def GetPlayersFromJSON(players_dict, exposure_all):
players = []
in_players = []
ex_players = []
for p in players_dict:
player = Player(
p['ID'],
p['PLAYER'],
p['PLAYER'],
[p['POS']],
p['TEAM'],
float(p['SAL']),
float(p['FPTS']),
projected_ownership=float(p['TM/P']))
players.append(player)
max_exp = int(p['max'])
min_exp = int(p['min'])
if exposure_all['max_all'] != '':
max_exp = min(int(exposure_all['max_all']), int(p['max']))
if exposure_all['min_all'] != '':
min_exp = max(int(exposure_all['min_all']), int(p['min']))
if max_exp < 100:
player.max_exposure = float(max_exp) / 100
if min_exp > 0:
player.min_exposure = float(min_exp) / 100
if p['inc_exc_state'] == 1:
in_players.append(player)
elif p['inc_exc_state'] == 2:
ex_players.append(player)
return [players, in_players, ex_players]
def transform_player(player, gameType):
return Player(
player["id"], player["firstName"], player["lastName"],
player["draftPositions"].split("/") if gameType
and 'Showdown' in gameType else player["position"].split("/"),
player["team"], float(player["salary"]), float(player["fppg"]),
player.get("status") == "O", None, player.get("minExposure"),
player.get("projectedOwnership"))
def test_adding_player_to_formed_position(self):
self.lineup_optimizer.reset_lineup()
players = []
for i in '1234':
players.append(Player(int(i), i, i, ['PG'], 'DEN', 10, 2))
for i in range(3):
self.lineup_optimizer.add_player_to_lineup(players[i])
with self.assertRaises(LineupOptimizerException):
self.lineup_optimizer.add_player_to_lineup(players[3])
def test_remove_player_from_lineup(self):
optimizer = self.lineup_optimizer
player = Player('1', 'P', 'P', ['PG'], 'DEN', 10, 2)
optimizer.extend_players([player])
optimizer.add_player_to_lineup(player)
optimizer.remove_player_from_lineup(player)
self.assertNotIn(player, optimizer.locked_players)
with self.assertRaises(LineupOptimizerException):
optimizer.remove_player_from_lineup(player)
def test_remove_player_from_lineup(self):
pool = self.player_pool
player = Player('1', 'P', 'P', ['PG'], 'DEN', 10, 2)
pool.extend_players([player])
pool.lock_player(player)
pool.unlock_player(player)
self.assertNotIn(player, pool.locked_players)
with self.assertRaises(LineupOptimizerException):
pool.unlock_player(player)
def GetPlayersFromFile(timestamp):
page = open(os.path.dirname(os.path.abspath(__file__)) + '/' + timestamp + '_players.json', 'r').read()
data = json.loads(page)
players_dict = data['players']
players = []
for p in players_dict:
player = Player(
p['ID'],
p['PLAYER'],
p['PLAYER'],
[p['POS']],
p['TEAM'],
float(p['SAL']),
float(p['FPTS']))
players.append(player)
if int(p['max']) < 100:
player.max_exposure = float(p['max']) / 100
if int(p['min']) > 0:
player.min_exposure = float(p['min']) / 100
return players
def setUpClass(cls):
optimizer = get_optimizer(Site.YAHOO, Sport.BASKETBALL)
cls.players = [
Player('1', 'First Name 1', 'Last Name 1', ['PG'], 'Team1', 20, 20),
Player('2', 'First Name 2', 'Last Name 2', ['SG'], 'Team2', 20, 20),
Player('3', 'First Name 3', 'Last Name 3', ['SF'], 'Team3', 20, 20),
Player('4', 'First Name 4', 'Last Name 4', ['PF'], 'Team4', 20, 20),
Player('5', 'First Name 5', 'Last Name 5', ['C'], 'Team5', 20, 20),
Player('6', 'First Name 6', 'Last Name 6', ['PG', 'SG'], 'Team6', 20, 20),
Player('7', 'First Name 7', 'Last Name 7', ['SF', 'PF'], 'Team7', 20, 20),
Player('8', 'First Name 8', 'Last Name 8', ['PG', 'SG', 'SF'], 'Team8', 20, 20),
]
optimizer.load_players(cls.players)
cls.lineups = list(optimizer.optimize(1))
def GetTestPlayersFromPyDFS():
url = "https://raw.githubusercontent.com/DimaKudosh/pydfs-lineup-optimizer/master/tests/players.json"
page = urlopen(url).read()
players_dict = json.loads(page)['players']
players = [Player(
p['id'],
p['first_name'],
p['last_name'],
p['positions'],
p['team'],
p['salary'],
p['fppg']
) for i, p in enumerate(players_dict)]
return players
def test_lineup_with_max_players(self):
self.lineup_optimizer.reset_lineup()
players = [
Player(1, 'P1', 'P1', ['PG'], 'DEN', 10, 2),
Player(5, 'P5', 'P5', ['SG'], 'DEN', 10, 2),
Player(2, 'P2', 'P2', ['SF'], 'DEN', 10, 2),
Player(6, 'P6', 'P6', ['PF'], 'DEN', 10, 2),
Player(3, 'P3', 'P3', ['C'], 'DEN', 10, 2),
Player(7, 'P7', 'P7', ['PG'], 'DEN', 10, 2),
Player(4, 'P4', 'P4', ['PF'], 'DEN', 10, 2),
Player(8, 'P8', 'P8', ['PG'], 'DEN', 10, 2)
]
self.lineup_optimizer.extend_players(players)
for player in players:
self.lineup_optimizer.add_player_to_lineup(player)
gen = self.lineup_optimizer.optimize(10)
self.assertEqual(len(list(gen)), 1)
def transform_player(player):
player = Player(
player[0],
player[1],
player[2],
player[3].split("/"),
player[4],
player[5],
player[6],
# True if player["status"] == "O" else False,
player[7] if player[7] != "O" else None,
# False
)
return player
def nba_to_pydfs(players):
'''
Takes results, make ready to create Player objects for pydfs_lineup_optimizer
Args:
players (list): day's worth of stats
Returns:
players (list): list of players, fixed for use in pydfs_lineup_optimizer
'''
return [
Player(p['nbacom_player_id'], p['first_name'], p['last_name'],
p.get('dfs_position').split('/'), p.get('team_code'),
float(p.get('salary', 100000)), float(p.get('dk_points', 0)))
for p in players
]
def preprocess_fantasylabs(players):
# id, first_name, last_name, positions, team, salary, fppg, is_injured=False):
pydfs_players = []
for p in players:
parts = p.get('Player_Name', '').split(' ')
if parts and len(parts) == 2:
first_name, last_name = parts
else:
first_name = p.get('Player_Name')
last_name = ''
positions = [p.get('Position')]
salary = float(p.get('Salary', 0))
fppg = float(p.get('AvgPts', 0))
pydfs_players.append(
Player('', first_name, last_name, positions, '', salary, fppg))
return pydfs_players
def GetPlayersFromRotoWire(site):
url_dk = "https://www.rotowire.com/daily/tables/optimizer-nfl.php?sport=NFL&site=DraftKings&projections=&type=main&slate=all&ownership="
url_fd = "https://www.rotowire.com/daily/tables/optimizer-nfl.php?sport=NFL&site=FanDuel&projections=&type=main&slate=Main&ownership="
url_yh = "https://www.rotowire.com/daily/tables/optimizer-nfl.php?sport=NFL&site=Yahoo&projections=&type=main&slate=all&ownership="
url = url_fd
# if site == 'DraftKings':
# url = url_dk
# elif site == 'Yahoo':
# url = url_yh
page = urlopen(url).read()
players_dict = json.loads(page)
players = [Player(
p['id'],
p['first_name'],
p['last_name'],
[p['position']],
p['team'],
float(p['salary']),
float(p['proj_points'])
) for i, p in enumerate(players_dict)]
return players
def test_adding_player_with_salary_bigger_than_budget(self):
self.lineup_optimizer.reset_lineup()
player = Player(1, '1', '1', ['PG'], 'DEN', 100000, 2)
with self.assertRaises(LineupOptimizerException):
self.lineup_optimizer.add_player_to_lineup(player)
if player.player:
if player.player.name == "{} {}".format(
data['first_name'], data['last_name']):
pts = base_fantasy_points(player)
data['last_pts'] = pts
try:
data['last_proj'] = last_df[last_df.Name == "{} {}".format(
data['first_name'], data['last_name'])].Projected.values[0]
except:
data['last_proj'] = 0
df = json_normalize(data)
main_df = main_df.append(df, ignore_index=True, sort=False)
try:
player_list.append(
Player(int(player_dict['id']), str(data['first_name']),
str(data['last_name']), data['position'].split("/"),
data['team'], data['salary_dk'],
float(data['projected'])))
except Exception as e:
continue
print("[*] Calculating percent change from last week.")
main_df['pct_change'] = (main_df.last_pts -
main_df.last_proj) / main_df.last_proj * 100
print("[*] Generating optimal lineups")
optimizer.load_players(player_list)
player = optimizer.get_player_by_name('Garoppolo')
optimizer.add_player_to_lineup(player)
for lineup in optimizer.optimize(n=5):
print(lineup)
def test_adding_player_with_salary_bigger_than_budget(self):
player = Player('1', '1', '1', ['PG'], 'DEN', 100000, 2)
with self.assertRaises(LineupOptimizerException):
self.player_pool.lock_player(player)