def get_draftkings_players(id):
csv_players = get_available_players(id)
draftable_players = draftables(id)["draftables"]
return list([
merge_draftking_players(draftable_players, player, id)
for index, player in csv_players.iterrows()
])
def update_nba_DK_slate():
if not contests_nba["contests"]:
return 0
# contests = contests(sport=Sport.NFL)
df = pd.DataFrame()
for label in contests_nba["contests"]:
if not str(label["starts_at"]).startswith(getdate()):
continue
# print(label["starts_at"])
id = label["draft_group_id"]
break
players = draftables(id)
playerName = [x['names']['display'] for x in players['draftables']]
sal = [x['salary'] for x in players['draftables']]
pos = [x['position'] for x in players['draftables']]
team = [x['team_abbreviation'] for x in players['draftables']]
opp = [x['competition']['name'] for x in players['draftables']]
index = 0
while index < len(playerName):
if index > 0 and playerName[index] == playerName[index-1]:
del playerName[index]
del sal[index]
del pos[index]
del team[index]
del opp[index]
else:
temp = opp[index].split()
if temp[0] == team[index]:
opp[index] = temp[-1]
else:
opp[index] = temp[0]
index+=1
df['playerName'] = playerName
df['sal'] = sal
df['pos'] = pos
df['team'] = team
df['opp'] = opp
df['proj'] = [0 for _ in range(len(playerName))]
df.to_csv('/home/ubuntu/gitrepositories/DailyFantasySports/DFOptimizerApp/app/src/main/python/slates/NBAslateDK.csv', index=False)
def update_mlb_DK_slate():
if not contests_mlb["contests"]:
return 0
# contests = contests(sport=Sport.NFL)
df = pd.DataFrame()
for label in contests_mlb["contests"]:
if not str(label["starts_at"]).startswith(getdate()):
continue
# print(label["starts_at"])
id = label["draft_group_id"]
break
players = draftables(id)
playerName = [x['names']['display'] for x in players['draftables']]
sal = [x['salary'] for x in players['draftables']]
pos = [x['position'] for x in players['draftables']]
team = [x['team_abbreviation'] for x in players['draftables']]
opp = [x['competition']['name'] for x in players['draftables']]
index = 0
while index < len(playerName):
if index > 0 and playerName[index] == playerName[index-1]:
del playerName[index]
del sal[index]
del pos[index]
del team[index]
del opp[index]
else:
temp = opp[index].split()
if temp[0] == team[index]:
opp[index] = temp[-1]
else:
opp[index] = temp[0]
index+=1
df['playerName'] = playerName
df['sal'] = sal
df['pos'] = pos
df['team'] = team
df['opp'] = opp
df['proj'] = [0 for _ in range(len(playerName))]
def test_get_draftables(self):
response = draftables(draft_group_id=18186)
self.assertIsNotNone(response)
def update_nfl_FD_slate():
if not contests_nfl["contests"]:
return 0
df = pd.DataFrame()
id = None
for label in contests_nfl["contests"]:
if not str(label["starts_at"]).startswith(changedate_nfl()):
continue
# print(label["starts_at"])
id = label["draft_group_id"]
break
if id is None:
return 0
players = draftables(id)
playerName = [x['names']['display'] for x in players['draftables']]
pos = [x['position'] for x in players['draftables']]
team = [x['team_abbreviation'] for x in players['draftables']]
opp = [x['competition']['name'] for x in players['draftables']]
index = 0
while index < len(playerName):
if index > 0 and playerName[index] == playerName[index - 1]:
del playerName[index]
del pos[index]
del team[index]
del opp[index]
else:
temp = opp[index].split()
if temp[0] == team[index]:
opp[index] = temp[-1]
else:
opp[index] = temp[0]
index += 1
df['playerName'] = playerName
df['sal'] = [0 for _ in range(len(playerName))]
df['pos'] = pos
df['team'] = team
df['opp'] = opp
df['proj'] = [0 for _ in range(len(playerName))]
sl = df
# set up some parameters for scrape
base_url = 'http://www.fantasypros.com/nfl/projections'
position_list = ['qb', 'rb', 'wr', 'te', 'k', 'dst']
frames = []
for position in position_list:
temp = position + '.php?scoring=PPR'
url = '%s/%s' % (base_url, temp)
response = requests.get(url)
# use expert:expert in request to get only one expert at a time
# use pandas to parse the HTML table for us
df = pd.io.html.read_html(response.text, attrs={'id': 'data'})[0]
# df['WEEK'] = current_week
# df['POSITION'] = position.upper()
df.rename(columns=COLUMN_MAPPINGS[position.upper()], inplace=True)
if position is not 'dst' and position is not 'k':
df.columns = ['{}'.format(x[1]) for x in df.columns]
# print(df.columns.values)
# print(df)
frames.append(df)
# msg = 'getting projections for {}, week {}, postition {}'
path = get_my_path()
path = functools.reduce(lambda x, f: f(x), [os.path.dirname] * 1, path)
# const_path = os.path.join(path, "NFLtemp.csv")
check = len(frames)
count = 0
for frame in frames:
count = count + 1
# print(frame)
for i in range(len(frame)):
if count < check:
name = frame.loc[i, "Player"]
name = name.rsplit(' ', 1)[0]
proj = frame.loc[i, "FPTS"]
# print(name, proj)
name = str(name)
proj = str(proj)
if (name == 'D.K. Metcalf'):
name = 'DK Metcalf'
if (name == 'Duke Johnson Jr.'):
name = 'Duke Johnson'
if (name == 'Wayne Gallman'):
name = 'Wayne Gallman Jr.'
if (name == 'D.J. Chark Jr.'):
name = 'DJ Chark Jr.'
if (name == 'Dwayne Haskins'):
name = 'Dwayne Haskins Jr.'
if (name == 'Darrell Henderson'):
name = 'Darrell Henderson Jr.'
sl.loc[sl['playerName'] == name, 'proj'] = proj
else:
name = frame.loc[i, "Player"]
words = name.split()
name = words[-1]
if name == 'Team':
name = 'Washington'
proj = frame.loc[i, "FPTS"]
name = name + ' '
name = str(name)
proj = str(proj)
# print(name, proj)
sl.loc[sl['playerName'] == name, 'proj'] = proj
# sl = pd.read_csv(const_path)
# set up some parameters for scrape
base_url = 'https://www.fantasypros.com/daily-fantasy/nfl/fanduel-salary-changes.php'
response = requests.get(base_url)
df = pd.io.html.read_html(response.text)[0]
# print(df)
# print(df[['Player','This Week']])
for i in range(len(df)):
name = df.loc[i, "Player"]
pos = name[-4:-1].strip()
if pos == 'DST':
name = name.split('(', 1)[0].strip()
words = name.split()
name = words[-1].strip()
name = name + ' '
if (name == 'Team '):
name = 'WAS Football Team '
else:
name = name.split('(', 1)[0].strip()
# Renames
if (name == 'D.K. Metcalf'):
name = 'DK Metcalf'
if (name == 'Duke Johnson Jr.'):
name = 'Duke Johnson'
if (name == 'Wayne Gallman'):
name = 'Wayne Gallman Jr.'
if (name == 'D.J. Chark Jr.'):
name = 'DJ Chark Jr.'
if (name == 'Dwayne Haskins'):
name = 'Dwayne Haskins Jr.'
if (name == 'Darrell Henderson'):
name = 'Darrell Henderson Jr.'
sal = df.loc[i, "This Week"]
sal = sal[1:]
sal = sal.replace(',', '')
# print(name, sal, pos)
sl.loc[sl['playerName'] == name, 'sal'] = sal
# print(sl.loc[sl['sal']==0])
path = get_my_path()
path = functools.reduce(lambda x, f: f(x), [os.path.dirname] * 1, path)
const_path = os.path.join(path, "NFLslateFD.csv")
sl.to_csv(const_path)
def test_nba_draftables(self):
draftables = client.draftables(draft_group_id=11513)
self.assertIsNotNone(draftables)
def test_euroleague_draftables(self):
draftables = client.draftables(draft_group_id=22916)
self.assertIsNotNone(draftables)
def test_soccer_epl_draftables(self):
draftables = client.draftables(draft_group_id=22831)
self.assertIsNotNone(draftables)
def test_soccer_uefa_national_league_draftables(self):
draftables = client.draftables(draft_group_id=22855)
self.assertIsNotNone(draftables)
def test_cbb_draftables(self):
draftables = client.draftables(draft_group_id=22958)
self.assertIsNotNone(draftables)
def test_nfl_draftables(self):
draftables = client.draftables(draft_group_id=22927)
self.assertIsNotNone(draftables)
# # return 0
# contests = contests(sport=Sport.NFL)
df = pd.DataFrame()
id = None
for label in contests_nfl["contests"]:
if not str(label["starts_at"]).startswith(changedate_nfl()):
continue
# print(label["starts_at"])
id = label["draft_group_id"]
break
#
# if id is None:
# return 0
players = draftables(id)
playerName = [x['names']['display'] for x in players['draftables']]
sal = [x['salary'] for x in players['draftables']]
pos = [x['position'] for x in players['draftables']]
team = [x['team_abbreviation'] for x in players['draftables']]
opp = [x['competition']['name'] for x in players['draftables']]
print(playerName)
index = 0
while index < len(playerName):
if index > 0 and playerName[index] == playerName[index - 1]:
del playerName[index]
del sal[index]
del pos[index]
del team[index]
