from app.sites import Site, Scraper
from app.utils import make_request, strip, TableParser
from data.data import nhl
def betdsi_nhl_extractor(page):
tp = TableParser()
tp.feed(strip(page))
tables = tp.get_tables()
# Get rid of garbage rows
tables = [t for t in tables if len(t) == 2]
# Find team names and moneylines
pairs = []
for table in tables:
name1 = table[0][1].strip()
name2 = table[1][0]
moneyline1 = table[0][-1].strip()
moneyline2 = table[1][-1].strip()
pairs.append(((name1, moneyline1), (name2, moneyline2)))
return pairs
betdsi = Site("betdsi.eu", {})
betdsi.scrapers[nhl] = Scraper(url="http://www.betdsi.eu/hockey-betting",
fetch_fn=make_request,
extract_fn=betdsi_nhl_extractor)
tp.feed(page)
tables = tp.get_tables()
# Get rid of garbage lines in the table
tables = tables[0][1:]
# Find team names and moneylines
pairs = []
for i in range(len(tables)/2):
name1 = tables[i*2][2].strip().split(" ")
name1 = name1[0] if len(name1) == 1 else " ".join(name1[1:])
name2 = tables[i*2+1][1].strip().split(" ")
name2 = name2[0] if len(name2) == 1 else " ".join(name2[1:])
moneyline1 = str(tables[i*2][-1]).strip()
moneyline2 = str(tables[i*2+1][-1]).strip()
if moneyline1 == '0' or moneyline2 == '0':
continue
pairs.append(((name1, moneyline1), (name2, moneyline2)))
return pairs
mybookie = Site("mybookie.ag", {})
mybookie.scrapers[nhl] = Scraper(
url="http://mybookie.ag/sportsbook/nhl-betting-lines/",
fetch_fn=make_request,
extract_fn=mybookie_nhl_extractor)
from app.sites import Site, Scraper
from app.utils import make_request, strip, TableParser
from data.data import nhl
def bodog_nhl_extractor(page):
tp = TableParser()
tp.feed(strip(page))
tables = tp.get_tables()
# Get rid of garbage rows
rows = [r for t in tables for r in t if len(r) > 3][1:]
# Find team names and moneylines
pairs = []
for i in range(len(rows)/2):
name1 = rows[i*2][2].strip()
name2 = rows[i*2+1][1].strip()
moneyline1 = rows[i*2][4].strip()
moneyline2 = rows[i*2+1][3].strip()
pairs.append(((name1, moneyline1), (name2, moneyline2)))
return pairs
bodog = Site("sports.bodog.eu", {})
bodog.scrapers[nhl] = Scraper(
url="http://sports.bodog.eu/sports-betting/nhl-hockey-lines.jsp",
fetch_fn=make_request,
extract_fn=bodog_nhl_extractor)
from app.utils import make_request, strip, TableParser
from data.data import nhl
def bovada_nhl_extractor(page):
tp = TableParser()
tp.feed(strip(page))
tables = tp.get_tables()
# Get rid of garbage lines in the table
tables = tables[1:]
for i, t in enumerate(tables):
tables[i] = max(t, key=lambda x: len(x))
# Find the team names and moneylines
pairs = []
for i in range(len(tables) / 2):
name1 = tables[i * 2][2].strip()
name2 = tables[i * 2 + 1][1].strip()
moneyline1 = tables[i * 2][4].strip()
moneyline2 = tables[i * 2 + 1][3].strip()
pairs.append(((name1, moneyline1), (name2, moneyline2)))
return pairs
bovada = Site("bovada.lv", {})
bovada.scrapers[nhl] = Scraper(
url="http://sports.bovada.lv/sports-betting/nhl-hockey-lines.jsp",
fetch_fn=make_request,
extract_fn=bovada_nhl_extractor)
import re
from app.sites import Site, Scraper
from app.utils import make_request
from data.data import nhl
def sportsbook_nhl_extractor(page):
page_stripped = re.sub("\t|\r\n|\n", "", page)
teams = re.findall('<span class="team" .+?>(.+?)</span>', page_stripped)
moneylines = re.findall(' ate="ML[AH]"><div class="market">' + "(.+?)</div></a>", page_stripped)
if len(teams) != len(moneylines):
return []
pairs = [
((teams[i * 2], moneylines[i * 2]), (teams[i * 2 + 1], moneylines[i * 2 + 1])) for i in range(len(teams) / 2)
]
return pairs
sportsbook = Site("sportsbook.ag", {})
sportsbook.scrapers[nhl] = Scraper(
url="https://www.sportsbook.ag/sbk/sportsbook4/" + "nhl-betting/nhl-game-lines.sbk",
fetch_fn=make_request,
extract_fn=sportsbook_nhl_extractor,
)
from app.sites import Site, Scraper
from app.utils import make_request, TableParser
from data.data import nhl
def topbet_nhl_extractor(page):
tp = TableParser()
tp.feed(page)
tables = tp.get_tables()
# Get rid of garbage tables
tables = [t for t in tables if len(t) == 3 and t[0][0] == t[0][1] == 0]
# Find team names and moneylines
pairs = []
for table in tables:
name1 = table[1][1].strip()
name2 = table[2][1].strip()
moneyline1 = table[1][5].strip()
moneyline2 = table[2][5].strip()
pairs.append(((name1, moneyline1), (name2, moneyline2)))
return pairs
topbet = Site("topbet.eu", {})
topbet.scrapers[nhl] = Scraper(
url="http://topbet.eu/sportsbook/nhl",
fetch_fn=make_request,
extract_fn=topbet_nhl_extractor)
import re
from app.sites import Site, Scraper
from app.utils import make_request
from data.data import nhl
def sportsbook_nhl_extractor(page):
page_stripped = re.sub("\t|\r\n|\n", "", page)
teams = re.findall("<span class=\"team\" .+?>(.+?)</span>", page_stripped)
moneylines = re.findall(
" ate=\"ML[AH]\"><div class=\"market\">" + "(.+?)</div></a>",
page_stripped)
if len(teams) != len(moneylines):
return []
pairs = [((teams[i * 2], moneylines[i * 2]), (teams[i * 2 + 1],
moneylines[i * 2 + 1]))
for i in range(len(teams) / 2)]
return pairs
sportsbook = Site("sportsbook.ag", {})
sportsbook.scrapers[nhl] = Scraper(
url="https://www.sportsbook.ag/sbk/sportsbook4/" +
"nhl-betting/nhl-game-lines.sbk",
fetch_fn=make_request,
extract_fn=sportsbook_nhl_extractor)
finally:
driver.close()
return source
def sportsbetting_nhl_extractor(page):
tp = TableParser()
tp.feed(page)
tables = tp.get_tables()
# Clean up tables
tables = tables[3][2:]
tables = [r for r in tables if len(r) > 20]
# Extract names/lines
pairs = []
for i in range(len(tables) / 2):
name1 = tables[i * 2][2].strip()
name2 = tables[i * 2 + 1][1].strip()
moneyline1 = str(tables[i * 2][9]).strip()
moneyline2 = str(tables[i * 2 + 1][8]).strip()
pairs.append(((name1, moneyline1), (name2, moneyline2)))
return pairs
sportsbetting = Site("sportsbetting.ag", {})
sportsbetting.scrapers[nhl] = Scraper(
url="http://www.sportsbetting.ag/sportsbook",
fetch_fn=sportsbetting_nhl_fetcher,
extract_fn=sportsbetting_nhl_extractor)
from app.sites import Site, Scraper
from app.utils import make_request, strip, TableParser
from data.data import nhl
def betdsi_nhl_extractor(page):
tp = TableParser()
tp.feed(strip(page))
tables = tp.get_tables()
# Get rid of garbage rows
tables = [t for t in tables if len(t) == 2]
# Find team names and moneylines
pairs = []
for table in tables:
name1 = table[0][1].strip()
name2 = table[1][0]
moneyline1 = table[0][-1].strip()
moneyline2 = table[1][-1].strip()
pairs.append(((name1, moneyline1), (name2, moneyline2)))
return pairs
betdsi = Site("betdsi.eu", {})
betdsi.scrapers[nhl] = Scraper(
url="http://www.betdsi.eu/hockey-betting",
fetch_fn=make_request,
extract_fn=betdsi_nhl_extractor)
finally:
driver.close()
return source
def sportsbetting_nhl_extractor(page):
tp = TableParser()
tp.feed(page)
tables = tp.get_tables()
# Clean up tables
tables = tables[3][2:]
tables = [r for r in tables if len(r) > 20]
# Extract names/lines
pairs = []
for i in range(len(tables)/2):
name1 = tables[i*2][2].strip()
name2 = tables[i*2+1][1].strip()
moneyline1 = str(tables[i*2][9]).strip()
moneyline2 = str(tables[i*2+1][8]).strip()
pairs.append(((name1, moneyline1), (name2, moneyline2)))
return pairs
sportsbetting = Site("sportsbetting.ag", {})
sportsbetting.scrapers[nhl] = Scraper(
url="http://www.sportsbetting.ag/sportsbook",
fetch_fn=sportsbetting_nhl_fetcher,
extract_fn=sportsbetting_nhl_extractor)
from app.sites import Site, Scraper
from app.utils import make_request
from data.data import nhl
def sportsinteraction_nhl_extractor(page):
# pull rows with regular moneylines out of page
page_stripped = re.sub("\t|\r\n|\n", "", page)
row_pattern = "<span class=\"name\">(.+?)</span>" + \
"<span class=\"handicap\">(.+?)</span>" + \
"<span class=\"price\">(.+?)</span>"
rows = re.findall(row_pattern, page_stripped)
moneyline_rows = [(r[0], r[2]) for r in rows if r[1].strip() == " "]
# Find team names and moneylines
pairs = []
for i in range(len(moneyline_rows) / 2):
name1 = moneyline_rows[i * 2][0].strip()
name2 = moneyline_rows[i * 2 + 1][0].strip()
moneyline1 = moneyline_rows[i * 2][1].strip()
moneyline2 = moneyline_rows[i * 2 + 1][1].strip()
pairs.append(((name1, moneyline1), (name2, moneyline2)))
return pairs
sportsinteraction = Site("sportsinteraction.com", {})
sportsinteraction.scrapers[nhl] = Scraper(
url="http://www.sportsinteraction.com/hockey/nhl-betting-lines/",
fetch_fn=make_request,
extract_fn=sportsinteraction_nhl_extractor)
