xonstat/views/player.py

   1 import datetime
   2 import json
   3 import logging
   4 import re
   5 import sqlalchemy as sa
   6 import sqlalchemy.sql.functions as func
   7 import time
   8 from collections import namedtuple
   9 from pyramid.response import Response
  10 from pyramid.url import current_route_url
  11 from sqlalchemy import desc, distinct
  12 from webhelpers.paginate import Page, PageURL
  13 from xonstat.models import *
  14 from xonstat.util import page_url
  15
  16 log = logging.getLogger(__name__)
  17
  18
  19 def player_index_data(request):
  20     if request.params.has_key('page'):
  21         current_page = request.params['page']
  22     else:
  23         current_page = 1
  24
  25     try:
  26         player_q = DBSession.query(Player).\
  27                 filter(Player.player_id > 2).\
  28                 filter(Player.active_ind == True).\
  29                 filter(sa.not_(Player.nick.like('Anonymous Player%'))).\
  30                 order_by(Player.player_id.desc())
  31
  32         players = Page(player_q, current_page, items_per_page=10, url=page_url)
  33
  34     except Exception as e:
  35         players = None
  36         raise e
  37
  38     return {'players':players
  39            }
  40
  41
  42 def player_index(request):
  43     """
  44     Provides a list of all the current players.
  45     """
  46     return player_index_data(request)
  47
  48
  49 def player_index_json(request):
  50     """
  51     Provides a list of all the current players. JSON.
  52     """
  53     return [{'status':'not implemented'}]
  54
  55
  56 def get_games_played(player_id):
  57     """
  58     Provides a breakdown by gametype of the games played by player_id.
  59
  60     Returns a list of namedtuples with the following members:
  61         - game_type_cd
  62         - games
  63         - wins
  64         - losses
  65         - win_pct
  66
  67     The list itself is ordered by the number of games played
  68     """
  69     GamesPlayed = namedtuple('GamesPlayed', ['game_type_cd', 'games', 'wins',
  70         'losses', 'win_pct'])
  71
  72     raw_games_played = DBSession.query('game_type_cd', 'wins', 'losses').\
  73             from_statement(
  74                 "SELECT game_type_cd, "
  75                        "SUM(win) wins, "
  76                        "SUM(loss) losses "
  77                 "FROM   (SELECT g.game_id, "
  78                                "g.game_type_cd, "
  79                                "CASE "
  80                                  "WHEN g.winner = pgs.team THEN 1 "
  81                                  "WHEN pgs.rank = 1 THEN 1 "
  82                                  "ELSE 0 "
  83                                "END win, "
  84                                "CASE "
  85                                  "WHEN g.winner = pgs.team THEN 0 "
  86                                  "WHEN pgs.rank = 1 THEN 0 "
  87                                  "ELSE 1 "
  88                                "END loss "
  89                         "FROM   games g, "
  90                                "player_game_stats pgs "
  91                         "WHERE  g.game_id = pgs.game_id "
  92                         "AND pgs.player_id = :player_id) win_loss "
  93                 "GROUP  BY game_type_cd "
  94             ).params(player_id=player_id).all()
  95
  96     games_played = []
  97     overall_games = 0
  98     overall_wins = 0
  99     overall_losses = 0
 100     for row in raw_games_played:
 101         games = row.wins + row.losses
 102         overall_games += games
 103         overall_wins += row.wins
 104         overall_losses += row.losses
 105         win_pct = float(row.wins)/games * 100
 106
 107         games_played.append(GamesPlayed(row.game_type_cd, games, row.wins,
 108             row.losses, win_pct))
 109
 110     try:
 111         overall_win_pct = float(overall_wins)/overall_games * 100
 112     except:
 113         overall_win_pct = 0.0
 114
 115     games_played.append(GamesPlayed('overall', overall_games, overall_wins,
 116         overall_losses, overall_win_pct))
 117
 118     # sort the resulting list by # of games played
 119     games_played = sorted(games_played, key=lambda x:x.games)
 120     games_played.reverse()
 121     return games_played
 122
 123
 124 def get_overall_stats(player_id):
 125     """
 126     Provides a breakdown of stats by gametype played by player_id.
 127
 128     Returns a dictionary of namedtuples with the following members:
 129         - total_kills
 130         - total_deaths
 131         - k_d_ratio
 132         - last_played (last time the player played the game type)
 133         - total_playing_time (total amount of time played the game type)
 134         - total_pickups (ctf only)
 135         - total_captures (ctf only)
 136         - cap_ratio (ctf only)
 137         - total_carrier_frags (ctf only)
 138         - game_type_cd
 139
 140     The key to the dictionary is the game type code. There is also an
 141     "overall" game_type_cd which sums the totals and computes the total ratios.
 142     """
 143     OverallStats = namedtuple('OverallStats', ['total_kills', 'total_deaths',
 144         'k_d_ratio', 'last_played', 'total_playing_time', 'total_pickups',
 145         'total_captures', 'cap_ratio', 'total_carrier_frags', 'game_type_cd'])
 146
 147     raw_stats = DBSession.query('game_type_cd', 'total_kills',
 148             'total_deaths', 'last_played', 'total_playing_time',
 149             'total_pickups', 'total_captures', 'total_carrier_frags').\
 150             from_statement(
 151                 "SELECT g.game_type_cd, "
 152                        "Sum(pgs.kills)         total_kills, "
 153                        "Sum(pgs.deaths)        total_deaths, "
 154                        "Max(pgs.create_dt)     last_played, "
 155                        "Sum(pgs.alivetime)     total_playing_time, "
 156                        "Sum(pgs.pickups)       total_pickups, "
 157                        "Sum(pgs.captures)      total_captures, "
 158                        "Sum(pgs.carrier_frags) total_carrier_frags "
 159                 "FROM   games g, "
 160                        "player_game_stats pgs "
 161                 "WHERE  g.game_id = pgs.game_id "
 162                   "AND  pgs.player_id = :player_id "
 163                 "GROUP  BY g.game_type_cd "
 164             ).params(player_id=player_id).all()
 165
 166     # to be indexed by game_type_cd
 167     overall_stats = {}
 168
 169     # sums for the "overall" game type (which is fake)
 170     overall_kills = 0
 171     overall_deaths = 0
 172     overall_last_played = None
 173     overall_playing_time = datetime.timedelta(seconds=0)
 174     overall_carrier_frags = 0
 175
 176     for row in raw_stats:
 177         # running totals or mins
 178         overall_kills += row.total_kills or 0
 179         overall_deaths += row.total_deaths or 0
 180
 181         if overall_last_played is None or row.last_played > overall_last_played:
 182             overall_last_played = row.last_played
 183
 184         overall_playing_time += row.total_playing_time
 185
 186         # individual gametype ratio calculations
 187         try:
 188             k_d_ratio = float(row.total_kills)/row.total_deaths
 189         except:
 190             k_d_ratio = None
 191
 192         try:
 193             cap_ratio = float(row.total_pickups)/row.total_captures
 194         except:
 195             cap_ratio = None
 196
 197         overall_carrier_frags += row.total_carrier_frags or 0
 198
 199         # everything else is untouched or "raw"
 200         os = OverallStats(total_kills=row.total_kills,
 201                 total_deaths=row.total_deaths,
 202                 k_d_ratio=k_d_ratio,
 203                 last_played=row.last_played,
 204                 total_playing_time=row.total_playing_time,
 205                 total_pickups=row.total_pickups,
 206                 total_captures=row.total_captures,
 207                 cap_ratio=cap_ratio,
 208                 total_carrier_frags=row.total_carrier_frags,
 209                 game_type_cd=row.game_type_cd)
 210
 211         overall_stats[row.game_type_cd] = os
 212
 213     # and lastly, the overall stuff
 214     try:
 215         overall_k_d_ratio = float(overall_kills)/overall_deaths
 216     except:
 217         overall_k_d_ratio = None
 218
 219     os = OverallStats(total_kills=overall_kills,
 220             total_deaths=overall_deaths,
 221             k_d_ratio=overall_k_d_ratio,
 222             last_played=overall_last_played,
 223             total_playing_time=overall_playing_time,
 224             total_pickups=None,
 225             total_captures=None,
 226             cap_ratio=None,
 227             total_carrier_frags=overall_carrier_frags,
 228             game_type_cd='overall')
 229
 230     overall_stats['overall'] = os
 231
 232     return overall_stats
 233
 234
 235 def get_fav_maps(player_id, game_type_cd=None):
 236     """
 237     Provides a breakdown of favorite maps by gametype.
 238
 239     Returns a dictionary of namedtuples with the following members:
 240         - game_type_cd
 241         - map_name (map name)
 242         - map_id
 243         - times_played
 244
 245     The favorite map is defined as the map you've played the most
 246     for the given game_type_cd.
 247
 248     The key to the dictionary is the game type code. There is also an
 249     "overall" game_type_cd which is the overall favorite map. This is
 250     defined as the favorite map of the game type you've played the
 251     most. The input parameter game_type_cd is for this.
 252     """
 253     raw_favs = DBSession.query('game_type_cd', 'map_name',
 254             'map_id', 'times_played').\
 255             from_statement(
 256                 "SELECT game_type_cd, "
 257                        "name map_name, "
 258                        "map_id, "
 259                        "times_played "
 260                 "FROM   (SELECT g.game_type_cd, "
 261                                "m.name, "
 262                                "m.map_id, "
 263                                "Count(*) times_played, "
 264                                "Row_number() "
 265                                  "OVER ( "
 266                                    "partition BY g.game_type_cd "
 267                                    "ORDER BY Count(*) DESC, m.map_id ASC) rank "
 268                         "FROM   games g, "
 269                                "player_game_stats pgs, "
 270                                "maps m "
 271                         "WHERE  g.game_id = pgs.game_id "
 272                                "AND g.map_id = m.map_id "
 273                                "AND pgs.player_id = :player_id "
 274                         "GROUP  BY g.game_type_cd, "
 275                                   "m.map_id, "
 276                                   "m.name) most_played "
 277                 "WHERE  rank = 1 "
 278                 "ORDER BY  times_played desc "
 279             ).params(player_id=player_id).all()
 280
 281     fav_maps = {}
 282     overall_fav = None
 283     for row in raw_favs:
 284         # if we aren't given a favorite game_type_cd
 285         # then the overall favorite is the one we've
 286         # played the most
 287         if overall_fav is None:
 288             fav_maps['overall'] = row
 289             overall_fav = row.game_type_cd
 290
 291         # otherwise it is the favorite map from the
 292         # favorite game_type_cd (provided as a param)
 293         # and we'll overwrite the first dict entry
 294         if game_type_cd == row.game_type_cd:
 295             fav_maps['overall'] = row
 296
 297         fav_maps[row.game_type_cd] = row
 298
 299     return fav_maps
 300
 301
 302 def get_ranks(player_id):
 303     """
 304     Provides a breakdown of the player's ranks by game type.
 305
 306     Returns a dictionary of namedtuples with the following members:
 307         - game_type_cd
 308         - rank
 309         - max_rank
 310
 311     The key to the dictionary is the game type code. There is also an
 312     "overall" game_type_cd which is the overall best rank.
 313     """
 314     raw_ranks = DBSession.query("game_type_cd", "rank", "max_rank").\
 315             from_statement(
 316                 "select pr.game_type_cd, pr.rank, overall.max_rank "
 317                 "from player_ranks pr,  "
 318                    "(select game_type_cd, max(rank) max_rank "
 319                     "from player_ranks  "
 320                     "group by game_type_cd) overall "
 321                 "where pr.game_type_cd = overall.game_type_cd  "
 322                 "and player_id = :player_id "
 323                 "order by rank").\
 324             params(player_id=player_id).all()
 325
 326     ranks = {}
 327     found_top_rank = False
 328     for row in raw_ranks:
 329         if not found_top_rank:
 330             ranks['overall'] = row
 331             found_top_rank = True
 332
 333         ranks[row.game_type_cd] = row
 334
 335     return ranks;
 336
 337
 338 def get_elos(player_id):
 339     """
 340     Provides a breakdown of the player's elos by game type.
 341
 342     Returns a dictionary of namedtuples with the following members:
 343         - player_id
 344         - game_type_cd
 345         - games
 346         - elo
 347
 348     The key to the dictionary is the game type code. There is also an
 349     "overall" game_type_cd which is the overall best rank.
 350     """
 351     raw_elos = DBSession.query(PlayerElo).filter_by(player_id=player_id).\
 352             order_by(PlayerElo.elo.desc()).all()
 353
 354     elos = {}
 355     found_max_elo = False
 356     for row in raw_elos:
 357         if not found_max_elo:
 358             elos['overall'] = row
 359             found_max_elo = True
 360
 361         elos[row.game_type_cd] = row
 362
 363     return elos
 364
 365
 366 def get_recent_games(player_id):
 367     """
 368     Provides a list of recent games.
 369
 370     Returns the full PlayerGameStat, Game, Server, Map
 371     objects for all recent games.
 372     """
 373     # recent games table, all data
 374     recent_games = DBSession.query(PlayerGameStat, Game, Server, Map).\
 375             filter(PlayerGameStat.player_id == player_id).\
 376             filter(PlayerGameStat.game_id == Game.game_id).\
 377             filter(Game.server_id == Server.server_id).\
 378             filter(Game.map_id == Map.map_id).\
 379             order_by(Game.game_id.desc())[0:10]
 380
 381     return recent_games
 382
 383
 384 def get_recent_weapons(player_id):
 385     """
 386     Returns the weapons that have been used in the past 90 days
 387     and also used in 5 games or more.
 388     """
 389     cutoff = datetime.datetime.utcnow() - datetime.timedelta(days=90)
 390     recent_weapons = []
 391     for weapon in DBSession.query(PlayerWeaponStat.weapon_cd, func.count()).\
 392             filter(PlayerWeaponStat.player_id == player_id).\
 393             filter(PlayerWeaponStat.create_dt > cutoff).\
 394             group_by(PlayerWeaponStat.weapon_cd).\
 395             having(func.count() > 4).\
 396             all():
 397                 recent_weapons.append(weapon[0])
 398
 399     return recent_weapons
 400
 401
 402 def get_accuracy_stats(player_id, weapon_cd, games):
 403     """
 404     Provides accuracy for weapon_cd by player_id for the past N games.
 405     """
 406     # Reaching back 90 days should give us an accurate enough average
 407     # We then multiply this out for the number of data points (games) to
 408     # create parameters for a flot graph
 409     try:
 410         raw_avg = DBSession.query(func.sum(PlayerWeaponStat.hit),
 411                 func.sum(PlayerWeaponStat.fired)).\
 412                 filter(PlayerWeaponStat.player_id == player_id).\
 413                 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
 414                 one()
 415
 416         avg = round(float(raw_avg[0])/raw_avg[1]*100, 2)
 417
 418         # Determine the raw accuracy (hit, fired) numbers for $games games
 419         # This is then enumerated to create parameters for a flot graph
 420         raw_accs = DBSession.query(PlayerWeaponStat.game_id,
 421             PlayerWeaponStat.hit, PlayerWeaponStat.fired).\
 422                 filter(PlayerWeaponStat.player_id == player_id).\
 423                 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
 424                 order_by(PlayerWeaponStat.game_id.desc()).\
 425                 limit(games).\
 426                 all()
 427
 428         # they come out in opposite order, so flip them in the right direction
 429         raw_accs.reverse()
 430
 431         accs = []
 432         for i in range(len(raw_accs)):
 433             accs.append((raw_accs[i][0], round(float(raw_accs[i][1])/raw_accs[i][2]*100, 2)))
 434     except:
 435         accs = []
 436         avg = 0.0
 437
 438     return (avg, accs)
 439
 440
 441 def get_damage_stats(player_id, weapon_cd, games):
 442     """
 443     Provides damage info for weapon_cd by player_id for the past N games.
 444     """
 445     try:
 446         raw_avg = DBSession.query(func.sum(PlayerWeaponStat.actual),
 447                 func.sum(PlayerWeaponStat.hit)).\
 448                 filter(PlayerWeaponStat.player_id == player_id).\
 449                 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
 450                 one()
 451
 452         avg = round(float(raw_avg[0])/raw_avg[1], 2)
 453
 454         # Determine the damage efficiency (hit, fired) numbers for $games games
 455         # This is then enumerated to create parameters for a flot graph
 456         raw_dmgs = DBSession.query(PlayerWeaponStat.game_id,
 457             PlayerWeaponStat.actual, PlayerWeaponStat.hit).\
 458                 filter(PlayerWeaponStat.player_id == player_id).\
 459                 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
 460                 order_by(PlayerWeaponStat.game_id.desc()).\
 461                 limit(games).\
 462                 all()
 463
 464         # they come out in opposite order, so flip them in the right direction
 465         raw_dmgs.reverse()
 466
 467         dmgs = []
 468         for i in range(len(raw_dmgs)):
 469             # try to derive, unless we've hit nothing then set to 0!
 470             try:
 471                 dmg = round(float(raw_dmgs[i][1])/raw_dmgs[i][2], 2)
 472             except:
 473                 dmg = 0.0
 474
 475             dmgs.append((raw_dmgs[i][0], dmg))
 476     except Exception as e:
 477         dmgs = []
 478         avg = 0.0
 479
 480     return (avg, dmgs)
 481
 482
 483 def player_info_data(request):
 484     player_id = int(request.matchdict['id'])
 485     if player_id <= 2:
 486         player_id = -1;
 487
 488     try:
 489         player = DBSession.query(Player).filter_by(player_id=player_id).\
 490                 filter(Player.active_ind == True).one()
 491
 492         games_played   = get_games_played(player_id)
 493         overall_stats  = get_overall_stats(player_id)
 494         fav_maps       = get_fav_maps(player_id)
 495         elos           = get_elos(player_id)
 496         ranks          = get_ranks(player_id)
 497         recent_games   = get_recent_games(player_id)
 498         recent_weapons = get_recent_weapons(player_id)
 499
 500     except Exception as e:
 501         player         = None
 502         games_played   = None
 503         overall_stats  = None
 504         fav_maps       = None
 505         elos           = None
 506         ranks          = None
 507         recent_games   = None
 508         recent_weapons = []
 509
 510     return {'player':player,
 511             'games_played':games_played,
 512             'overall_stats':overall_stats,
 513             'fav_maps':fav_maps,
 514             'elos':elos,
 515             'ranks':ranks,
 516             'recent_games':recent_games,
 517             'recent_weapons':recent_weapons
 518             }
 519
 520
 521 def player_info(request):
 522     """
 523     Provides detailed information on a specific player
 524     """
 525     return player_info_data(request)
 526
 527
 528 def player_info_json(request):
 529     """
 530     Provides detailed information on a specific player. JSON.
 531     """
 532     return [{'status':'not implemented'}]
 533
 534
 535 def player_game_index_data(request):
 536     player_id = request.matchdict['player_id']
 537
 538     if request.params.has_key('page'):
 539         current_page = request.params['page']
 540     else:
 541         current_page = 1
 542
 543     try:
 544         games_q = DBSession.query(Game, Server, Map).\
 545             filter(PlayerGameStat.game_id == Game.game_id).\
 546             filter(PlayerGameStat.player_id == player_id).\
 547             filter(Game.server_id == Server.server_id).\
 548             filter(Game.map_id == Map.map_id).\
 549             order_by(Game.game_id.desc())
 550
 551         games = Page(games_q, current_page, items_per_page=10, url=page_url)
 552
 553         pgstats = {}
 554         for (game, server, map) in games:
 555             pgstats[game.game_id] = DBSession.query(PlayerGameStat).\
 556                     filter(PlayerGameStat.game_id == game.game_id).\
 557                     order_by(PlayerGameStat.rank).\
 558                     order_by(PlayerGameStat.score).all()
 559
 560     except Exception as e:
 561         player = None
 562         games = None
 563
 564     return {'player_id':player_id,
 565             'games':games,
 566             'pgstats':pgstats}
 567
 568
 569 def player_game_index(request):
 570     """
 571     Provides an index of the games in which a particular
 572     player was involved. This is ordered by game_id, with
 573     the most recent game_ids first. Paginated.
 574     """
 575     return player_game_index_data(request)
 576
 577
 578 def player_game_index_json(request):
 579     """
 580     Provides an index of the games in which a particular
 581     player was involved. This is ordered by game_id, with
 582     the most recent game_ids first. Paginated. JSON.
 583     """
 584     return [{'status':'not implemented'}]
 585
 586
 587 def player_accuracy_data(request):
 588     player_id = request.matchdict['id']
 589     allowed_weapons = ['nex', 'rifle', 'shotgun', 'uzi', 'minstanex']
 590     weapon_cd = 'nex'
 591     games = 20
 592
 593     if request.params.has_key('weapon'):
 594         if request.params['weapon'] in allowed_weapons:
 595             weapon_cd = request.params['weapon']
 596
 597     if request.params.has_key('games'):
 598         try:
 599             games = request.params['games']
 600
 601             if games < 0:
 602                 games = 20
 603             if games > 50:
 604                 games = 50
 605         except:
 606             games = 20
 607
 608     (avg, accs) = get_accuracy_stats(player_id, weapon_cd, games)
 609
 610     # if we don't have enough data for the given weapon
 611     if len(accs) < games:
 612         games = len(accs)
 613
 614     return {
 615             'player_id':player_id,
 616             'player_url':request.route_url('player_info', id=player_id),
 617             'weapon':weapon_cd,
 618             'games':games,
 619             'avg':avg,
 620             'accs':accs
 621             }
 622
 623
 624 def player_accuracy(request):
 625     """
 626     Provides the accuracy for the given weapon. (JSON only)
 627     """
 628     return player_accuracy_data(request)
 629
 630
 631 def player_accuracy_json(request):
 632     """
 633     Provides a JSON response representing the accuracy for the given weapon.
 634
 635     Parameters:
 636        weapon = which weapon to display accuracy for. Valid values are 'nex',
 637                 'shotgun', 'uzi', and 'minstanex'.
 638        games = over how many games to display accuracy. Can be up to 50.
 639     """
 640     return player_accuracy_data(request)
 641
 642
 643 def player_damage_data(request):
 644     player_id = request.matchdict['id']
 645     allowed_weapons = ['grenadelauncher', 'electro', 'crylink', 'hagar',
 646             'rocketlauncher', 'laser']
 647     weapon_cd = 'rocketlauncher'
 648     games = 20
 649
 650     if request.params.has_key('weapon'):
 651         if request.params['weapon'] in allowed_weapons:
 652             weapon_cd = request.params['weapon']
 653
 654     if request.params.has_key('games'):
 655         try:
 656             games = request.params['games']
 657
 658             if games < 0:
 659                 games = 20
 660             if games > 50:
 661                 games = 50
 662         except:
 663             games = 20
 664
 665     (avg, dmgs) = get_damage_stats(player_id, weapon_cd, games)
 666
 667     # if we don't have enough data for the given weapon
 668     if len(dmgs) < games:
 669         games = len(dmgs)
 670
 671     return {
 672             'player_id':player_id,
 673             'player_url':request.route_url('player_info', id=player_id),
 674             'weapon':weapon_cd,
 675             'games':games,
 676             'avg':avg,
 677             'dmgs':dmgs
 678             }
 679
 680
 681 def player_damage_json(request):
 682     """
 683     Provides a JSON response representing the damage for the given weapon.
 684
 685     Parameters:
 686        weapon = which weapon to display damage for. Valid values are
 687          'grenadelauncher', 'electro', 'crylink', 'hagar', 'rocketlauncher',
 688          'laser'.
 689        games = over how many games to display damage. Can be up to 50.
 690     """
 691     return player_damage_data(request)