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
15 log = logging.getLogger(__name__)
18 def player_index_data(request):
19 if request.params.has_key('page'):
20 current_page = request.params['page']
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())
31 players = Page(player_q, current_page, items_per_page=25, url=page_url)
33 except Exception as e:
37 return {'players':players
41 def player_index(request):
43 Provides a list of all the current players.
45 return player_index_data(request)
48 def player_index_json(request):
50 Provides a list of all the current players. JSON.
52 return [{'status':'not implemented'}]
55 def get_games_played(player_id):
57 Provides a breakdown by gametype of the games played by player_id.
59 Returns a list of namedtuples with the following members:
66 The list itself is ordered by the number of games played
68 GamesPlayed = namedtuple('GamesPlayed', ['game_type_cd', 'games', 'wins',
71 raw_games_played = DBSession.query('game_type_cd', 'wins', 'losses').\
73 "SELECT game_type_cd, "
76 "FROM (SELECT g.game_id, "
79 "WHEN g.winner = pgs.team THEN 1 "
80 "WHEN pgs.scoreboardpos = 1 THEN 1 "
84 "WHEN g.winner = pgs.team THEN 0 "
85 "WHEN pgs.scoreboardpos = 1 THEN 0 "
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()
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
106 games_played.append(GamesPlayed(row.game_type_cd, games, row.wins,
107 row.losses, win_pct))
110 overall_win_pct = float(overall_wins)/overall_games * 100
112 overall_win_pct = 0.0
114 games_played.append(GamesPlayed('overall', overall_games, overall_wins,
115 overall_losses, overall_win_pct))
117 # sort the resulting list by # of games played
118 games_played = sorted(games_played, key=lambda x:x.games)
119 games_played.reverse()
123 def get_overall_stats(player_id):
125 Provides a breakdown of stats by gametype played by player_id.
127 Returns a dictionary of namedtuples with the following members:
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)
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.
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'])
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').\
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 "
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 "
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()
185 # to be indexed by game_type_cd
188 for row in raw_stats:
189 # individual gametype ratio calculations
191 k_d_ratio = float(row.total_kills)/row.total_deaths
196 cap_ratio = float(row.total_captures)/row.total_pickups
200 # everything else is untouched or "raw"
201 os = OverallStats(total_kills=row.total_kills,
202 total_deaths=row.total_deaths,
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,
212 total_carrier_frags=row.total_carrier_frags,
213 game_type_cd=row.game_type_cd,
214 game_type_descr=row.game_type_descr)
216 overall_stats[row.game_type_cd] = os
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']
225 k_d_ratio = float(os.total_kills)/(os.total_deaths - overall_stats['cts'].total_deaths)
229 non_cts_deaths = os.total_deaths - overall_stats['cts'].total_deaths
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)
251 def get_fav_maps(player_id, game_type_cd=None):
253 Provides a breakdown of favorite maps by gametype.
255 Returns a dictionary of namedtuples with the following members:
257 - map_name (map name)
261 The favorite map is defined as the map you've played the most
262 for the given game_type_cd.
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.
269 FavMap = namedtuple('FavMap', ['map_name', 'map_id', 'times_played', 'game_type_cd'])
271 raw_favs = DBSession.query('game_type_cd', 'map_name',
272 'map_id', 'times_played').\
274 "SELECT game_type_cd, "
278 "FROM (SELECT g.game_type_cd, "
281 "Count(*) times_played, "
284 "partition BY g.game_type_cd "
285 "ORDER BY Count(*) DESC, m.map_id ASC) rank "
287 "player_game_stats pgs, "
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, "
294 "m.name) most_played "
296 "ORDER BY times_played desc "
297 ).params(player_id=player_id).all()
302 fv = FavMap(map_name=row.map_name,
304 times_played=row.times_played,
305 game_type_cd=row.game_type_cd)
307 # if we aren't given a favorite game_type_cd
308 # then the overall favorite is the one we've
310 if overall_fav is None:
311 fav_maps['overall'] = fv
312 overall_fav = fv.game_type_cd
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
320 fav_maps[row.game_type_cd] = fv
325 def get_ranks(player_id):
327 Provides a breakdown of the player's ranks by game type.
329 Returns a dictionary of namedtuples with the following members:
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.
337 Rank = namedtuple('Rank', ['rank', 'max_rank', 'percentile', 'game_type_cd'])
339 raw_ranks = DBSession.query("game_type_cd", "rank", "max_rank").\
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 "
345 "group by game_type_cd) overall "
346 "where pr.game_type_cd = overall.game_type_cd "
347 "and player_id = :player_id "
349 params(player_id=player_id).all()
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)
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
366 ranks[row.game_type_cd] = rank
371 def get_elos(player_id):
373 Provides a breakdown of the player's elos by game type.
375 Returns a dictionary of namedtuples with the following members:
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.
384 raw_elos = DBSession.query(PlayerElo).filter_by(player_id=player_id).\
385 order_by(PlayerElo.elo.desc()).all()
388 found_max_elo = False
390 if not found_max_elo:
391 elos['overall'] = row
394 elos[row.game_type_cd] = row
399 def get_recent_games(player_id, limit=10):
401 Provides a list of recent games for a player. Uses the recent_games_q helper.
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]
410 def get_recent_weapons(player_id):
412 Returns the weapons that have been used in the past 90 days
413 and also used in 5 games or more.
415 cutoff = datetime.datetime.utcnow() - datetime.timedelta(days=90)
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).\
423 recent_weapons.append(weapon[0])
425 return recent_weapons
428 def get_accuracy_stats(player_id, weapon_cd, games):
430 Provides accuracy for weapon_cd by player_id for the past N games.
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
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).\
442 avg = round(float(raw_avg[0])/raw_avg[1]*100, 2)
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()).\
454 # they come out in opposite order, so flip them in the right direction
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)))
467 def get_damage_stats(player_id, weapon_cd, games):
469 Provides damage info for weapon_cd by player_id for the past N games.
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).\
478 avg = round(float(raw_avg[0])/raw_avg[1], 2)
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()).\
490 # they come out in opposite order, so flip them in the right direction
494 for i in range(len(raw_dmgs)):
495 # try to derive, unless we've hit nothing then set to 0!
497 dmg = round(float(raw_dmgs[i][1])/raw_dmgs[i][2], 2)
501 dmgs.append((raw_dmgs[i][0], dmg))
502 except Exception as e:
509 def player_info_data(request):
510 player_id = int(request.matchdict['id'])
515 player = DBSession.query(Player).filter_by(player_id=player_id).\
516 filter(Player.active_ind == True).one()
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)
527 except Exception as e:
528 raise pyramid.httpexceptions.HTTPNotFound
530 ## do not raise application exceptions here (only for debugging)
533 return {'player':player,
534 'games_played':games_played,
535 'overall_stats':overall_stats,
539 'recent_games':recent_games,
540 'recent_weapons':recent_weapons,
545 def player_info(request):
547 Provides detailed information on a specific player
549 return player_info_data(request)
552 def player_info_json(request):
554 Provides detailed information on a specific player. JSON.
557 # All player_info fields are converted into JSON-formattable dictionaries
558 player_info = player_info_data(request)
560 player = player_info['player'].to_dict()
563 for game in player_info['games_played']:
564 games_played[game.game_type_cd] = to_json(game)
567 for gt,stats in player_info['overall_stats'].items():
568 overall_stats[gt] = to_json(stats)
571 for gt,elo in player_info['elos'].items():
572 elos[gt] = to_json(elo.to_dict())
575 for gt,rank in player_info['ranks'].items():
576 ranks[gt] = to_json(rank)
579 for gt,mapinfo in player_info['fav_maps'].items():
580 fav_maps[gt] = to_json(mapinfo)
583 for game in player_info['recent_games']:
584 recent_games.append(to_json(game))
586 #recent_weapons = player_info['recent_weapons']
590 'games_played': games_played,
591 'overall_stats': overall_stats,
592 'fav_maps': fav_maps,
595 'recent_games': recent_games,
596 # 'recent_weapons': recent_weapons,
597 'recent_weapons': ['not implemented'],
599 #return [{'status':'not implemented'}]
602 def player_game_index_data(request):
603 player_id = request.matchdict['player_id']
606 game_type_descr = None
608 if request.params.has_key('type'):
609 game_type_cd = request.params['type']
611 game_type_descr = DBSession.query(GameType.descr).\
612 filter(GameType.game_type_cd == game_type_cd).\
614 except Exception as e:
619 game_type_descr = None
621 if request.params.has_key('page'):
622 current_page = request.params['page']
627 player = DBSession.query(Player).\
628 filter_by(player_id=player_id).\
629 filter(Player.active_ind == True).\
632 rgs_q = recent_games_q(player_id=player.player_id,
633 force_player_id=True, game_type_cd=game_type_cd)
635 games = Page(rgs_q, current_page, items_per_page=20, url=page_url)
637 # replace the items in the canned pagination class with more rich ones
638 games.items = [RecentGame(row) for row in games.items]
640 games_played = get_games_played(player_id)
642 except Exception as e:
646 game_type_descr = None
650 'player_id':player.player_id,
653 'game_type_cd':game_type_cd,
654 'game_type_descr':game_type_descr,
655 'games_played':games_played,
659 def player_game_index(request):
661 Provides an index of the games in which a particular
662 player was involved. This is ordered by game_id, with
663 the most recent game_ids first. Paginated.
665 return player_game_index_data(request)
668 def player_game_index_json(request):
670 Provides an index of the games in which a particular
671 player was involved. This is ordered by game_id, with
672 the most recent game_ids first. Paginated. JSON.
674 return [{'status':'not implemented'}]
677 def player_accuracy_data(request):
678 player_id = request.matchdict['id']
679 allowed_weapons = ['nex', 'rifle', 'shotgun', 'uzi', 'minstanex']
683 if request.params.has_key('weapon'):
684 if request.params['weapon'] in allowed_weapons:
685 weapon_cd = request.params['weapon']
687 if request.params.has_key('games'):
689 games = request.params['games']
698 (avg, accs) = get_accuracy_stats(player_id, weapon_cd, games)
700 # if we don't have enough data for the given weapon
701 if len(accs) < games:
705 'player_id':player_id,
706 'player_url':request.route_url('player_info', id=player_id),
714 def player_accuracy(request):
716 Provides the accuracy for the given weapon. (JSON only)
718 return player_accuracy_data(request)
721 def player_accuracy_json(request):
723 Provides a JSON response representing the accuracy for the given weapon.
726 weapon = which weapon to display accuracy for. Valid values are 'nex',
727 'shotgun', 'uzi', and 'minstanex'.
728 games = over how many games to display accuracy. Can be up to 50.
730 return player_accuracy_data(request)
733 def player_damage_data(request):
734 player_id = request.matchdict['id']
735 allowed_weapons = ['grenadelauncher', 'electro', 'crylink', 'hagar',
736 'rocketlauncher', 'laser']
737 weapon_cd = 'rocketlauncher'
740 if request.params.has_key('weapon'):
741 if request.params['weapon'] in allowed_weapons:
742 weapon_cd = request.params['weapon']
744 if request.params.has_key('games'):
746 games = request.params['games']
755 (avg, dmgs) = get_damage_stats(player_id, weapon_cd, games)
757 # if we don't have enough data for the given weapon
758 if len(dmgs) < games:
762 'player_id':player_id,
763 'player_url':request.route_url('player_info', id=player_id),
771 def player_damage_json(request):
773 Provides a JSON response representing the damage for the given weapon.
776 weapon = which weapon to display damage for. Valid values are
777 'grenadelauncher', 'electro', 'crylink', 'hagar', 'rocketlauncher',
779 games = over how many games to display damage. Can be up to 50.
781 return player_damage_data(request)
784 def player_hashkey_info_data(request):
785 # hashkey = request.matchdict['hashkey']
787 # the incoming hashkey is double quoted, and WSGI unquotes once...
788 # hashkey = unquote(hashkey)
790 # if using request verification to obtain the hashkey
791 (hashkey, status) = verify_request(request)
793 # if config is to *not* verify requests and we get nothing back, this
794 # query will return nothing and we'll 404.
796 player = DBSession.query(Player).\
797 filter(Player.player_id == Hashkey.player_id).\
798 filter(Player.active_ind == True).\
799 filter(Hashkey.hashkey == hashkey).one()
801 games_played = get_games_played(player.player_id)
802 overall_stats = get_overall_stats(player.player_id)
803 fav_maps = get_fav_maps(player.player_id)
804 elos = get_elos(player.player_id)
805 ranks = get_ranks(player.player_id)
806 most_recent_game = get_recent_games(player.player_id, 1)[0]
808 except Exception as e:
809 raise pyramid.httpexceptions.HTTPNotFound
811 return {'player':player,
813 'games_played':games_played,
814 'overall_stats':overall_stats,
818 'most_recent_game':most_recent_game,
822 def player_hashkey_info_json(request):
824 Provides detailed information on a specific player. JSON.
827 # All player_info fields are converted into JSON-formattable dictionaries
828 player_info = player_hashkey_info_data(request)
830 player = player_info['player'].to_dict()
833 for game in player_info['games_played']:
834 games_played[game.game_type_cd] = to_json(game)
837 for gt,stats in player_info['overall_stats'].items():
838 overall_stats[gt] = to_json(stats)
841 for gt,elo in player_info['elos'].items():
842 elos[gt] = to_json(elo.to_dict())
845 for gt,rank in player_info['ranks'].items():
846 ranks[gt] = to_json(rank)
849 for gt,mapinfo in player_info['fav_maps'].items():
850 fav_maps[gt] = to_json(mapinfo)
852 most_recent_game = to_json(player_info['most_recent_game'])
857 'games_played': games_played,
858 'overall_stats': overall_stats,
859 'fav_maps': fav_maps,
862 'most_recent_game': most_recent_game,
866 def player_hashkey_info_text(request):
868 Provides detailed information on a specific player. Plain text.
871 now = timegm(datetime.datetime.utcnow().timetuple())
873 # All player_info fields are converted into JSON-formattable dictionaries
874 player_info = player_hashkey_info_data(request)
876 # gather all of the data up into aggregate structures
877 player = player_info['player']
878 games_played = player_info['games_played']
879 overall_stats = player_info['overall_stats']
880 elos = player_info['elos']
881 ranks = player_info['ranks']
882 fav_maps = player_info['fav_maps']
883 most_recent_game = player_info['most_recent_game']
885 # one-offs for things needing conversion for text/plain
886 player_joined = timegm(player.create_dt.timetuple())
887 player_joined_dt = player.create_dt
888 alivetime = int(datetime_seconds(overall_stats['overall'].total_playing_time))
890 # this is a plain text response, if we don't do this here then
891 # Pyramid will assume html
892 request.response.content_type = 'text/plain'
898 'hashkey': player_info['hashkey'],
899 'player_joined': player_joined,
900 'player_joined_dt': player_joined_dt,
901 'games_played': games_played,
902 'overall_stats': overall_stats,
903 'alivetime': alivetime,
904 'fav_maps': fav_maps,
907 'most_recent_game': most_recent_game,
911 def player_elo_info_data(request):
913 Provides elo information on a specific player. Raw data is returned.
915 hashkey = request.matchdict['hashkey']
917 # the incoming hashkey is double quoted, and WSGI unquotes once...
918 hashkey = unquote(hashkey)
921 player = DBSession.query(Player).\
922 filter(Player.player_id == Hashkey.player_id).\
923 filter(Player.active_ind == True).\
924 filter(Hashkey.hashkey == hashkey).one()
926 elos = get_elos(player.player_id)
928 except Exception as e:
930 raise pyramid.httpexceptions.HTTPNotFound
939 def player_elo_info_json(request):
941 Provides elo information on a specific player. JSON.
943 elo_info = player_elo_info_data(request)
945 player = player_info['player'].to_dict()
948 for gt, elo in elo_info['elos'].items():
949 elos[gt] = to_json(elo.to_dict())
958 def player_elo_info_text(request):
960 Provides elo information on a specific player. Plain text.
963 now = timegm(datetime.datetime.utcnow().timetuple())
965 # All player_info fields are converted into JSON-formattable dictionaries
966 elo_info = player_elo_info_data(request)
968 # this is a plain text response, if we don't do this here then
969 # Pyramid will assume html
970 request.response.content_type = 'text/plain'
975 'hashkey': elo_info['hashkey'],
976 'player': elo_info['player'],
977 'elos': elo_info['elos'],
981 def player_captimes_data(request):
982 player_id = int(request.matchdict['id'])
986 PlayerCaptimes = namedtuple('PlayerCaptimes', ['fastest_cap', 'create_dt', 'create_dt_epoch', 'create_dt_fuzzy',
987 'player_id', 'game_id', 'map_id', 'map_name', 'server_id', 'server_name'])
989 dbquery = DBSession.query('fastest_cap', 'create_dt', 'player_id', 'game_id', 'map_id',
990 'map_name', 'server_id', 'server_name').\
992 "SELECT ct.fastest_cap, "
999 "s.name server_name "
1000 "FROM player_map_captimes ct, "
1004 "WHERE ct.player_id = :player_id "
1005 "AND g.game_id = ct.game_id "
1006 "AND g.server_id = s.server_id "
1007 "AND m.map_id = ct.map_id "
1008 #"ORDER BY ct.fastest_cap "
1009 "ORDER BY ct.create_dt desc"
1010 ).params(player_id=player_id).all()
1012 player = DBSession.query(Player).filter_by(player_id=player_id).one()
1014 player_captimes = []
1016 player_captimes.append(PlayerCaptimes(
1017 fastest_cap=row.fastest_cap,
1018 create_dt=row.create_dt,
1019 create_dt_epoch=timegm(row.create_dt.timetuple()),
1020 create_dt_fuzzy=pretty_date(row.create_dt),
1021 player_id=row.player_id,
1022 game_id=row.game_id,
1024 map_name=row.map_name,
1025 server_id=row.server_id,
1026 server_name=row.server_name,
1030 'captimes':player_captimes,
1031 'player_id':player_id,
1032 'player_url':request.route_url('player_info', id=player_id),
1037 def player_captimes(request):
1038 return player_captimes_data(request)
1041 def player_captimes_json(request):
1042 return player_captimes_data(request)
1045 def player_weaponstats_data_json(request):
1046 player_id = request.matchdict["id"]
1050 game_type_cd = request.params.get("game_type", None)
1051 if game_type_cd == "overall":
1055 if request.params.has_key("limit"):
1056 limit = int(request.params["limit"])
1063 games_raw = DBSession.query(sa.distinct(Game.game_id)).\
1064 filter(Game.game_id == PlayerWeaponStat.game_id).\
1065 filter(PlayerWeaponStat.player_id == player_id)
1067 if game_type_cd is not None:
1068 games_raw = games_raw.filter(Game.game_type_cd == game_type_cd)
1070 games_raw = games_raw.order_by(Game.game_id.desc()).limit(limit).all()
1072 weapon_stats_raw = DBSession.query(PlayerWeaponStat).\
1073 filter(PlayerWeaponStat.player_id == player_id).\
1074 filter(PlayerWeaponStat.game_id.in_(games_raw)).all()
1076 # NVD3 expects data points for all weapons used across the
1077 # set of games *for each* point on the x axis. This means populating
1078 # zero-valued weapon stat entries for games where a weapon was not
1079 # used in that game, but was used in another game for the set
1080 games_to_weapons = {}
1083 for ws in weapon_stats_raw:
1084 if ws.game_id not in games_to_weapons:
1085 games_to_weapons[ws.game_id] = [ws.weapon_cd]
1087 games_to_weapons[ws.game_id].append(ws.weapon_cd)
1089 weapons_used[ws.weapon_cd] = weapons_used.get(ws.weapon_cd, 0) + 1
1090 sum_avgs[ws.weapon_cd] = sum_avgs.get(ws.weapon_cd, 0) + float(ws.hit)/float(ws.fired)
1092 for game_id in games_to_weapons.keys():
1093 for weapon_cd in set(weapons_used.keys()) - set(games_to_weapons[game_id]):
1094 weapon_stats_raw.append(PlayerWeaponStat(player_id=player_id,
1095 game_id=game_id, weapon_cd=weapon_cd))
1097 # averages for the weapons used in the range
1099 for w in weapons_used.keys():
1100 avgs[w] = round(sum_avgs[w]/float(weapons_used[w])*100, 2)
1102 weapon_stats_raw = sorted(weapon_stats_raw, key = lambda x: x.game_id)
1103 games = sorted(games_to_weapons.keys())
1104 weapon_stats = [ws.to_dict() for ws in weapon_stats_raw]
1107 "weapon_stats": weapon_stats,
1108 "weapons_used": weapons_used.keys(),