pgs.carrier_frags) total_carrier_frags "
 181                 "FROM   player_game_stats pgs "
 182                 "WHERE  pgs.player_id = :player_id "
 183             ).params(player_id=player_id).all()
 184
 185     # to be indexed by game_type_cd
 186     overall_stats = {}
 187
 188     for row in raw_stats:
 189         # individual gametype ratio calculations
 190         try:
 191             k_d_ratio = float(row.total_kills)/row.total_deaths
 192         except:
 193             k_d_ratio = None
 194
 195         try:
 196             cap_ratio = float(row.total_captures)/row.total_pickups
 197         except:
 198             cap_ratio = None
 199
 200         # everything else is untouched or "raw"
 201         os = OverallStats(total_kills=row.total_kills,
 202                 total_deaths=row.total_deaths,
 203                 k_d_ratio=k_d_ratio,
 204                 last_played=row.last_played,
 205                 last_played_epoch=timegm(row.last_played.timetuple()),
 206                 last_played_fuzzy=pretty_date(row.last_played),
 207                 total_playing_time=row.total_playing_time,
 208                 total_playing_time_secs=int(datetime_seconds(row.total_playing_time)),
 209                 total_pickups=row.total_pickups,
 210                 total_captures=row.total_captures,
 211                 cap_ratio=cap_ratio,
 212                 total_carrier_frags=row.total_carrier_frags,
 213                 game_type_cd=row.game_type_cd,
 214                 game_type_descr=row.game_type_descr)
 215
 216         overall_stats[row.game_type_cd] = os
 217
 218     # We have to edit "overall" stats to exclude deaths in CTS.
 219     # Although we still want to record deaths, they shouldn't
 220     # count towards the overall K:D ratio.
 221     if 'cts' in overall_stats:
 222         os = overall_stats['overall']
 223
 224         try:
 225             k_d_ratio = float(os.total_kills)/(os.total_deaths - overall_stats['cts'].total_deaths)
 226         except:
 227             k_d_ratio = None
 228
 229         non_cts_deaths = os.total_deaths - overall_stats['cts'].total_deaths
 230
 231
 232         overall_stats['overall'] = OverallStats(
 233                 total_kills             = os.total_kills,
 234                 total_deaths            = non_cts_deaths,
 235                 k_d_ratio               = k_d_ratio,
 236                 last_played             = os.last_played,
 237                 last_played_epoch       = os.last_played_epoch,
 238                 last_played_fuzzy       = os.last_played_fuzzy,
 239                 total_playing_time      = os.total_playing_time,
 240                 total_playing_time_secs = os.total_playing_time_secs,
 241                 total_pickups           = os.total_pickups,
 242                 total_captures          = os.total_captures,
 243                 cap_ratio               = os.cap_ratio,
 244                 total_carrier_frags     = os.total_carrier_frags,
 245                 game_type_cd            = os.game_type_cd,
 246                 game_type_descr         = os.game_type_descr)
 247
 248     return overall_stats
 249
 250
 251 def get_fav_maps(player_id, game_type_cd=None):
 252     """
 253     Provides a breakdown of favorite maps by gametype.
 254
 255     Returns a dictionary of namedtuples with the following members:
 256         - game_type_cd
 257         - map_name (map name)
 258         - map_id
 259         - times_played
 260
 261     The favorite map is defined as the map you've played the most
 262     for the given game_type_cd.
 263
 264     The key to the dictionary is the game type code. There is also an
 265     "overall" game_type_cd which is the overall favorite map. This is
 266     defined as the favorite map of the game type you've played the
 267     most. The input parameter game_type_cd is for this.
 268     """
 269     FavMap = namedtuple('FavMap', ['map_name', 'map_id', 'times_played', 'game_type_cd'])
 270
 271     raw_favs = DBSession.query('game_type_cd', 'map_name',
 272             'map_id', 'times_played').\
 273             from_statement(
 274                 "SELECT game_type_cd, "
 275                        "name map_name, "
 276                        "map_id, "
 277                        "times_played "
 278                 "FROM   (SELECT g.game_type_cd, "
 279                                "m.name, "
 280                                "m.map_id, "
 281                                "Count(*) times_played, "
 282                                "Row_number() "
 283                                  "OVER ( "
 284                                    "partition BY g.game_type_cd "
 285                                    "ORDER BY Count(*) DESC, m.map_id ASC) rank "
 286                         "FROM   games g, "
 287                                "player_game_stats pgs, "
 288                                "maps m "
 289                         "WHERE  g.game_id = pgs.game_id "
 290                                "AND g.map_id = m.map_id "
 291                                "AND pgs.player_id = :player_id "
 292                         "GROUP  BY g.game_type_cd, "
 293                                   "m.map_id, "
 294                                   "m.name) most_played "
 295                 "WHERE  rank = 1 "
 296                 "ORDER BY  times_played desc "
 297             ).params(player_id=player_id).all()
 298
 299     fav_maps = {}
 300     overall_fav = None
 301     for row in raw_favs:
 302         fv = FavMap(map_name=row.map_name,
 303             map_id=row.map_id,
 304             times_played=row.times_played,
 305             game_type_cd=row.game_type_cd)
 306
 307         # if we aren't given a favorite game_type_cd
 308         # then the overall favorite is the one we've
 309         # played the most
 310         if overall_fav is None:
 311             fav_maps['overall'] = fv
 312             overall_fav = fv.game_type_cd
 313
 314         # otherwise it is the favorite map from the
 315         # favorite game_type_cd (provided as a param)
 316         # and we'll overwrite the first dict entry
 317         if game_type_cd == fv.game_type_cd:
 318             fav_maps['overall'] = fv
 319
 320         fav_maps[row.game_type_cd] = fv
 321
 322     return fav_maps
 323
 324
 325 def get_ranks(player_id):
 326     """
 327     Provides a breakdown of the player's ranks by game type.
 328
 329     Returns a dictionary of namedtuples with the following members:
 330         - game_type_cd
 331         - rank
 332         - max_rank
 333
 334     The key to the dictionary is the game type code. There is also an
 335     "overall" game_type_cd which is the overall best rank.
 336     """
 337     Rank = namedtuple('Rank', ['rank', 'max_rank', 'percentile', 'game_type_cd'])
 338
 339     raw_ranks = DBSession.query("game_type_cd", "rank", "max_rank").\
 340             from_statement(
 341                 "select pr.game_type_cd, pr.rank, overall.max_rank "
 342                 "from player_ranks pr,  "
 343                    "(select game_type_cd, max(rank) max_rank "
 344                     "from player_ranks  "
 345                     "group by game_type_cd) overall "
 346                 "where pr.game_type_cd = overall.game_type_cd  "
 347                 "and player_id = :player_id "
 348                 "order by rank").\
 349             params(player_id=player_id).all()
 350
 351     ranks = {}
 352     found_top_rank = False
 353     for row in raw_ranks:
 354         rank = Rank(rank=row.rank,
 355             max_rank=row.max_rank,
 356             percentile=100 - 100*float(row.rank-1)/(row.max_rank-1),
 357             game_type_cd=row.game_type_cd)
 358
 359
 360         if not found_top_rank:
 361             ranks['overall'] = rank
 362             found_top_rank = True
 363         elif rank.percentile > ranks['overall'].percentile:
 364             ranks['overall'] = rank
 365
 366         ranks[row.game_type_cd] = rank
 367
 368     return ranks;
 369
 370
 371 def get_elos(player_id):
 372     """
 373     Provides a breakdown of the player's elos by game type.
 374
 375     Returns a dictionary of namedtuples with the following members:
 376         - player_id
 377         - game_type_cd
 378         - games
 379         - elo
 380
 381     The key to the dictionary is the game type code. There is also an
 382     "overall" game_type_cd which is the overall best rank.
 383     """
 384     raw_elos = DBSession.query(PlayerElo).filter_by(player_id=player_id).\
 385             order_by(PlayerElo.elo.desc()).all()
 386
 387     elos = {}
 388     found_max_elo = False
 389     for row in raw_elos:
 390         if not found_max_elo:
 391             elos['overall'] = row
 392             found_max_elo = True
 393
 394         elos[row.game_type_cd] = row
 395
 396     return elos
 397
 398
 399 def get_recent_games(player_id, limit=10):
 400     """
 401     Provides a list of recent games for a player. Uses the recent_games_q helper.
 402     """
 403     # recent games played in descending order
 404     rgs = recent_games_q(player_id=player_id, force_player_id=True).limit(limit).all()
 405     recent_games = [RecentGame(row) for row in rgs]
 406
 407     return recent_games
 408
 409
 410 def get_recent_weapons(player_id):
 411     """
 412     Returns the weapons that have been used in the past 90 days
 413     and also used in 5 games or more.
 414     """
 415     cutoff = datetime.datetime.utcnow() - datetime.timedelta(days=90)
 416     recent_weapons = []
 417     for weapon in DBSession.query(PlayerWeaponStat.weapon_cd, func.count()).\
 418             filter(PlayerWeaponStat.player_id == player_id).\
 419             filter(PlayerWeaponStat.create_dt > cutoff).\
 420             group_by(PlayerWeaponStat.weapon_cd).\
 421             having(func.count() > 4).\
 422             all():
 423                 recent_weapons.append(weapon[0])
 424
 425     return recent_weapons
 426
 427
 428 def get_accuracy_stats(player_id, weapon_cd, games):
 429     """
 430     Provides accuracy for weapon_cd by player_id for the past N games.
 431     """
 432     # Reaching back 90 days should give us an accurate enough average
 433     # We then multiply this out for the number of data points (games) to
 434     # create parameters for a flot graph
 435     try:
 436         raw_avg = DBSession.query(func.sum(PlayerWeaponStat.hit),
 437                 func.sum(PlayerWeaponStat.fired)).\
 438                 filter(PlayerWeaponStat.player_id == player_id).\
 439                 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
 440                 one()
 441
 442         avg = round(float(raw_avg[0])/raw_avg[1]*100, 2)
 443
 444         # Determine the raw accuracy (hit, fired) numbers for $games games
 445         # This is then enumerated to create parameters for a flot graph
 446         raw_accs = DBSession.query(PlayerWeaponStat.game_id,
 447             PlayerWeaponStat.hit, PlayerWeaponStat.fired).\
 448                 filter(PlayerWeaponStat.player_id == player_id).\
 449                 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
 450                 order_by(PlayerWeaponStat.game_id.desc()).\
 451                 limit(games).\
 452                 all()
 453
 454         # they come out in opposite order, so flip them in the right direction
 455         raw_accs.reverse()
 456
 457         accs = []
 458         for i in range(len(raw_accs)):
 459             accs.append((raw_accs[i][0], round(float(raw_accs[i][1])/raw_accs[i][2]*100, 2)))
 460     except:
 461         accs = []
 462         avg = 0.0
 463
 464     return (avg, accs)
 465
 466
 467 def get_damage_stats(player_id, weapon_cd, games):
 468     """
 469     Provides damage info for weapon_cd by player_id for the past N games.
 470     """
 471     try:
 472         raw_avg = DBSession.query(func.sum(PlayerWeaponStat.actual),
 473                 func.sum(PlayerWeaponStat.hit)).\
 474                 filter(PlayerWeaponStat.player_id == player_id).\
 475                 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
 476                 one()
 477
 478         avg = round(float(raw_avg[0])/raw_avg[1], 2)
 479
 480         # Determine the damage efficiency (hit, fired) numbers for $games games
 481         # This is then enumerated to create parameters for a flot graph
 482         raw_dmgs = DBSession.query(PlayerWeaponStat.game_id,
 483             PlayerWeaponStat.actual, PlayerWeaponStat.hit).\
 484                 filter(PlayerWeaponStat.player_id == player_id).\
 485                 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
 486                 order_by(PlayerWeaponStat.game_id.desc()).\
 487                 limit(games).\
 488                 all()
 489
 490         # they come out in opposite order, so flip them in the right direction
 491         raw_dmgs.reverse()
 492
 493         dmgs = []
 494         for i in range(len(raw_dmgs)):
 495             # try to derive, unless we've hit nothing then set to 0!
 496             try:
 497                 dmg = round(float(raw_dmgs[i][1])/raw_dmgs[i][2], 2)
 498             except:
 499                 dmg = 0.0
 500
 501             dmgs.append((raw_dmgs[i][0], dmg))
 502     except Exception as e:
 503         dmgs = []
 504         avg = 0.0
 505
 506     return (avg, dmgs)
 507
 508
 509 def player_info_data(request):
 510     player_id = int(request.matchdict['id'])
 511     if player_id <= 2:
 512         player_id = -1;
 513
 514     try:
 515         player = DBSession.query(Player).filter_by(player_id=player_id).\
 516                 filter(Player.active_ind == True).one()
 517
 518         games_played   = get_games_played(player_id)
 519         overall_stats  = get_overall_stats(player_id)
 520         fav_maps       = get_fav_maps(player_id)
 521         elos           = get_elos(player_id)
 522         ranks          = get_ranks(player_id)
 523         recent_games   = get_recent_games(player_id)
 524         recent_weapons = get_recent_weapons(player_id)
 525         cake_day       = is_cake_day(player.create_dt)
 526
 527     except Exception as e:
 528         player         = None
 529         games_played   = None
 530         overall_stats  = None
 531         fav_maps       = None
 532         elos           = None
 533         ranks          = None
 534         recent_games   = None
 535         recent_weapons = []
 536         cake_day       = False
 537         ## do not raise exceptions here (only for debugging)
 538         # raise e
 539
 540     return {'player':player,
 541             'games_played':games_played,
 542             'overall_stats':overall_stats,
 543             'fav_maps':fav_maps,
 544             'elos':elos,
 545             'ranks':ranks,
 546             'recent_games':recent_games,
 547             'recent_weapons':recent_weapons,
 548             'cake_day':cake_day,
 549             }
 550
 551
 552 def player_info(request):
 553     """
 554     Provides detailed information on a specific player
 555     """
 556     return player_info_data(request)
 557
 558
 559 def player_info_json(request):
 560     """
 561     Provides detailed information on a specific player. JSON.
 562     """
 563
 564     # All player_info fields are converted into JSON-formattable dictionaries
 565     player_info = player_info_data(request)
 566
 567     player = player_info['player'].to_dict()
 568
 569     games_played = {}
 570     for game in player_info['games_played']:
 571         games_played[game.game_type_cd] = to_json(game)
 572
 573     overall_stats = {}
 574     for gt,stats in player_info['overall_stats'].items():
 575         overall_stats[gt] = to_json(stats)
 576
 577     elos = {}
 578     for gt,elo in player_info['elos'].items():
 579         elos[gt] = to_json(elo.to_dict())
 580
 581     ranks = {}
 582     for gt,rank in player_info['ranks'].items():
 583         ranks[gt] = to_json(rank)
 584
 585     fav_maps = {}
 586     for gt,mapinfo in player_info['fav_maps'].items():
 587         fav_maps[gt] = to_json(mapinfo)
 588
 589     recent_games = []
 590     for game in player_info['recent_games']:
 591         recent_games.append(to_json(game))
 592
 593     #recent_weapons = player_info['recent_weapons']
 594
 595     return [{
 596         'player':           player,
 597         'games_played':     games_played,
 598         'overall_stats':    overall_stats,
 599         'fav_maps':         fav_maps,
 600         'elos':             elos,
 601         'ranks':            ranks,
 602         'recent_games':     recent_games,
 603     #    'recent_weapons':   recent_weapons,
 604         'recent_weapons':   ['not implemented'],
 605     }]
 606     #return [{'status':'not implemented'}]
 607
 608
 609 def player_game_index_data(request):
 610     player_id = request.matchdict['player_id']
 611
 612     game_type_cd = None
 613     game_type_descr = None
 614
 615     if request.params.has_key('type'):
 616         game_type_cd = request.params['type']
 617         try:
 618             game_type_descr = DBSession.query(GameType.descr).\
 619                 filter(GameType.game_type_cd == game_type_cd).\
 620                 one()[0]
 621         except Exception as e:
 622             pass
 623
 624     else:
 625         game_type_cd = None
 626         game_type_descr = None
 627
 628     if request.params.has_key('page'):
 629         current_page = request.params['page']
 630     else:
 631         current_page = 1
 632
 633     try:
 634         player = DBSession.query(Player).\
 635                 filter_by(player_id=player_id).\
 636                 filter(Player.active_ind == True).\
 637                 one()
 638
 639         rgs_q = recent_games_q(player_id=player.player_id,
 640             force_player_id=True, game_type_cd=game_type_cd)
 641
 642         games = Page(rgs_q, current_page, items_per_page=20, url=page_url)
 643
 644         # replace the items in the canned pagination class with more rich ones
 645         games.items = [RecentGame(row) for row in games.items]
 646
 647         games_played = get_games_played(player_id)
 648
 649     except Exception as e:
 650         player = None
 651         games = None
 652         game_type_cd = None
 653         game_type_descr = None
 654         games_played = None
 655
 656     return {
 657             'player_id':player.player_id,
 658             'player':player,
 659             'games':games,
 660             'game_type_cd':game_type_cd,
 661             'game_type_descr':game_type_descr,
 662             'games_played':games_played,
 663            }
 664
 665
 666 def player_game_index(request):
 667     """
 668     Provides an index of the games in which a particular
 669     player was involved. This is ordered by game_id, with
 670     the most recent game_ids first. Paginated.
 671     """
 672     return player_game_index_data(request)
 673
 674
 675 def player_game_index_json(request):
 676     """
 677     Provides an index of the games in which a particular
 678     player was involved. This is ordered by game_id, with
 679     the most recent game_ids first. Paginated. JSON.
 680     """
 681     return [{'status':'not implemented'}]
 682
 683
 684 def player_accuracy_data(request):
 685     player_id = request.matchdict['id']
 686     allowed_weapons = ['nex', 'rifle', 'shotgun', 'uzi', 'minstanex']
 687     weapon_cd = 'nex'
 688     games = 20
 689
 690     if request.params.has_key('weapon'):
 691         if request.params['weapon'] in allowed_weapons:
 692             weapon_cd = request.params['weapon']
 693
 694     if request.params.has_key('games'):
 695         try:
 696             games = request.params['games']
 697
 698             if games < 0:
 699                 games = 20
 700             if games > 50:
 701                 games = 50
 702         except:
 703             games = 20
 704
 705     (avg, accs) = get_accuracy_stats(player_id, weapon_cd, games)
 706
 707     # if we don't have enough data for the given weapon
 708     if len(accs) < games:
 709         games = len(accs)
 710
 711     return {
 712             'player_id':player_id,
 713             'player_url':request.route_url('player_info', id=player_id),
 714             'weapon':weapon_cd,
 715             'games':games,
 716             'avg':avg,
 717             'accs':accs
 718             }
 719
 720
 721 def player_accuracy(request):
 722     """
 723     Provides the accuracy for the given weapon. (JSON only)
 724     """
 725     return player_accuracy_data(request)
 726
 727
 728 def player_accuracy_json(request):
 729     """
 730     Provides a JSON response representing the accuracy for the given weapon.
 731
 732     Parameters:
 733        weapon = which weapon to display accuracy for. Valid values are 'nex',
 734                 'shotgun', 'uzi', and 'minstanex'.
 735        games = over how many games to display accuracy. Can be up to 50.
 736     """
 737     return player_accuracy_data(request)
 738
 739
 740 def player_damage_data(request):
 741     player_id = request.matchdict['id']
 742     allowed_weapons = ['grenadelauncher', 'electro', 'crylink', 'hagar',
 743             'rocketlauncher', 'laser']
 744     weapon_cd = 'rocketlauncher'
 745     games = 20
 746
 747     if request.params.has_key('weapon'):
 748         if request.params['weapon'] in allowed_weapons:
 749             weapon_cd = request.params['weapon']
 750
 751     if request.params.has_key('games'):
 752         try:
 753             games = request.params['games']
 754
 755             if games < 0:
 756                 games = 20
 757             if games > 50:
 758                 games = 50
 759         except:
 760             games = 20
 761
 762     (avg, dmgs) = get_damage_stats(player_id, weapon_cd, games)
 763
 764     # if we don't have enough data for the given weapon
 765     if len(dmgs) < games:
 766         games = len(dmgs)
 767
 768     return {
 769             'player_id':player_id,
 770             'player_url':request.route_url('player_info', id=player_id),
 771             'weapon':weapon_cd,
 772             'games':games,
 773             'avg':avg,
 774             'dmgs':dmgs
 775             }
 776
 777
 778 def player_damage_json(request):
 779     """
 780     Provides a JSON response representing the damage for the given weapon.
 781
 782     Parameters:
 783        weapon = which weapon to display damage for. Valid values are
 784          'grenadelauncher', 'electro', 'crylink', 'hagar', 'rocketlauncher',
 785          'laser'.
 786        games = over how many games to display damage. Can be up to 50.
 787     """
 788     return player_damage_data(request)
 789
 790
 791 def player_hashkey_info_data(request):
 792     # hashkey = request.matchdict['hashkey']
 793
 794     # the incoming hashkey is double quoted, and WSGI unquotes once...
 795     # hashkey = unquote(hashkey)
 796
 797     # if using request verification to obtain the hashkey
 798     (idfp, status) = verify_request(request)
 799     log.debug("d0_blind_id verification: idfp={0} status={1}\n".format(idfp, status))
 800
 801     log.debug("\n----- BEGIN REQUEST BODY -----\n" + request.body +
 802             "----- END REQUEST BODY -----\n\n")
 803
 804     # if config is to *not* verify requests and we get nothing back, this
 805     # query will return nothing and we'll 404.
 806     try:
 807         player = DBSession.query(Player).\
 808                 filter(Player.player_id == Hashkey.player_id).\
 809                 filter(Player.active_ind == True).\
 810                 filter(Hashkey.hashkey == idfp).one()
 811
 812         games_played      = get_games_played(player.player_id)
 813         overall_stats     = get_overall_stats(player.player_id)
 814         fav_maps          = get_fav_maps(player.player_id)
 815         elos              = get_elos(player.player_id)
 816         ranks             = get_ranks(player.player_id)
 817         most_recent_game  = get_recent_games(player.player_id, 1)[0]
 818
 819     except Exception as e:
 820         raise pyramid.httpexceptions.HTTPNotFound
 821
 822     return {'player':player,
 823             'hashkey':idfp,
 824             'games_played':games_played,
 825             'overall_stats':overall_stats,
 826             'fav_maps':fav_maps,
 827             'elos':elos,
 828             'ranks':ranks,
 829             'most_recent_game':most_recent_game,
 830             }
 831
 832
 833 def player_hashkey_info_json(request):
 834     """
 835     Provides detailed information on a specific player. JSON.
 836     """
 837
 838     # All player_info fields are converted into JSON-formattable dictionaries
 839     player_info = player_hashkey_info_data(request)
 840
 841     player = player_info['player'].to_dict()
 842
 843     games_played = {}
 844     for game in player_info['games_played']:
 845         games_played[game.game_type_cd] = to_json(game)
 846
 847     overall_stats = {}
 848     for gt,stats in player_info['overall_stats'].items():
 849         overall_stats[gt] = to_json(stats)
 850
 851     elos = {}
 852     for gt,elo in player_info['elos'].items():
 853         elos[gt] = to_json(elo.to_dict())
 854
 855     ranks = {}
 856     for gt,rank in player_info['ranks'].items():
 857         ranks[gt] = to_json(rank)
 858
 859     fav_maps = {}
 860     for gt,mapinfo in player_info['fav_maps'].items():
 861         fav_maps[gt] = to_json(mapinfo)
 862
 863     most_recent_game = to_json(player_info['most_recent_game'])
 864
 865     return [{
 866         'version':          1,
 867         'player':           player,
 868         'games_played':     games_played,
 869         'overall_stats':    overall_stats,
 870         'fav_maps':         fav_maps,
 871         'elos':             elos,
 872         'ranks':            ranks,
 873         'most_recent_game': most_recent_game,
 874     }]
 875
 876
 877 def player_hashkey_info_text(request):
 878     """
 879     Provides detailed information on a specific player. Plain text.
 880     """
 881     # UTC epoch
 882     now = timegm(datetime.datetime.utcnow().timetuple())
 883
 884     # All player_info fields are converted into JSON-formattable dictionaries
 885     player_info = player_hashkey_info_data(request)
 886
 887     # gather all of the data up into aggregate structures
 888     player = player_info['player']
 889     games_played = player_info['games_played']
 890     overall_stats = player_info['overall_stats']
 891     elos = player_info['elos']
 892     ranks = player_info['ranks']
 893     fav_maps = player_info['fav_maps']
 894     most_recent_game = player_info['most_recent_game']
 895
 896     # one-offs for things needing conversion for text/plain
 897     player_joined = timegm(player.create_dt.timetuple())
 898     player_joined_dt = player.create_dt
 899     alivetime = int(datetime_seconds(overall_stats['overall'].total_playing_time))
 900
 901     # this is a plain text response, if we don't do this here then
 902     # Pyramid will assume html
 903     request.response.content_type = 'text/plain'
 904
 905     return {
 906         'version':          1,
 907         'now':              now,
 908         'player':           player,
 909         'hashkey':          player_info['hashkey'],
 910         'player_joined':    player_joined,
 911         'player_joined_dt': player_joined_dt,
 912         'games_played':     games_played,
 913         'overall_stats':    overall_stats,
 914         'alivetime':        alivetime,
 915         'fav_maps':         fav_maps,
 916         'elos':             elos,
 917         'ranks':            ranks,
 918         'most_recent_game': most_recent_game,
 919     }
 920
 921
 922 def player_elo_info_data(request):
 923     """
 924     Provides elo information on a specific player. Raw data is returned.
 925     """
 926     (idfp, status) = verify_request(request)
 927     log.debug("d0_blind_id verification: idfp={0} status={1}\n".format(idfp, status))
 928
 929     hashkey = request.matchdict['hashkey']
 930 <<<<<<< HEAD
 931     log.debug("\n----- BEGIN REQUEST BODY -----\n" + request.body +
 932             "----- END REQUEST BODY -----\n\n")
 933 =======
 934
 935     # the incoming hashkey is double quoted, and WSGI unquotes once...
 936     hashkey = unquote(hashkey)
 937 >>>>>>> master
 938
 939     try:
 940         player = DBSession.query(Player).\
 941                 filter(Player.player_id == Hashkey.player_id).\
 942                 filter(Player.active_ind == True).\
 943                 filter(Hashkey.hashkey == hashkey).one()
 944
 945         elos = get_elos(player.player_id)
 946
 947     except Exception as e:
 948         log.debug(e)
 949         raise pyramid.httpexceptions.HTTPNotFound
 950
 951     return {
 952         'hashkey':hashkey,
 953         'player':player,
 954         'elos':elos,
 955     }
 956
 957
 958 def player_elo_info_json(request):
 959     """
 960     Provides elo information on a specific player. JSON.
 961     """
 962     elo_info = player_elo_info_data(request)
 963
 964     player = player_info['player'].to_dict()
 965
 966     elos = {}
 967     for gt, elo in elo_info['elos'].items():
 968         elos[gt] = to_json(elo.to_dict())
 969
 970     return [{
 971         'version':          1,
 972         'player':           player,
 973         'elos':             elos,
 974     }]
 975
 976
 977 def player_elo_info_text(request):
 978     """
 979     Provides elo information on a specific player. Plain text.
 980     """
 981     # UTC epoch
 982     now = timegm(datetime.datetime.utcnow().timetuple())
 983
 984     # All player_info fields are converted into JSON-formattable dictionaries
 985     elo_info = player_elo_info_data(request)
 986
 987     # this is a plain text response, if we don't do this here then
 988     # Pyramid will assume html
 989     request.response.content_type = 'text/plain'
 990
 991     return {
 992         'version':          1,
 993         'now':              now,
 994         'hashkey':          elo_info['hashkey'],
 995         'player':           elo_info['player'],
 996         'elos':             elo_info['elos'],
 997     }
 998
 999
1000 def player_captimes_data(request):
1001     player_id = int(request.matchdict['id'])
1002     if player_id <= 2:
1003         player_id = -1;
1004
1005     PlayerCaptimes = namedtuple('PlayerCaptimes', ['fastest_cap', 'create_dt', 'create_dt_epoch', 'create_dt_fuzzy',
1006         'player_id', 'game_id', 'map_id', 'map_name', 'server_id', 'server_name'])
1007
1008     dbquery = DBSession.query('fastest_cap', 'create_dt', 'player_id', 'game_id', 'map_id',
1009                 'map_name', 'server_id', 'server_name').\
1010             from_statement(
1011                 "SELECT ct.fastest_cap, "
1012                        "ct.create_dt, "
1013                        "ct.player_id, "
1014                        "ct.game_id, "
1015                        "ct.map_id, "
1016                        "m.name map_name, "
1017                        "g.server_id, "
1018                        "s.name server_name "
1019                 "FROM   player_map_captimes ct, "
1020                        "games g, "
1021                        "maps m, "
1022                        "servers s "
1023                 "WHERE  ct.player_id = :player_id "
1024                   "AND  g.game_id = ct.game_id "
1025                   "AND  g.server_id = s.server_id "
1026                   "AND  m.map_id = ct.map_id "
1027                 #"ORDER  BY ct.fastest_cap "
1028                 "ORDER  BY ct.create_dt desc"
1029             ).params(player_id=player_id).all()
1030
1031     player = DBSession.query(Player).filter_by(player_id=player_id).one()
1032
1033     player_captimes = []
1034     for row in dbquery:
1035         player_captimes.append(PlayerCaptimes(
1036                 fastest_cap=row.fastest_cap,
1037                 create_dt=row.create_dt,
1038                 create_dt_epoch=timegm(row.create_dt.timetuple()),
1039                 create_dt_fuzzy=pretty_date(row.create_dt),
1040                 player_id=row.player_id,
1041                 game_id=row.game_id,
1042                 map_id=row.map_id,
1043                 map_name=row.map_name,
1044                 server_id=row.server_id,
1045                 server_name=row.server_name,
1046             ))
1047
1048     return {
1049             'captimes':player_captimes,
1050             'player_id':player_id,
1051             'player_url':request.route_url('player_info', id=player_id),
1052             'player':player,
1053         }
1054
1055
1056 def player_captimes(request):
1057     return player_captimes_data(request)
1058
1059
1060 def player_captimes_json(request):
1061     return player_captimes_data(request)
1062
1063
1064 def player_weaponstats_data_json(request):
1065     player_id = request.matchdict["id"]
1066     if player_id <= 2:
1067         player_id = -1;
1068
1069     game_type_cd = request.params.get("game_type", None)
1070     if game_type_cd == "overall":
1071         game_type_cd = None
1072
1073     limit = 20
1074     if request.params.has_key("limit"):
1075         limit = int(request.params["limit"])
1076
1077         if limit < 0:
1078             limit = 20
1079         if limit > 50:
1080             limit = 50
1081
1082     games_raw = DBSession.query(sa.distinct(Game.game_id)).\
1083         filter(Game.game_id == PlayerWeaponStat.game_id).\
1084         filter(PlayerWeaponStat.player_id == player_id)
1085
1086     if game_type_cd is not None:
1087         games_raw = games_raw.filter(Game.game_type_cd == game_type_cd)
1088
1089     games_raw = games_raw.order_by(Game.game_id.desc()).limit(limit).all()
1090
1091     weapon_stats_raw = DBSession.query(PlayerWeaponStat).\
1092         filter(PlayerWeaponStat.player_id == player_id).\
1093         filter(PlayerWeaponStat.game_id.in_(games_raw)).all()
1094
1095     # NVD3 expects data points for all weapons used across the
1096     # set of games *for each* point on the x axis. This means populating
1097     # zero-valued weapon stat entries for games where a weapon was not
1098     # used in that game, but was used in another game for the set
1099     games_to_weapons = {}
1100     weapons_used = {}
1101     sum_avgs = {}
1102     for ws in weapon_stats_raw:
1103         if ws.game_id not in games_to_weapons:
1104             games_to_weapons[ws.game_id] = [ws.weapon_cd]
1105         else:
1106             games_to_weapons[ws.game_id].append(ws.weapon_cd)
1107
1108         weapons_used[ws.weapon_cd] = weapons_used.get(ws.weapon_cd, 0) + 1
1109         sum_avgs[ws.weapon_cd] = sum_avgs.get(ws.weapon_cd, 0) + float(ws.hit)/float(ws.fired)
1110
1111     for game_id in games_to_weapons.keys():
1112         for weapon_cd in set(weapons_used.keys()) - set(games_to_weapons[game_id]):
1113             weapon_stats_raw.append(PlayerWeaponStat(player_id=player_id,
1114                 game_id=game_id, weapon_cd=weapon_cd))
1115
1116     # averages for the weapons used in the range
1117     avgs = {}
1118     for w in weapons_used.keys():
1119         avgs[w] = round(sum_avgs[w]/float(weapons_used[w])*100, 2)
1120
1121     weapon_stats_raw = sorted(weapon_stats_raw, key = lambda x: x.game_id)
1122     games            = sorted(games_to_weapons.keys())
1123     weapon_stats     = [ws.to_dict() for ws in weapon_stats_raw]
1124
1125     return {
1126         "weapon_stats": weapon_stats,
1127         "weapons_used": weapons_used.keys(),
1128         "games": games,
1129         "averages": avgs,
1130     }
1131