3 import pyramid.httpexceptions
4 import sqlalchemy as sa
5 import sqlalchemy.sql.functions as func
6 import sqlalchemy.sql.expression as expr
7 from calendar import timegm
8 from collections import namedtuple
9 from webhelpers.paginate import Page
10 from xonstat.models import *
11 from xonstat.util import page_url, to_json, pretty_date, datetime_seconds
12 from xonstat.util import is_cake_day, verify_request
13 from xonstat.views.helpers import RecentGame, recent_games_q
14 from urllib import unquote
16 log = logging.getLogger(__name__)
19 def player_index_data(request):
20 if request.params.has_key('page'):
21 current_page = request.params['page']
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())
32 players = Page(player_q, current_page, items_per_page=25, url=page_url)
34 except Exception as e:
38 return {'players':players
42 def player_index(request):
44 Provides a list of all the current players.
46 return player_index_data(request)
49 def player_index_json(request):
51 Provides a list of all the current players. JSON.
53 return [{'status':'not implemented'}]
56 def get_games_played(player_id):
58 Provides a breakdown by gametype of the games played by player_id.
60 Returns a list of namedtuples with the following members:
67 The list itself is ordered by the number of games played
69 GamesPlayed = namedtuple('GamesPlayed', ['game_type_cd', 'games', 'wins',
72 raw_games_played = DBSession.query('game_type_cd', 'wins', 'losses').\
74 "SELECT game_type_cd, "
77 "FROM (SELECT g.game_id, "
80 "WHEN g.winner = pgs.team THEN 1 "
81 "WHEN pgs.scoreboardpos = 1 THEN 1 "
85 "WHEN g.winner = pgs.team THEN 0 "
86 "WHEN pgs.scoreboardpos = 1 THEN 0 "
90 "player_game_stats pgs "
91 "WHERE g.game_id = pgs.game_id "
92 "AND pgs.player_id = :player_id "
93 "AND g.players @> ARRAY[:player_id]) win_loss "
94 "GROUP BY game_type_cd "
95 ).params(player_id=player_id).all()
101 for row in raw_games_played:
102 games = row.wins + row.losses
103 overall_games += games
104 overall_wins += row.wins
105 overall_losses += row.losses
106 win_pct = float(row.wins)/games * 100
108 games_played.append(GamesPlayed(row.game_type_cd, games, row.wins,
109 row.losses, win_pct))
112 overall_win_pct = float(overall_wins)/overall_games * 100
114 overall_win_pct = 0.0
116 games_played.append(GamesPlayed('overall', overall_games, overall_wins,
117 overall_losses, overall_win_pct))
119 # sort the resulting list by # of games played
120 games_played = sorted(games_played, key=lambda x:x.games)
121 games_played.reverse()
126 def get_overall_stats(player_id):
128 Provides a breakdown of stats by gametype played by player_id.
130 Returns a dictionary of namedtuples with the following members:
134 - last_played (last time the player played the game type)
135 - last_played_epoch (same as above, but in seconds since epoch)
136 - last_played_fuzzy (same as above, but in relative date)
137 - total_playing_time (total amount of time played the game type)
138 - total_playing_time_secs (same as the above, but in seconds)
139 - total_pickups (ctf only)
140 - total_captures (ctf only)
141 - cap_ratio (ctf only)
142 - total_carrier_frags (ctf only)
146 The key to the dictionary is the game type code. There is also an
147 "overall" game_type_cd which sums the totals and computes the total ratios.
149 OverallStats = namedtuple('OverallStats', ['total_kills', 'total_deaths',
150 'k_d_ratio', 'last_played', 'last_played_epoch', 'last_played_fuzzy',
151 'total_playing_time', 'total_playing_time_secs', 'total_pickups', 'total_captures', 'cap_ratio',
152 'total_carrier_frags', 'game_type_cd', 'game_type_descr'])
154 raw_stats = DBSession.query('game_type_cd', 'game_type_descr',
155 'total_kills', 'total_deaths', 'last_played', 'total_playing_time',
156 'total_pickups', 'total_captures', 'total_carrier_frags').\
158 "SELECT g.game_type_cd, "
159 "gt.descr game_type_descr, "
160 "Sum(pgs.kills) total_kills, "
161 "Sum(pgs.deaths) total_deaths, "
162 "Max(pgs.create_dt) last_played, "
163 "Sum(pgs.alivetime) total_playing_time, "
164 "Sum(pgs.pickups) total_pickups, "
165 "Sum(pgs.captures) total_captures, "
166 "Sum(pgs.carrier_frags) total_carrier_frags "
169 "player_game_stats pgs "
170 "WHERE g.game_id = pgs.game_id "
171 "AND g.game_type_cd = gt.game_type_cd "
172 "AND g.players @> ARRAY[:player_id] "
173 "AND pgs.player_id = :player_id "
174 "GROUP BY g.game_type_cd, game_type_descr "
176 "SELECT 'overall' game_type_cd, "
177 "'Overall' game_type_descr, "
178 "Sum(pgs.kills) total_kills, "
179 "Sum(pgs.deaths) total_deaths, "
180 "Max(pgs.create_dt) last_played, "
181 "Sum(pgs.alivetime) total_playing_time, "
182 "Sum(pgs.pickups) total_pickups, "
183 "Sum(pgs.captures) total_captures, "
184 "Sum(pgs.carrier_frags) total_carrier_frags "
185 "FROM player_game_stats pgs "
186 "WHERE pgs.player_id = :player_id "
187 ).params(player_id=player_id).all()
189 # to be indexed by game_type_cd
192 for row in raw_stats:
193 # individual gametype ratio calculations
195 k_d_ratio = float(row.total_kills)/row.total_deaths
200 cap_ratio = float(row.total_captures)/row.total_pickups
204 # everything else is untouched or "raw"
205 os = OverallStats(total_kills=row.total_kills,
206 total_deaths=row.total_deaths,
208 last_played=row.last_played,
209 last_played_epoch=timegm(row.last_played.timetuple()),
210 last_played_fuzzy=pretty_date(row.last_played),
211 total_playing_time=row.total_playing_time,
212 total_playing_time_secs=int(datetime_seconds(row.total_playing_time)),
213 total_pickups=row.total_pickups,
214 total_captures=row.total_captures,
216 total_carrier_frags=row.total_carrier_frags,
217 game_type_cd=row.game_type_cd,
218 game_type_descr=row.game_type_descr)
220 overall_stats[row.game_type_cd] = os
222 # We have to edit "overall" stats to exclude deaths in CTS.
223 # Although we still want to record deaths, they shouldn't
224 # count towards the overall K:D ratio.
225 if 'cts' in overall_stats:
226 os = overall_stats['overall']
229 k_d_ratio = float(os.total_kills)/(os.total_deaths - overall_stats['cts'].total_deaths)
233 non_cts_deaths = os.total_deaths - overall_stats['cts'].total_deaths
236 overall_stats['overall'] = OverallStats(
237 total_kills = os.total_kills,
238 total_deaths = non_cts_deaths,
239 k_d_ratio = k_d_ratio,
240 last_played = os.last_played,
241 last_played_epoch = os.last_played_epoch,
242 last_played_fuzzy = os.last_played_fuzzy,
243 total_playing_time = os.total_playing_time,
244 total_playing_time_secs = os.total_playing_time_secs,
245 total_pickups = os.total_pickups,
246 total_captures = os.total_captures,
247 cap_ratio = os.cap_ratio,
248 total_carrier_frags = os.total_carrier_frags,
249 game_type_cd = os.game_type_cd,
250 game_type_descr = os.game_type_descr)
255 def get_fav_maps(player_id, game_type_cd=None):
257 Provides a breakdown of favorite maps by gametype.
259 Returns a dictionary of namedtuples with the following members:
261 - map_name (map name)
265 The favorite map is defined as the map you've played the most
266 for the given game_type_cd.
268 The key to the dictionary is the game type code. There is also an
269 "overall" game_type_cd which is the overall favorite map. This is
270 defined as the favorite map of the game type you've played the
271 most. The input parameter game_type_cd is for this.
273 FavMap = namedtuple('FavMap', ['map_name', 'map_id', 'times_played', 'game_type_cd'])
275 raw_favs = DBSession.query('game_type_cd', 'map_name',
276 'map_id', 'times_played').\
278 "SELECT game_type_cd, "
282 "FROM (SELECT g.game_type_cd, "
285 "Count(*) times_played, "
288 "partition BY g.game_type_cd "
289 "ORDER BY Count(*) DESC, m.map_id ASC) rank "
291 "player_game_stats pgs, "
293 "WHERE g.game_id = pgs.game_id "
294 "AND g.map_id = m.map_id "
295 "AND g.players @> ARRAY[:player_id]"
296 "AND pgs.player_id = :player_id "
297 "GROUP BY g.game_type_cd, "
299 "m.name) most_played "
301 "ORDER BY times_played desc "
302 ).params(player_id=player_id).all()
307 fv = FavMap(map_name=row.map_name,
309 times_played=row.times_played,
310 game_type_cd=row.game_type_cd)
312 # if we aren't given a favorite game_type_cd
313 # then the overall favorite is the one we've
315 if overall_fav is None:
316 fav_maps['overall'] = fv
317 overall_fav = fv.game_type_cd
319 # otherwise it is the favorite map from the
320 # favorite game_type_cd (provided as a param)
321 # and we'll overwrite the first dict entry
322 if game_type_cd == fv.game_type_cd:
323 fav_maps['overall'] = fv
325 fav_maps[row.game_type_cd] = fv
330 def get_ranks(player_id):
332 Provides a breakdown of the player's ranks by game type.
334 Returns a dictionary of namedtuples with the following members:
339 The key to the dictionary is the game type code. There is also an
340 "overall" game_type_cd which is the overall best rank.
342 Rank = namedtuple('Rank', ['rank', 'max_rank', 'percentile', 'game_type_cd'])
344 raw_ranks = DBSession.query("game_type_cd", "rank", "max_rank").\
346 "select pr.game_type_cd, pr.rank, overall.max_rank "
347 "from player_ranks pr, "
348 "(select game_type_cd, max(rank) max_rank "
350 "group by game_type_cd) overall "
351 "where pr.game_type_cd = overall.game_type_cd "
353 "and player_id = :player_id "
355 params(player_id=player_id).all()
358 found_top_rank = False
359 for row in raw_ranks:
360 rank = Rank(rank=row.rank,
361 max_rank=row.max_rank,
362 percentile=100 - 100*float(row.rank-1)/(row.max_rank-1),
363 game_type_cd=row.game_type_cd)
366 if not found_top_rank:
367 ranks['overall'] = rank
368 found_top_rank = True
369 elif rank.percentile > ranks['overall'].percentile:
370 ranks['overall'] = rank
372 ranks[row.game_type_cd] = rank
377 def get_elos(player_id):
379 Provides a breakdown of the player's elos by game type.
381 Returns a dictionary of namedtuples with the following members:
387 The key to the dictionary is the game type code. There is also an
388 "overall" game_type_cd which is the overall best rank.
390 raw_elos = DBSession.query(PlayerElo).filter_by(player_id=player_id).\
391 order_by(PlayerElo.elo.desc()).all()
394 found_max_elo = False
396 if not found_max_elo:
397 elos['overall'] = row
400 elos[row.game_type_cd] = row
405 def get_recent_games(player_id, limit=10):
407 Provides a list of recent games for a player. Uses the recent_games_q helper.
409 # recent games played in descending order
410 rgs = recent_games_q(player_id=player_id, force_player_id=True).limit(limit).all()
411 recent_games = [RecentGame(row) for row in rgs]
416 def get_accuracy_stats(player_id, weapon_cd, games):
418 Provides accuracy for weapon_cd by player_id for the past N games.
420 # Reaching back 90 days should give us an accurate enough average
421 # We then multiply this out for the number of data points (games) to
422 # create parameters for a flot graph
424 raw_avg = DBSession.query(func.sum(PlayerWeaponStat.hit),
425 func.sum(PlayerWeaponStat.fired)).\
426 filter(PlayerWeaponStat.player_id == player_id).\
427 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
430 avg = round(float(raw_avg[0])/raw_avg[1]*100, 2)
432 # Determine the raw accuracy (hit, fired) numbers for $games games
433 # This is then enumerated to create parameters for a flot graph
434 raw_accs = DBSession.query(PlayerWeaponStat.game_id,
435 PlayerWeaponStat.hit, PlayerWeaponStat.fired).\
436 filter(PlayerWeaponStat.player_id == player_id).\
437 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
438 order_by(PlayerWeaponStat.game_id.desc()).\
442 # they come out in opposite order, so flip them in the right direction
446 for i in range(len(raw_accs)):
447 accs.append((raw_accs[i][0], round(float(raw_accs[i][1])/raw_accs[i][2]*100, 2)))
455 def get_damage_stats(player_id, weapon_cd, games):
457 Provides damage info for weapon_cd by player_id for the past N games.
460 raw_avg = DBSession.query(func.sum(PlayerWeaponStat.actual),
461 func.sum(PlayerWeaponStat.hit)).\
462 filter(PlayerWeaponStat.player_id == player_id).\
463 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
466 avg = round(float(raw_avg[0])/raw_avg[1], 2)
468 # Determine the damage efficiency (hit, fired) numbers for $games games
469 # This is then enumerated to create parameters for a flot graph
470 raw_dmgs = DBSession.query(PlayerWeaponStat.game_id,
471 PlayerWeaponStat.actual, PlayerWeaponStat.hit).\
472 filter(PlayerWeaponStat.player_id == player_id).\
473 filter(PlayerWeaponStat.weapon_cd == weapon_cd).\
474 order_by(PlayerWeaponStat.game_id.desc()).\
478 # they come out in opposite order, so flip them in the right direction
482 for i in range(len(raw_dmgs)):
483 # try to derive, unless we've hit nothing then set to 0!
485 dmg = round(float(raw_dmgs[i][1])/raw_dmgs[i][2], 2)
489 dmgs.append((raw_dmgs[i][0], dmg))
490 except Exception as e:
497 def player_info_data(request):
498 player_id = int(request.matchdict['id'])
503 player = DBSession.query(Player).filter_by(player_id=player_id).\
504 filter(Player.active_ind == True).one()
506 games_played = get_games_played(player_id)
507 overall_stats = get_overall_stats(player_id)
508 fav_maps = get_fav_maps(player_id)
509 elos = get_elos(player_id)
510 ranks = get_ranks(player_id)
511 recent_games = get_recent_games(player_id)
512 cake_day = is_cake_day(player.create_dt)
514 except Exception as e:
515 raise pyramid.httpexceptions.HTTPNotFound
517 ## do not raise application exceptions here (only for debugging)
520 return {'player':player,
521 'games_played':games_played,
522 'overall_stats':overall_stats,
526 'recent_games':recent_games,
531 def player_info(request):
533 Provides detailed information on a specific player
535 return player_info_data(request)
538 def player_info_json(request):
540 Provides detailed information on a specific player. JSON.
543 # All player_info fields are converted into JSON-formattable dictionaries
544 player_info = player_info_data(request)
546 player = player_info['player'].to_dict()
549 for game in player_info['games_played']:
550 games_played[game.game_type_cd] = to_json(game)
553 for gt,stats in player_info['overall_stats'].items():
554 overall_stats[gt] = to_json(stats)
557 for gt,elo in player_info['elos'].items():
558 elos[gt] = to_json(elo.to_dict())
561 for gt,rank in player_info['ranks'].items():
562 ranks[gt] = to_json(rank)
565 for gt,mapinfo in player_info['fav_maps'].items():
566 fav_maps[gt] = to_json(mapinfo)
568 recent_games = [g.to_dict() for g in player_info['recent_games']]
572 'games_played': games_played,
573 'overall_stats': overall_stats,
574 'fav_maps': fav_maps,
577 'recent_games': recent_games,
581 def player_game_index_data(request):
583 player_id = int(request.matchdict['player_id'])
588 game_type_descr = None
590 if request.params.has_key('type'):
591 game_type_cd = request.params['type']
593 game_type_descr = DBSession.query(GameType.descr).\
594 filter(GameType.game_type_cd == game_type_cd).\
596 except Exception as e:
601 game_type_descr = None
603 if request.params.has_key('page'):
604 current_page = request.params['page']
609 player = DBSession.query(Player).\
610 filter_by(player_id=player_id).\
611 filter(Player.active_ind == True).\
614 rgs_q = recent_games_q(player_id=player.player_id,
615 force_player_id=True, game_type_cd=game_type_cd)
617 games = Page(rgs_q, current_page, items_per_page=20, url=page_url)
619 # replace the items in the canned pagination class with more rich ones
620 games.items = [RecentGame(row) for row in games.items]
622 games_played = get_games_played(player_id)
624 except Exception as e:
629 game_type_descr = None
633 'player_id':player.player_id,
636 'game_type_cd':game_type_cd,
637 'game_type_descr':game_type_descr,
638 'games_played':games_played,
642 def player_game_index(request):
644 Provides an index of the games in which a particular
645 player was involved. This is ordered by game_id, with
646 the most recent game_ids first. Paginated.
648 return player_game_index_data(request)
651 def player_game_index_json(request):
653 Provides an index of the games in which a particular
654 player was involved. This is ordered by game_id, with
655 the most recent game_ids first. Paginated. JSON.
657 return [{'status':'not implemented'}]
660 def player_accuracy_data(request):
661 player_id = request.matchdict['id']
662 allowed_weapons = ['nex', 'rifle', 'shotgun', 'uzi', 'minstanex']
666 if request.params.has_key('weapon'):
667 if request.params['weapon'] in allowed_weapons:
668 weapon_cd = request.params['weapon']
670 if request.params.has_key('games'):
672 games = request.params['games']
681 (avg, accs) = get_accuracy_stats(player_id, weapon_cd, games)
683 # if we don't have enough data for the given weapon
684 if len(accs) < games:
688 'player_id':player_id,
689 'player_url':request.route_url('player_info', id=player_id),
697 def player_accuracy(request):
699 Provides the accuracy for the given weapon. (JSON only)
701 return player_accuracy_data(request)
704 def player_accuracy_json(request):
706 Provides a JSON response representing the accuracy for the given weapon.
709 weapon = which weapon to display accuracy for. Valid values are 'nex',
710 'shotgun', 'uzi', and 'minstanex'.
711 games = over how many games to display accuracy. Can be up to 50.
713 return player_accuracy_data(request)
716 def player_damage_data(request):
717 player_id = request.matchdict['id']
718 allowed_weapons = ['grenadelauncher', 'electro', 'crylink', 'hagar',
719 'rocketlauncher', 'laser']
720 weapon_cd = 'rocketlauncher'
723 if request.params.has_key('weapon'):
724 if request.params['weapon'] in allowed_weapons:
725 weapon_cd = request.params['weapon']
727 if request.params.has_key('games'):
729 games = request.params['games']
738 (avg, dmgs) = get_damage_stats(player_id, weapon_cd, games)
740 # if we don't have enough data for the given weapon
741 if len(dmgs) < games:
745 'player_id':player_id,
746 'player_url':request.route_url('player_info', id=player_id),
754 def player_damage_json(request):
756 Provides a JSON response representing the damage for the given weapon.
759 weapon = which weapon to display damage for. Valid values are
760 'grenadelauncher', 'electro', 'crylink', 'hagar', 'rocketlauncher',
762 games = over how many games to display damage. Can be up to 50.
764 return player_damage_data(request)
767 def player_hashkey_info_data(request):
768 # hashkey = request.matchdict['hashkey']
770 # the incoming hashkey is double quoted, and WSGI unquotes once...
771 # hashkey = unquote(hashkey)
773 # if using request verification to obtain the hashkey
774 (idfp, status) = verify_request(request)
775 log.debug("d0_blind_id verification: idfp={0} status={1}\n".format(idfp, status))
777 log.debug("\n----- BEGIN REQUEST BODY -----\n" + request.body +
778 "----- END REQUEST BODY -----\n\n")
780 # if config is to *not* verify requests and we get nothing back, this
781 # query will return nothing and we'll 404.
783 player = DBSession.query(Player).\
784 filter(Player.player_id == Hashkey.player_id).\
785 filter(Player.active_ind == True).\
786 filter(Hashkey.hashkey == idfp).one()
788 games_played = get_games_played(player.player_id)
789 overall_stats = get_overall_stats(player.player_id)
790 fav_maps = get_fav_maps(player.player_id)
791 elos = get_elos(player.player_id)
792 ranks = get_ranks(player.player_id)
793 most_recent_game = get_recent_games(player.player_id, 1)[0]
795 except Exception as e:
796 raise pyramid.httpexceptions.HTTPNotFound
798 return {'player':player,
800 'games_played':games_played,
801 'overall_stats':overall_stats,
805 'most_recent_game':most_recent_game,
809 def player_hashkey_info_json(request):
811 Provides detailed information on a specific player. JSON.
814 # All player_info fields are converted into JSON-formattable dictionaries
815 player_info = player_hashkey_info_data(request)
817 player = player_info['player'].to_dict()
820 for game in player_info['games_played']:
821 games_played[game.game_type_cd] = to_json(game)
824 for gt,stats in player_info['overall_stats'].items():
825 overall_stats[gt] = to_json(stats)
828 for gt,elo in player_info['elos'].items():
829 elos[gt] = to_json(elo.to_dict())
832 for gt,rank in player_info['ranks'].items():
833 ranks[gt] = to_json(rank)
836 for gt,mapinfo in player_info['fav_maps'].items():
837 fav_maps[gt] = to_json(mapinfo)
839 most_recent_game = to_json(player_info['most_recent_game'])
844 'games_played': games_played,
845 'overall_stats': overall_stats,
846 'fav_maps': fav_maps,
849 'most_recent_game': most_recent_game,
853 def player_hashkey_info_text(request):
855 Provides detailed information on a specific player. Plain text.
858 now = timegm(datetime.datetime.utcnow().timetuple())
860 # All player_info fields are converted into JSON-formattable dictionaries
861 player_info = player_hashkey_info_data(request)
863 # gather all of the data up into aggregate structures
864 player = player_info['player']
865 games_played = player_info['games_played']
866 overall_stats = player_info['overall_stats']
867 elos = player_info['elos']
868 ranks = player_info['ranks']
869 fav_maps = player_info['fav_maps']
870 most_recent_game = player_info['most_recent_game']
872 # one-offs for things needing conversion for text/plain
873 player_joined = timegm(player.create_dt.timetuple())
874 player_joined_dt = player.create_dt
875 alivetime = int(datetime_seconds(overall_stats['overall'].total_playing_time))
877 # this is a plain text response, if we don't do this here then
878 # Pyramid will assume html
879 request.response.content_type = 'text/plain'
885 'hashkey': player_info['hashkey'],
886 'player_joined': player_joined,
887 'player_joined_dt': player_joined_dt,
888 'games_played': games_played,
889 'overall_stats': overall_stats,
890 'alivetime': alivetime,
891 'fav_maps': fav_maps,
894 'most_recent_game': most_recent_game,
898 def player_elo_info_data(request):
900 Provides elo information on a specific player. Raw data is returned.
902 (idfp, status) = verify_request(request)
903 log.debug("d0_blind_id verification: idfp={0} status={1}\n".format(idfp, status))
905 log.debug("\n----- BEGIN REQUEST BODY -----\n" + request.body +
906 "----- END REQUEST BODY -----\n\n")
908 hashkey = request.matchdict['hashkey']
910 # the incoming hashkey is double quoted, and WSGI unquotes once...
911 hashkey = unquote(hashkey)
914 player = DBSession.query(Player).\
915 filter(Player.player_id == Hashkey.player_id).\
916 filter(Player.active_ind == True).\
917 filter(Hashkey.hashkey == hashkey).one()
919 elos = get_elos(player.player_id)
921 except Exception as e:
923 raise pyramid.httpexceptions.HTTPNotFound
932 def player_elo_info_json(request):
934 Provides elo information on a specific player. JSON.
936 elo_info = player_elo_info_data(request)
938 player = player_info['player'].to_dict()
941 for gt, elo in elo_info['elos'].items():
942 elos[gt] = to_json(elo.to_dict())
951 def player_elo_info_text(request):
953 Provides elo information on a specific player. Plain text.
956 now = timegm(datetime.datetime.utcnow().timetuple())
958 # All player_info fields are converted into JSON-formattable dictionaries
959 elo_info = player_elo_info_data(request)
961 # this is a plain text response, if we don't do this here then
962 # Pyramid will assume html
963 request.response.content_type = 'text/plain'
968 'hashkey': elo_info['hashkey'],
969 'player': elo_info['player'],
970 'elos': elo_info['elos'],
974 def player_captimes_data(request):
975 player_id = int(request.matchdict['player_id'])
979 current_page = request.params.get("page", 1)
982 player = DBSession.query(Player).filter_by(player_id=player_id).one()
984 pct_q = DBSession.query(PlayerCaptime.fastest_cap, PlayerCaptime.create_dt,
985 PlayerCaptime.player_id, PlayerCaptime.game_id, PlayerCaptime.map_id,
986 Map.name.label('map_name'), Game.server_id, Server.name.label('server_name')).\
987 filter(PlayerCaptime.player_id==player_id).\
988 filter(PlayerCaptime.game_id==Game.game_id).\
989 filter(PlayerCaptime.map_id==Map.map_id).\
990 filter(Game.server_id==Server.server_id).\
991 order_by(expr.desc(PlayerCaptime.create_dt))
993 except Exception as e:
994 raise pyramid.httpexceptions.HTTPNotFound
996 captimes = Page(pct_q, current_page, items_per_page=20, url=page_url)
998 # replace the items in the canned pagination class with more rich ones
999 captimes.items = [PlayerCapTime(row) for row in captimes.items]
1002 "player_id" : player_id,
1004 "captimes" : captimes,
1008 def player_captimes(request):
1009 return player_captimes_data(request)
1012 def player_captimes_json(request):
1013 data = player_captimes_data(request)
1014 page = request.params.get("page", 1)
1016 # perform any necessary JSON conversions
1017 player_id = data["player_id"]
1018 player = data["player"].to_dict()
1019 captimes = [ct.to_dict() for ct in data["captimes"].items]
1023 "captimes" : captimes,
1028 def player_weaponstats_data_json(request):
1029 player_id = int(request.matchdict["id"])
1033 game_type_cd = request.params.get("game_type", None)
1034 if game_type_cd == "overall":
1038 if request.params.has_key("limit"):
1039 limit = int(request.params["limit"])
1047 # the game_ids of the most recently played ones
1048 # of the given game type is used for a subquery
1049 games_list = DBSession.query(Game.game_id).\
1050 filter(Game.players.contains([player_id]))
1052 if game_type_cd is not None:
1053 games_list = games_list.filter(Game.game_type_cd == game_type_cd)
1055 games_list = games_list.order_by(Game.game_id.desc()).limit(limit)
1057 weapon_stats_raw = DBSession.query(PlayerWeaponStat).\
1058 filter(PlayerWeaponStat.player_id == player_id).\
1059 filter(PlayerWeaponStat.game_id.in_(games_list)).\
1062 games_to_weapons = {}
1065 for ws in weapon_stats_raw:
1066 if ws.game_id not in games_to_weapons:
1067 games_to_weapons[ws.game_id] = [ws.weapon_cd]
1069 games_to_weapons[ws.game_id].append(ws.weapon_cd)
1071 weapons_used[ws.weapon_cd] = weapons_used.get(ws.weapon_cd, 0) + 1
1072 sum_avgs[ws.weapon_cd] = sum_avgs.get(ws.weapon_cd, 0) + float(ws.hit)/float(ws.fired)
1074 # Creating zero-valued weapon stat entries for games where a weapon was not
1075 # used in that game, but was used in another game for the set. This makes
1076 # the charts look smoother
1077 for game_id in games_to_weapons.keys():
1078 for weapon_cd in set(weapons_used.keys()) - set(games_to_weapons[game_id]):
1079 weapon_stats_raw.append(PlayerWeaponStat(player_id=player_id,
1080 game_id=game_id, weapon_cd=weapon_cd))
1082 # averages for the weapons used in the range
1084 for w in weapons_used.keys():
1085 avgs[w] = round(sum_avgs[w]/float(weapons_used[w])*100, 2)
1087 weapon_stats_raw = sorted(weapon_stats_raw, key = lambda x: x.game_id)
1088 games = sorted(games_to_weapons.keys())
1089 weapon_stats = [ws.to_dict() for ws in weapon_stats_raw]
1092 "weapon_stats": weapon_stats,
1093 "weapons_used": weapons_used.keys(),