def to_team(row):
tpos = row.find(class_='playertablePlayerName').a.next_sibling
tpos = tpos.strip(' \r\n\t*,|').upper()
# This is a little weird because the team name seems to run
# in with the position. Perhaps a weird encoding quirk?
if len(tpos) < 2:
return 'UNK'
elif len(tpos) == 2:
return nfldb.standard_team(tpos)
else:
team = nfldb.standard_team(tpos[0:3])
if team == 'UNK':
team = nfldb.standard_team(tpos[0:2])
return team
def to_team(row):
tpos = row.find(class_='playertablePlayerName').a.next_sibling
tpos = tpos.strip(' \r\n\t*,|').upper()
# This is a little weird because the team name seems to run
# in with the position. Perhaps a weird encoding quirk?
if len(tpos) < 2:
return 'UNK'
elif len(tpos) == 2:
return nfldb.standard_team(tpos)
else:
team = nfldb.standard_team(tpos[0:3])
if team == 'UNK':
team = nfldb.standard_team(tpos[0:2])
return team
def schedule(bot, trigger):
season_type, season_year, current_week = nfldb.current(db)
if current_week is None:
bot.reply('not currently in season')
return
name = trigger.group(2)
team = nfldb.standard_team(name)
p = None
if team == 'UNK':
results = nfldb.player_search2(db, name, limit=1000)
if len(results) == 0:
bot.reply("No player or team matching that name could be found")
return
else:
p = results[0][0]
team = p.team
weeks = range(18)
q = nfldb.Query(db).game(season_type=season_type,
season_year=season_year,
week=weeks[current_week:current_week + 5],
team=team)
message = []
if p is not None:
message.append('Upcoming schedule for %s' % p)
else:
message.append('Upcoming schedule for %s' % team)
for g in q.sort(('week', 'asc')).as_games():
message.append(str(g))
say_multiline(bot, '\n'.join(message))
def schedule(bot, trigger):
season_type, season_year, current_week = nfldb.current(db)
if current_week is None:
bot.reply("not currently in season")
return
name = trigger.group(2)
team = nfldb.standard_team(name)
p = None
if team == "UNK":
results = nfldb.player_search2(db, name, limit=1000)
if len(results) == 0:
bot.reply("No player or team matching that name could be found")
return
else:
p = results[0][0]
team = p.team
weeks = range(18)
q = nfldb.Query(db).game(
season_type=season_type, season_year=season_year, week=weeks[current_week : current_week + 5], team=team
)
message = []
if p is not None:
message.append("Upcoming schedule for %s" % p)
else:
message.append("Upcoming schedule for %s" % team)
for g in q.sort(("week", "asc")).as_games():
message.append(str(g))
say_multiline(bot, "\n".join(message))
def rplayer(r, name, team, pos):
bench = pos == 'BN'
if name is None and team is None:
return r.new_player(pos, None, bench, None)
elif nfldb.standard_team(name) != 'UNK':
return r.new_player(pos, team, bench, None)
else:
player = player_search(name, team=team, position=pos)
return r.new_player(pos, team, bench, player.player_id)
def rplayer(r, name, team, pos):
bench = pos == 'BN'
if name is None and team is None:
return r.new_player(pos, None, bench, None)
elif nfldb.standard_team(name) != 'UNK':
return r.new_player(pos, team, bench, None)
else:
player = player_search(name, team=team, position=pos)
return r.new_player(pos, team, bench, player.player_id)
def gameforecast(bot, trigger):
""".gameforecast denver gives the forecast for the denver game this week"""
week = None
team = nfldb.standard_team(trigger.group(2))
if team == 'UNK':
bot.reply('I do not know that team')
return
season_type, season_year, current_week = nfldb.current(db)
if week is None:
if current_week is None:
bot.reply('Not currently in season')
return
week = current_week
q = nfldb.Query(db).game(season_type='Regular',
season_year=season_year,
week=week,
team=team)
games = q.as_games()
if len(games) == 0:
bot.reply('%s is on BYE' % team)
return
g = games[0]
start_time = g.start_time
stadium = stadiums[g.home_team]
lat, lon = stadium[2]
output = []
output.append('Kickoff forecast for %s at %s %s' %
(g.away_team, g.home_team,
g.start_time.strftime('%Y-%m-%d %I:%M:%S%p')))
if stadium[3] == False:
try:
forecast = forecastio.load_forecast(forecastio_api_key,
lat,
lon,
time=start_time,
units='us')
output.append(
u'%s %s\u00B0F windspeed %smph from the %s chance of precip %s%%'
% (forecast.currently().d['summary'],
forecast.currently().d['temperature'],
forecast.currently().d['windSpeed'],
windbearing(forecast.currently().d['windBearing']),
forecast.currently().d['precipProbability']))
except:
output.append('there was an error getting the forecast')
else:
output.append('Dome')
say_multiline(bot, '\n'.join(output))
def gameforecast(bot, trigger):
""".gameforecast denver gives the forecast for the denver game this week"""
week = None
team = nfldb.standard_team(trigger.group(2))
if team == "UNK":
bot.reply("I do not know that team")
return
season_type, season_year, current_week = nfldb.current(db)
if week is None:
if current_week is None:
bot.reply("Not currently in season")
return
week = current_week
q = nfldb.Query(db).game(season_type="Regular", season_year=season_year, week=week, team=team)
games = q.as_games()
if len(games) == 0:
bot.reply("%s is on BYE" % team)
return
g = games[0]
start_time = g.start_time
stadium = stadiums[g.home_team]
lat, lon = stadium[2]
output = []
output.append(
"Kickoff forecast for %s at %s %s" % (g.away_team, g.home_team, g.start_time.strftime("%Y-%m-%d %I:%M:%S%p"))
)
if stadium[3] == False:
try:
forecast = forecastio.load_forecast(forecastio_api_key, lat, lon, time=start_time, units="us")
output.append(
u"%s %s\u00B0F windspeed %smph from the %s chance of precip %s%%"
% (
forecast.currently().d["summary"],
forecast.currently().d["temperature"],
forecast.currently().d["windSpeed"],
windbearing(forecast.currently().d["windBearing"]),
forecast.currently().d["precipProbability"],
)
)
except:
output.append("there was an error getting the forecast")
else:
output.append("Dome")
say_multiline(bot, "\n".join(output))
def spread(bot, trigger):
vdb = vegasdb.VegasDb('vegas.db')
team = nfldb.standard_team(trigger.group(2))
if team == 'UNK':
bot.reply("No team matching that name could be found")
return
line = vdb.get_line(format_team(team))
if line is None:
bot.say('sorry i do not have a line for that game at this time')
ltz = reference.LocalTimezone()
d = line[0].astimezone(ltz)
if line[3] is None and line[4] is None and line[5] is None:
bot.say('sorry i do not have a line for that game at this time')
return
message = '%s (%0.1f) @ %s (%0.1f) %0.1fo/u %s' % (
line[1], line[3] if line[3] is not None else 0, line[2], line[4]
if line[4] is not None else 0, line[5] if line[5] is not None else 0,
d.strftime('%I:%M%p %A %b %d, %Y'))
bot.say(message)
def spread(bot, trigger):
vdb = vegasdb.VegasDb("vegas.db")
team = nfldb.standard_team(trigger.group(2))
if team == "UNK":
bot.reply("No team matching that name could be found")
return
line = vdb.get_line(format_team(team))
if line is None:
bot.say("sorry i do not have a line for that game at this time")
ltz = reference.LocalTimezone()
d = line[0].astimezone(ltz)
if line[3] is None and line[4] is None and line[5] is None:
bot.say("sorry i do not have a line for that game at this time")
return
message = "%s (%0.1f) @ %s (%0.1f) %0.1fo/u %s" % (
line[1],
line[3] if line[3] is not None else 0,
line[2],
line[4] if line[4] is not None else 0,
line[5] if line[5] is not None else 0,
d.strftime("%I:%M%p %A %b %d, %Y"),
)
bot.say(message)
def parse_upsert_xmls(xml_filenames, qb_stat_descs, stat_descs,
stat_with_dash_descs, rare_stat_descs,
rare_stat_with_dash_descs):
for xml_file in xml_filenames:
# raw game summary data
season_year, week, season_type, gamekey = xml_file.split(
'.xml')[0].split('-')
sys.stderr.write("{}-{}-{}-{}.xml\n".format(season_year, week,
season_type, gamekey))
season_type = short_to_long_stype(season_type)
dom = get_dom(gamebooks_path, xml_file)
gamebook_summary = dom.getElementsByTagName('GamebookSummary')[0]
schedule_date = get_xml_attribute(gamebook_summary, 'ScheduleDate')
home_team = get_xml_attribute(gamebook_summary, 'HomeTeam')
away_team = get_xml_attribute(gamebook_summary, 'VisitingTeam')
start_time = get_xml_attribute(gamebook_summary, 'StartTime')
time_zone = get_xml_attribute(gamebook_summary, 'TimeZone')
stadium = get_xml_attribute(gamebook_summary, 'Stadium')
stadium_type = get_xml_attribute(gamebook_summary, 'StadiumType')
game_weather = get_xml_attribute(gamebook_summary, 'GameWeather')
temp = get_xml_attribute(gamebook_summary, 'Temperature')
humidity = get_xml_attribute(gamebook_summary, 'Humidity')
windspeed = get_xml_attribute(gamebook_summary, 'WindSpeed')
turf_type = get_xml_attribute(gamebook_summary, 'TurfType')
outdoor_weather = get_xml_attribute(gamebook_summary, 'OutdoorWeather')
wind_chill = get_xml_attribute(gamebook_summary, 'WindChill')
wind_direction = get_xml_attribute(gamebook_summary, 'WindDirection')
referee = get_xml_attribute(gamebook_summary, 'Referee')
umpire = get_xml_attribute(gamebook_summary, 'Umpire')
head_linesman = get_xml_attribute(gamebook_summary, 'HeadLinesman')
line_judge = get_xml_attribute(gamebook_summary, 'LineJudge')
side_judge = get_xml_attribute(gamebook_summary, 'SideJudge')
back_judge = get_xml_attribute(gamebook_summary, 'BackJudge')
field_judge = get_xml_attribute(gamebook_summary, 'FieldJudge')
replay_official = get_xml_attribute(gamebook_summary, 'ReplayOfficial')
attendance = get_xml_attribute(gamebook_summary,
'Attendance').replace(',', '')
game_length = get_xml_attribute(gamebook_summary, 'GameLength')
visitor_score_q1 = get_xml_attribute(gamebook_summary,
'VisitorScoreQ1')
visitor_score_q2 = get_xml_attribute(gamebook_summary,
'VisitorScoreQ2')
visitor_score_q3 = get_xml_attribute(gamebook_summary,
'VisitorScoreQ3')
visitor_score_q4 = get_xml_attribute(gamebook_summary,
'VisitorScoreQ4')
visitor_score_ot = get_xml_attribute(gamebook_summary,
'VisitorScoreOT')
visitor_score = int(visitor_score_q1) + int(visitor_score_q2) + int(
visitor_score_q3) + int(visitor_score_q4) + int(visitor_score_ot)
home_score_q1 = get_xml_attribute(gamebook_summary, 'HomeScoreQ1')
home_score_q2 = get_xml_attribute(gamebook_summary, 'HomeScoreQ2')
home_score_q3 = get_xml_attribute(gamebook_summary, 'HomeScoreQ3')
home_score_q4 = get_xml_attribute(gamebook_summary, 'HomeScoreQ4')
home_score_ot = get_xml_attribute(gamebook_summary, 'HomeScoreOT')
home_score = int(home_score_q1) + int(home_score_q2) + int(
home_score_q3) + int(home_score_q4) + int(home_score_ot)
last_updated = get_xml_attribute(gamebook_summary, 'LastUpdated')
# raw roster data
offensive_starters_away = parse_players_from_xml(
dom, 'OffensiveStarterVisitor')
offensive_starters_home = parse_players_from_xml(
dom, 'OffensiveStarterHome')
defensive_starters_away = parse_players_from_xml(
dom, 'DefensiveStarterVisitor')
defensive_starters_home = parse_players_from_xml(
dom, 'DefensiveStarterHome')
subs_away = parse_players_from_xml(dom, 'SubstitutionsVisitor')
subs_home = parse_players_from_xml(dom, 'SubstitutionsHome')
did_not_play_away = parse_players_from_xml(dom, 'DidNotPlayVisitor')
did_not_play_home = parse_players_from_xml(dom, 'DidNotPlayHome')
not_active_away = parse_players_from_xml(dom, 'NotActiveVisitor')
not_active_home = parse_players_from_xml(dom, 'NotActiveHome')
# raw team statistics
all_team_stats_xml = dom.getElementsByTagName('TeamStatistics')
first_half_team_stats_xml = dom.getElementsByTagName(
'FirstHalfSummary')[0].getElementsByTagName('TeamStatistics')
# filter out first half stats to get just the full game team stats
game_team_stats_xml = []
for team_stat_xml in all_team_stats_xml:
if team_stat_xml not in first_half_team_stats_xml:
game_team_stats_xml.append(team_stat_xml)
home_team_stats = {}
away_team_stats = {}
for team_stat_xml in game_team_stats_xml:
# convert all descriptions to lowercase
team_stat_description = get_xml_attribute(team_stat_xml,
'Description').lower()
# edge case error, replace all double -- with single -
away_team_stats[team_stat_description] = re.sub(
'--', '-', get_xml_attribute(team_stat_xml, 'VisitorStats'))
home_team_stats[team_stat_description] = re.sub(
'--', '-', get_xml_attribute(team_stat_xml, 'HomeStats'))
# check for unknown stats
if team_stat_description not in stat_descs and \
team_stat_description not in stat_with_dash_descs and \
team_stat_description not in rare_stat_descs and \
team_stat_description not in rare_stat_with_dash_descs:
print "ERROR: Unknown team stat %s" % team_stat_description
# clean and standardize the raw game summary data
home_team = standard_team(home_team)
away_team = standard_team(away_team)
# some stadium values are empty, manually replace each one
if stadium == '':
stadium = edge_case_stadium(gamekey)
stadium = standard_stadium(stadium)
# split up the team stats with dash
away_team_stats['third downs converted'], away_team_stats[
'third downs'], away_team_stats[
'third down convert percent'] = re.sub(
'%', '',
away_team_stats['third down efficiency']).split('-')
home_team_stats['third downs converted'], home_team_stats[
'third downs'], home_team_stats[
'third down convert percent'] = re.sub(
'%', '',
home_team_stats['third down efficiency']).split('-')
away_team_stats['fourth downs converted'], away_team_stats[
'fourth downs'], away_team_stats[
'fourth down convert percent'] = re.sub(
'%', '',
away_team_stats['fourth down efficiency']).split('-')
home_team_stats['fourth downs converted'], home_team_stats[
'fourth downs'], home_team_stats[
'fourth down convert percent'] = re.sub(
'%', '',
home_team_stats['fourth down efficiency']).split('-')
away_team_stats['tackles for a loss'], away_team_stats[
'tackles for a loss yardage'] = away_team_stats[
'tackles for a loss-number and yards'].split('-')
home_team_stats['tackles for a loss'], home_team_stats[
'tackles for a loss yardage'] = home_team_stats[
'tackles for a loss-number and yards'].split('-')
away_team_stats['times thrown'], away_team_stats[
'yards lost attempting to pass'] = away_team_stats[
'times thrown - yards lost attempting to pass'].split('-')
home_team_stats['times thrown'], home_team_stats[
'yards lost attempting to pass'] = home_team_stats[
'times thrown - yards lost attempting to pass'].split('-')
away_team_stats['pass attempts'], away_team_stats[
'completions'], away_team_stats[
'had intercepted'] = away_team_stats[
'pass attempts-completions-had intercepted'].split('-')
home_team_stats['pass attempts'], home_team_stats[
'completions'], home_team_stats[
'had intercepted'] = home_team_stats[
'pass attempts-completions-had intercepted'].split('-')
away_team_stats['n kickoffs'], away_team_stats[
'n kickoffs in endzone'], away_team_stats[
'n kickoffs touchbacks'] = away_team_stats[
'kickoffs number-in end zone-touchbacks'].split('-')
home_team_stats['n kickoffs'], home_team_stats[
'n kickoffs in endzone'], home_team_stats[
'n kickoffs touchbacks'] = home_team_stats[
'kickoffs number-in end zone-touchbacks'].split('-')
away_team_stats['n punts'], away_team_stats[
'avg punt'] = away_team_stats['punts number and average'].split(
'-')
home_team_stats['n punts'], home_team_stats[
'avg punt'] = home_team_stats['punts number and average'].split(
'-')
away_team_stats['fgs had blocked'], away_team_stats[
'pats had blocked'] = away_team_stats[
'fgs - pats had blocked'].split('-')
home_team_stats['fgs had blocked'], home_team_stats[
'pats had blocked'] = home_team_stats[
'fgs - pats had blocked'].split('-')
away_team_stats['n punt returns'], away_team_stats[
'yards punt returns'] = away_team_stats[
'no. and yards punt returns'].split('-')
home_team_stats['n punt returns'], home_team_stats[
'yards punt returns'] = home_team_stats[
'no. and yards punt returns'].split('-')
away_team_stats['n kickoff returns'], away_team_stats[
'yards kickoff returns'] = away_team_stats[
'no. and yards kickoff returns'].split('-')
home_team_stats['n kickoff returns'], home_team_stats[
'yards kickoff returns'] = home_team_stats[
'no. and yards kickoff returns'].split('-')
away_team_stats['n interception returns'], away_team_stats[
'yards interception returns'] = away_team_stats[
'no. and yards interception returns'].split('-')
home_team_stats['n interception returns'], home_team_stats[
'yards interception returns'] = home_team_stats[
'no. and yards interception returns'].split('-')
away_team_stats['n penalties'], away_team_stats[
'penalty yards'] = away_team_stats[
'penalties number and yards'].split('-')
home_team_stats['n penalties'], home_team_stats[
'penalty yards'] = home_team_stats[
'penalties number and yards'].split('-')
away_team_stats['n fumbles'], away_team_stats[
'n fumbles lost'] = away_team_stats[
'fumbles number and lost'].split('-')
home_team_stats['n fumbles'], home_team_stats[
'n fumbles lost'] = home_team_stats[
'fumbles number and lost'].split('-')
away_team_stats['extra points made'], away_team_stats[
'extra points attempts'] = away_team_stats[
'extra points made-attempts'].split('-')
home_team_stats['extra points made'], home_team_stats[
'extra points attempts'] = home_team_stats[
'extra points made-attempts'].split('-')
away_team_stats['kicking made'], away_team_stats[
'kicking attempts'] = away_team_stats[
'kicking made-attempts'].split('-')
home_team_stats['kicking made'], home_team_stats[
'kicking attempts'] = home_team_stats[
'kicking made-attempts'].split('-')
away_team_stats['field goals made'], away_team_stats[
'field goals attempts'] = away_team_stats[
'field goals made-attempts'].split('-')
home_team_stats['field goals made'], home_team_stats[
'field goals attempts'] = home_team_stats[
'field goals made-attempts'].split('-')
away_team_stats['red zone converts'], away_team_stats[
'red zone attempts'], away_team_stats[
'red zone convert percentage'] = re.sub(
'%', '', away_team_stats['red zone efficiency']).split('-')
home_team_stats['red zone converts'], home_team_stats[
'red zone attempts'], home_team_stats[
'red zone convert percentage'] = re.sub(
'%', '', home_team_stats['red zone efficiency']).split('-')
away_team_stats['goal to go converts'], away_team_stats[
'goal to go attempts'], away_team_stats[
'goal to go convert percentage'] = re.sub(
'%', '',
away_team_stats['goal to go efficiency']).split('-')
home_team_stats['goal to go converts'], home_team_stats[
'goal to go attempts'], home_team_stats[
'goal to go convert percentage'] = re.sub(
'%', '',
home_team_stats['goal to go efficiency']).split('-')
'''
away_team_stats['time of possession minutes'], away_team_stats['time of possession seconds'] = away_team_stats['time of possession'].split(':')
home_team_stats['time of possession minutes'], home_team_stats['time of possession seconds'] = home_team_stats['time of possession'].split(':')
away_team_stats['time of possession decimal'] = str(round(float(away_team_stats['time of possession minutes']) + float(away_team_stats['time of possession seconds']) / 60.0, 2))
home_team_stats['time of possession decimal'] = str(round(float(home_team_stats['time of possession minutes']) + float(home_team_stats['time of possession seconds']) / 60.0, 2))
'''
# set rare team stats to zero if they don't exist
for rare_stat_desc in rare_stat_descs:
if rare_stat_desc not in away_team_stats:
away_team_stats[rare_stat_desc] = '0'
home_team_stats[rare_stat_desc] = '0'
# set rare team stats with dash to zero if they don't exist, fill them in otherwise
if 'rushing made-attempts' in away_team_stats:
away_team_stats['2pt conv rush made'] = away_team_stats[
'rushing made-attempts'].split('-')[0]
away_team_stats['2pt conv rush att'] = away_team_stats[
'rushing made-attempts'].split('-')[1]
home_team_stats['2pt conv rush made'] = home_team_stats[
'rushing made-attempts'].split('-')[0]
home_team_stats['2pt conv rush att'] = home_team_stats[
'rushing made-attempts'].split('-')[1]
else:
away_team_stats['2pt conv rush made'] = '0'
away_team_stats['2pt conv rush att'] = '0'
home_team_stats['2pt conv rush made'] = '0'
home_team_stats['2pt conv rush att'] = '0'
if 'passing made-attempts' in away_team_stats:
away_team_stats['2pt conv pass made'] = away_team_stats[
'passing made-attempts'].split('-')[0]
away_team_stats['2pt conv pass att'] = away_team_stats[
'passing made-attempts'].split('-')[1]
home_team_stats['2pt conv pass made'] = home_team_stats[
'passing made-attempts'].split('-')[0]
home_team_stats['2pt conv pass att'] = home_team_stats[
'passing made-attempts'].split('-')[1]
else:
away_team_stats['2pt conv pass made'] = '0'
away_team_stats['2pt conv pass att'] = '0'
home_team_stats['2pt conv pass made'] = '0'
home_team_stats['2pt conv pass att'] = '0'
# raw individual stats
individual_stats_dom = dom.getElementsByTagName(
'IndividualStatistics')[0]
# get starting qbs names
starting_qb_away_name = get_starting_position_player_name(
offensive_starters_away, 'QB')
starting_qb_home_name = get_starting_position_player_name(
offensive_starters_home, 'QB')
# get qb stats for away starter and for the game
away_passers_xml = individual_stats_dom.getElementsByTagName(
'PasserVisitor')
away_rushers_xml = individual_stats_dom.getElementsByTagName(
'RusherVisitor')
away_qb_stats = get_qb_stats(starting_qb_away_name, away_passers_xml,
away_rushers_xml)
away_total_qb_stats = get_qb_stats('Total', away_passers_xml,
away_rushers_xml)
# get qb stats for home starter and for the game
home_passers_xml = individual_stats_dom.getElementsByTagName(
'PasserHome')
home_rushers_xml = individual_stats_dom.getElementsByTagName(
'RusherHome')
home_qb_stats = get_qb_stats(starting_qb_home_name, home_passers_xml,
home_rushers_xml)
home_total_qb_stats = get_qb_stats('Total', home_passers_xml,
home_rushers_xml)
# get away interceptors stats
away_interceptors_xml = individual_stats_dom.getElementsByTagName(
'InterceptorVisitor')
away_interceptor_stats = get_interceptor_stats('Total',
away_interceptors_xml)
# get home interceptors stats
home_interceptors_xml = individual_stats_dom.getElementsByTagName(
'InterceptorHome')
home_interceptor_stats = get_interceptor_stats('Total',
home_interceptors_xml)
output = [
season_year, week, season_type, gamekey, away_team, home_team,
stadium, stadium_type, turf_type, schedule_date, start_time,
time_zone, game_weather, temp, humidity, windspeed,
outdoor_weather, wind_chill, wind_direction, referee, umpire,
head_linesman, line_judge, side_judge, back_judge, field_judge,
replay_official, attendance, game_length, visitor_score,
visitor_score_q1, visitor_score_q2, visitor_score_q3,
visitor_score_q4, visitor_score_ot, home_score, home_score_q1,
home_score_q2, home_score_q3, home_score_q4, home_score_ot,
last_updated
]
for qb_stat in qb_stat_descs:
output.append(away_qb_stats[qb_stat])
output.append(home_qb_stats[qb_stat])
for stat in stat_descs + rare_stat_descs:
output.append(away_team_stats[stat])
output.append(home_team_stats[stat])
output += [
away_team_stats['2pt conv rush made'],
away_team_stats['2pt conv rush att'],
away_team_stats['2pt conv pass made'],
away_team_stats['2pt conv pass att']
]
output += [
home_team_stats['2pt conv rush made'],
home_team_stats['2pt conv rush att'],
home_team_stats['2pt conv pass made'],
home_team_stats['2pt conv pass att']
]
# upsert gamebooks
upsert_gamebook(output)
# parse and upsert gamebook drives
away_drive_stats_dom = dom.getElementsByTagName('DriveVisitor')
home_drive_stats_dom = dom.getElementsByTagName('DriveHome')
away_drives_inserted = parse_and_upsert_drives(gamekey,
away_drive_stats_dom,
True, away_team,
home_team)
home_drives_inserted = parse_and_upsert_drives(gamekey,
home_drive_stats_dom,
False, away_team,
home_team)
def player_search2(db,
full_name,
team=None,
position=None,
limit=1,
soundex=False):
from nfldb.db import Tx
import nfldb.sql as sql
import nfldb.types as types
"""
Given a database handle and a player's full name, this function
searches the database for players with full names *similar* to the
one given. Similarity is measured by the
[Levenshtein distance](http://en.wikipedia.org/wiki/Levenshtein_distance),
or by [Soundex similarity](http://en.wikipedia.org/wiki/Soundex).
Results are returned as tuples. The first element is the is a
`nfldb.Player` object and the second element is the Levenshtein
(or Soundex) distance. When `limit` is `1` (the default), then the
return value is a tuple. When `limit` is more than `1`, then the
return value is a list of tuples.
If no results are found, then `(None, None)` is returned when
`limit == 1` or the empty list is returned when `limit > 1`.
If `team` is not `None`, then only players **currently** on the
team provided will be returned. Any players with an unknown team
are therefore omitted.
If `position` is not `None`, then only players **currently**
at that position will be returned. Any players with an unknown
position are therefore omitted.
In order to use this function, the PostgreSQL `levenshtein`
function must be available. If running this functions gives
you an error about "No function matches the given name and
argument types", then you can install the `levenshtein` function
into your database by running the SQL query `CREATE EXTENSION
fuzzystrmatch` as a superuser like `postgres`. For example:
#!bash
psql -U postgres -c 'CREATE EXTENSION fuzzystrmatch;' nfldb
Note that enabled the `fuzzystrmatch` extension also provides
functions for comparing using Soundex.
"""
assert isinstance(limit, int) and limit >= 1
if soundex:
# Careful, soundex distances are sorted in reverse of Levenshtein
# distances.
# Difference yields an integer in [0, 4].
# A 4 is an exact match.
fuzzy = 'difference(%s, %%s)'
q = '''
SELECT {columns}
FROM player
WHERE {where}
ORDER BY distance DESC LIMIT {limit}
'''
else:
fuzzy = 'levenshtein(LOWER(%s), %%s)'
q = '''
SELECT {columns}
FROM player
WHERE {where}
ORDER BY distance ASC LIMIT {limit}
'''
full_name = full_name.lower()
tokens = full_name.split(' ')
for token in tokens:
team = nfldb.standard_team(token)
if team != 'UNK':
tokens.remove(token)
full_name = ' '.join(tokens)
break
team = None
def get_results(fuzzy, q, name_type, name):
fuzzy = fuzzy % name_type
similar = 'LOWER(%s) LIKE %%s' % name_type
qteam, qposition = '', ''
results = []
with Tx(db) as cursor:
if team is not None:
qteam = cursor.mogrify('team = %s', (team, ))
if position is not None:
qposition = cursor.mogrify('position = %s', (position, ))
fuzzy_filled = cursor.mogrify(fuzzy, (name, ))
similar_filled = cursor.mogrify(similar, (name + '%', ))
columns = types.Player._sql_select_fields(
types.Player.sql_fields())
columns.append('%s AS distance' % fuzzy_filled)
q = q.format(columns=', '.join(columns),
where=sql.ands(similar_filled,
fuzzy_filled + ' IS NOT NULL',
'team != \'UNK\'', qteam, qposition),
limit=limit)
cursor.execute(q)
for row in cursor.fetchall():
results.append(
(types.Player.from_row_dict(db, row), row['distance']))
return results
if len(full_name.split(' ')) > 1:
first_name, last_name = full_name.split(' ')[:2]
results_first = get_results(fuzzy, q, 'first_name', first_name)
results_last = get_results(fuzzy, q, 'last_name', last_name)
results_dict = {}
for player, dist in results_last:
results_dict[str(player)] = dist
results_2nd_pass = {}
for player, dist in results_first:
if str(player) in results_dict:
results_2nd_pass[player] = (results_dict[str(player)], dist)
combined_results = results_2nd_pass.items()
combined_results = sorted(
combined_results,
cmp=lambda x, y: x[1][0] - y[1][0]
if x[1][0] - y[1][0] != 0 else x[1][1] - y[1][1])
results = combined_results
else:
results = get_results(fuzzy, q, 'last_name', full_name)
results.extend(get_results(fuzzy, q, 'first_name', full_name))
results = sorted(results, cmp=lambda x, y: x[1] - y[1])
if limit == 1:
if len(results) == 0:
return (None, None)
return results[0]
return results
def to_team(row):
team_pos = row.find(class_='ysf-player-name').span.text.strip()
return nfldb.standard_team(re.search('^\S+', team_pos).group(0))
def player_search2(db, full_name, team=None, position=None, limit=1, soundex=False):
from nfldb.db import Tx
import nfldb.sql as sql
import nfldb.types as types
"""
Given a database handle and a player's full name, this function
searches the database for players with full names *similar* to the
one given. Similarity is measured by the
[Levenshtein distance](http://en.wikipedia.org/wiki/Levenshtein_distance),
or by [Soundex similarity](http://en.wikipedia.org/wiki/Soundex).
Results are returned as tuples. The first element is the is a
`nfldb.Player` object and the second element is the Levenshtein
(or Soundex) distance. When `limit` is `1` (the default), then the
return value is a tuple. When `limit` is more than `1`, then the
return value is a list of tuples.
If no results are found, then `(None, None)` is returned when
`limit == 1` or the empty list is returned when `limit > 1`.
If `team` is not `None`, then only players **currently** on the
team provided will be returned. Any players with an unknown team
are therefore omitted.
If `position` is not `None`, then only players **currently**
at that position will be returned. Any players with an unknown
position are therefore omitted.
In order to use this function, the PostgreSQL `levenshtein`
function must be available. If running this functions gives
you an error about "No function matches the given name and
argument types", then you can install the `levenshtein` function
into your database by running the SQL query `CREATE EXTENSION
fuzzystrmatch` as a superuser like `postgres`. For example:
#!bash
psql -U postgres -c 'CREATE EXTENSION fuzzystrmatch;' nfldb
Note that enabled the `fuzzystrmatch` extension also provides
functions for comparing using Soundex.
"""
assert isinstance(limit, int) and limit >= 1
if soundex:
# Careful, soundex distances are sorted in reverse of Levenshtein
# distances.
# Difference yields an integer in [0, 4].
# A 4 is an exact match.
fuzzy = "difference(%s, %%s)"
q = """
SELECT {columns}
FROM player
WHERE {where}
ORDER BY distance DESC LIMIT {limit}
"""
else:
fuzzy = "levenshtein(LOWER(%s), %%s)"
q = """
SELECT {columns}
FROM player
WHERE {where}
ORDER BY distance ASC LIMIT {limit}
"""
full_name = full_name.lower()
tokens = full_name.split(" ")
for token in tokens:
team = nfldb.standard_team(token)
if team != "UNK":
tokens.remove(token)
full_name = " ".join(tokens)
break
team = None
def get_results(fuzzy, q, name_type, name):
fuzzy = fuzzy % name_type
similar = "LOWER(%s) LIKE %%s" % name_type
qteam, qposition = "", ""
results = []
with Tx(db) as cursor:
if team is not None:
qteam = cursor.mogrify("team = %s", (team,))
if position is not None:
qposition = cursor.mogrify("position = %s", (position,))
fuzzy_filled = cursor.mogrify(fuzzy, (name,))
similar_filled = cursor.mogrify(similar, (name + "%",))
columns = types.Player._sql_select_fields(types.Player.sql_fields())
columns.append("%s AS distance" % fuzzy_filled)
q = q.format(
columns=", ".join(columns),
where=sql.ands(similar_filled, fuzzy_filled + " IS NOT NULL", "team != 'UNK'", qteam, qposition),
limit=limit,
)
cursor.execute(q)
for row in cursor.fetchall():
results.append((types.Player.from_row_dict(db, row), row["distance"]))
return results
if len(full_name.split(" ")) > 1:
first_name, last_name = full_name.split(" ")[:2]
results_first = get_results(fuzzy, q, "first_name", first_name)
results_last = get_results(fuzzy, q, "last_name", last_name)
results_dict = {}
for player, dist in results_last:
results_dict[str(player)] = dist
results_2nd_pass = {}
for player, dist in results_first:
if str(player) in results_dict:
results_2nd_pass[player] = (results_dict[str(player)], dist)
combined_results = results_2nd_pass.items()
combined_results = sorted(
combined_results, cmp=lambda x, y: x[1][0] - y[1][0] if x[1][0] - y[1][0] != 0 else x[1][1] - y[1][1]
)
results = combined_results
else:
results = get_results(fuzzy, q, "last_name", full_name)
results.extend(get_results(fuzzy, q, "first_name", full_name))
results = sorted(results, cmp=lambda x, y: x[1] - y[1])
if limit == 1:
if len(results) == 0:
return (None, None)
return results[0]
return results
def _defense_lookup(d, conn):
t = standard_team(d)
if t != 'UNK':
return (t, t), False
else:
return _player_lookup(d, conn), True
def to_team(row):
team_pos = row.find(class_='ysf-player-name').span.text.strip()
return nfldb.standard_team(re.search('^\S+', team_pos).group(0))
