Python nfldb.connect函数代码示例

def week_choices(request):
    response_data = week_choices_dict()
    db = nfldb.connect()
    current_week = nfldb.current(db)
    response_data['current_year'] = current_week[1]
    response_data['current_week'] = current_week[2]
    return HttpResponse(json.dumps(response_data), content_type="application/json")

def showStatDefense(team_input, week_input):
	statJSON = {}
	#STAT_STRING_LIST_DEFENSE=['defense_sk', 'defense_int', 'defense_frec', 'defense_safe', 'defense_frec_tds', 'defense_int_tds', 'defense_misc_tds', 'kickret_tds']
	stat_string_list = STAT_STRING_LIST_DEFENSE	
	stat_season_totals =  [0 for x in range(len(stat_string_list))]
	#stat_string_list = ['puntret_tds']	
	db = nfldb.connect()
	q = nfldb.Query(db)
	q.game(season_year=2012, season_type='Regular',  week=week_input, team=team_input)
		
	for p in q.as_games():				
		if p.away_team == team_input:
			statJSON['points_allowed']= p.home_score
		else:
			statJSON['points_allowed']= p.away_score
	
	#check for bye week all stats = 0
	if len(q.as_games())==0:
		team_home_away = 'bye'
		for index in xrange(len(stat_string_list)):
			statJSON[stat_string_list[index]] = 0
		return statJSON
	
	for index in xrange(len(stat_string_list)):
			stat = showStat(stat_string_list[index], team_input, week_input)
			statJSON[stat_string_list[index]] = stat
			#stat_season_totals[index] +=stat	
	
	statJSON['defense_touchdowns'] = statJSON['defense_int_tds'] + statJSON['defense_frec_tds'] + statJSON['defense_misc_tds']
	#	for key, index in statJSON.items():	
		#print ("Totals Week: " +str(week_input) + " " + team_input + " " + key+ " "+ str(index) + '\n')	
	return statJSON

 def playerstats(self, **kwargs):
     player = kwargs['player']
     db = nfldb.connect()
     q = nfldb.Query(db)
     q.game(season_year=kwargs['season'], season_type='Regular')
     if kwargs['targtype'] == "non-redzone":
         pos1 = nfldb.FieldPosition.from_str('OWN 1')
         pos2 = nfldb.FieldPosition.from_str('OPP 21')
     #OPP 20 to OPP 10 yardline
     elif kwargs['targtype'] == 'redzone':
         pos1 = nfldb.FieldPosition.from_str('OPP 20')
         pos2 = nfldb.FieldPosition.from_str('OPP 11')
     #OPP 10 to OPP 6
     elif kwargs['targtype'] == 'goaline1':
         pos1 = nfldb.FieldPosition.from_str('OPP 10')
         pos2 = nfldb.FieldPosition.from_str('OPP 6')
     # OPP 5 to OPP 3
     elif kwargs['targtype'] == 'goaline2':
         pos1 = nfldb.FieldPosition.from_str('OPP 5')
         pos2 = nfldb.FieldPosition.from_str('OPP 3')
     #OPP 2 or OPP 1
     elif kwargs['targtype'] == 'goaline3':
         pos1 = nfldb.FieldPosition.from_str('OPP 2')
         pos2 = nfldb.FieldPosition.from_str('OPP 1')
     
     q.play(yardline__ge=pos1)
     q.play(yardline__le=pos2)
     q.player(full_name= player)
     for pp in q.as_aggregate():
         return pp

def showPlayerStat(player_ID, week_input):
	statJSON={}	
	stat_string_list = STAT_STRING_LIST
	
	db = nfldb.connect()
	q = nfldb.Query(db)
		
	q.game(season_year=2012, season_type='Regular',  week=week_input)	
	q.player(player_id=player_ID)
	
	# for p in q.sort([('gsis_id', 'asc'), ('time', 'asc')]).as_plays():
		# print p	
	
	for p in q.as_aggregate():
		
		for index in xrange(len(stat_string_list)):
			key = stat_string_list[index]
			value = eval('p.'+stat_string_list[index])
			statJSON[key]=value
			#print key, value
	#Check for empty week stat due to BYE week
	if len(q.as_aggregate() )==0:
		for index in xrange(len(stat_string_list)):
			key = stat_string_list[index]			
			statJSON[key]=0	
	return statJSON

def getOpponent(team_input, week_input):
	statJSON = {}
	STAT_STRING_OPPONENT = ['passing_yds', 'passing_tds',  'rushing_yds','receiving_yds', 'receiving_tds' ,'kickret_tds', 'fumbles_rec_tds','rushing_tds']	
	stat_string_list = STAT_STRING_OPPONENT
	stat_season_totals =  [0 for x in range(len(stat_string_list))]
	#stat_string_list = ['puntret_tds']	
	db = nfldb.connect()
	q = nfldb.Query(db)
	q.game(season_year=2012, season_type='Regular',  week=week_input, team=team_input)

	#check for bye week all stats = 0
	if len(q.as_games())==0:
		team_home_away = 'bye'
		statJSON['opponent']= 'bye'
		for index in xrange(len(stat_string_list)):
			statJSON[stat_string_list[index]+'_allowed'] = 0		
		return statJSON
	
	for p in q.as_games():				
		if p.away_team == team_input:
			opponent = p.home_team
		else:
			opponent = p.away_team
		statJSON['opponent'] = opponent
		#print "Team: ", team_input, " has Opponent: ", opponent
	
	q.game(season_year=2012, season_type='Regular',  week=week_input, team=opponent)	
	for p in q.as_games():					
		for index in xrange(len(stat_string_list)):
				stat = showStat(stat_string_list[index], opponent, week_input)
				statJSON[stat_string_list[index]+'_allowed'] = stat
				stat_season_totals[index] +=stat	
	
	#print statJSON
	return statJSON

def makeWinMatrix(players):

    db = nfldb.connect()

    # Get number of players in list
    size = len(players)
    playerInd = {}

    ind = 0

    print '\n index\tname'
    for x in players:
        x = x.split(' (')
        print str(ind) + '\t' + x[0]

        qd = nfldb.Query(db)
        qd.game(season_year=2015, season_type='Regular')
        pp = qd.player(full_name=x[0]).as_aggregate()
        for x in pp:
            playerInd[ind] = x
        ind += 1

    xcord = 0

    allWins = []
    allLoses = []
    while xcord < size - 1:
        winsList = []
        losesList = []
        check = playerInd[xcord]
        loses = 0
        ycord = 0
        while ycord < size - 1:
            losesList.append(0)
            if ycord != xcord:
                against = playerInd[ycord]
                wins, loses = calcWins(check, against, loses)
                winsList.append(wins)
            else:
                winsList.append(0)

            ycord += 1
        losesList[xcord] = loses
        rowWins = numpy.array([winsList])
        rowLoses = numpy.array([losesList])

        allWins.append(rowWins)
        allLoses.append(rowLoses)

        xcord += 1

    matrixWins = numpy.vstack(allWins)
    matrixLoses = numpy.vstack(allLoses)
    print '---------- Wins ----------'
    print(matrixWins)
    print '---------- Loses ----------'
    print(matrixLoses)

    return matrixWins, matrixLoses

 def games_played(self,player,year):
     db = nfldb.connect()
     q = nfldb.Query(db)
     q.game(season_year=year, season_type='Regular',)
     q.player(full_name=player)
     if q.as_games() != None:
         return len(q.as_games())
     else:
         return 0

    def __init__(self, name, seasonyear):
        self.__name = name
        self.__seasonYear = seasonyear
        __nfldbConnect = nfldb.connect()

        q = nfldb.Query(__nfldbConnect).game(season_year=self.__seasonYear, season_type='Regular')
        for pp in q.as_aggregate():
            print pp.player
        return

 def __init__(self, name = "Team", short_name = "UNK", year = 2009):
     self.name = name
     self.short_name = short_name
     self.possession = False
     self.year = year
     self.db = nfl.connect()
     self.q = nfl.Query(self.db)
     self.q.player(team=short_name)
     self.roster = self.q.as_aggregate()
     print self.name

 def testCheck(self):
     return
     db = nfldb.connect()
     calc = Trade.Calculator(PURE)
     q = nfldb.Query(db)
     q.game(season_year=2009, season_type='Regular')
     rushers = q.sort('rushing_yds').limit(100).as_aggregate()
     receivers = q.sort('receiving_yds').limit(100).as_aggregate()
     passers = q.sort('passing_yds').limit(35).as_aggregate()
     players = Trade.aggpps_to_players(rushers + receivers + passers)
     for rec,yds in calc.sort_position_more(players, 'TE'):
         print "{} {}".format(rec,yds)

    def query_players_by_year(self, year):
        db = nfldb.connect()
        q = nfldb.Query(db)
        q.game(season_year=year, season_type='Regular')

        # Only retrieving a limited amount to avoid more manual position tagging
        rushers = q.sort('rushing_yds').limit(100).as_aggregate()
        receivers = q.sort('receiving_yds').limit(100).as_aggregate()
        passers = q.sort('passing_yds').limit(35).as_aggregate()

        players = self.aggpps_to_players(rushers + receivers + passers)
        return players

def get_weeklypts(team, week, year):
    players = []
    db = nfldb.connect()
    q = nfldb.Query(db)
    q.game(season_year=year, season_type='Regular', team=team, week=week )
    for p in q.as_players():
        if p.team == team and p.team != "UNK":  
            pts = get_weeklypoints(year,p.full_name, week)
            if pts != 0:
                players.append((p.full_name,str(p.position),str(p.team), week, pts)) 
                
    return players

def module1():

	db = nfldb.connect()
	q = nfldb.Query(db)
	q.game(season_year=2013, season_type='Regular')
	
	for pp in q.sort('passing_yds').limit(10).as_aggregate():
		print pp.player, pp.passing_yds
	
	q.player(full_name="Tom Brady").play(passing_tds=1)	
	for play in q.as_plays():
		print play

def nfldb(year = 2013):
    import nfldb
    db = nfldb.connect()
    q = nfldb.Query(db)

    q.game(season_year=year, season_type='Regular')
    for pp in q.sort('passing_yds').limit(15).as_aggregate():
        print pp.player, pp.passing_yds, pp.rushing_tds

    print "\n"

    for pp in q.sort('rushing_yds').limit(15).as_aggregate():
        print pp.player, pp.rushing_yds, pp.rushing_tds

def index(request, year=0, week=0, season_type='Regular'):
    db = nfldb.connect()
    current = nfldb.current(db)
    if year == 0:
        season_type, year, week = nfldb.current(db)
        return redirect('index', year, season_type.name, week)
    q = nfldb.Query(db).game(
        season_year=year,
        season_type=season_type,
        week=week).sort('start_time')
    games = q.as_games()
    return render(request, 'games/index.html',
                  {'games_list': games, 'current': current, 'year': year})