def get_table_data(self):
self.data = []
etree = self.tree.xpath(
'//div[@data-type="league-table-container"]/div[@data-type="table"]/div[@data-type="table-row"]'
)
for element in etree:
name = sc.get_text(element.xpath('./div[@class="team"]/text()'))
place = sc.get_text(
element.xpath('.//span[@data-type="rank"]/text()'))
played = sc.get_text(
element.xpath('.//div[@data-type="played"]/text()'))
wins = sc.get_text(
element.xpath('.//div[@data-type="wins"]/text()'))
draws = sc.get_text(
element.xpath('./div[@data-type="draws"]/text()'))
losses = sc.get_text(
element.xpath('./div[@data-type="losses"]/text()'))
scored = sc.get_text(
element.xpath('./div[@data-type="goals-scored"]/text()'))
received = sc.get_text(
element.xpath('./div[@data-type="goals-received"]/text()'))
difference = sc.get_text(
element.xpath('./div[@data-type="goal-difference"]/text()'))
points = sc.get_text(
element.xpath('./div[@data-type="points"]/text()'))
print(name, place, played, wins, draws, losses, scored, received,
difference, points)
self.data.append([
name, place, played, wins, draws, losses, scored, received,
difference, points
])
sc.Database(('name', 'place', 'played', 'wins', 'draws', 'losses',
'scored', 'received', 'difference', 'points'),
'table.db').database(self.data)
def collect_info(product_url):
product_html = scraper.content(product_url)
info = {
'name':
scraper.get_text(product_html, 'div#variant-info h1').pop(),
'sku':
scraper.get_text(product_html, 'div.commerce-product-sku span').pop(),
'price':
scraper.get_text(product_html, 'p.field-type-commerce-price').pop()
}
return info
def get_data(self):
for number in range(1, 17):
self.source = requests.get(self.url + str(number) + '/')
self.tree = lxml.html.fromstring(self.source.content)
self.etree = self.tree.xpath(
'//div[@id="departement-content"]/a[@class]')
for element in self.etree:
self.location = sc.get_text(
element.xpath('./span[@class="ville"]/text()'))
self.name = sc.get_text(
element.xpath('./span[@class="nom"]/text()'))
self.description = sc.get_text(
element.xpath('./span[@class="intitule"]/text()'))
self.data.append([self.location, self.name, self.description])
sc.Database(('location', 'name', 'description')).push_data(self.data)
def get_data(self):
for number in range(1, 247):
print(number)
self.url = self.get_url(number)
self.source = requests.get(self.url)
self.etree = lxml.html.fromstring(self.source.content)
self.tree = self.etree.xpath('//div[@id="listingsResults"]//tr[not(@id)]')
for element in self.tree:
self.job = sc.get_href(element.xpath('.//div[@class="listing-title"]/a[@href]'))
self.location = sc.get_text(element.xpath('.//div[@class="left-side"]/span[1]/following-sibling::span[1]/text()'))
self.posted = sc.get_text(element.xpath('.//div[@class="left-side"]/span[2]/following-sibling::span[2]/text()'))
self.link = sc.get_href(element.xpath('.//div[@class="left-side"]/span[3]/following-sibling::span[3]/a[@href]'))
self.company = sc.get_text(element.xpath('.//div[@class="left-side"]/span[3]/following-sibling::span[3]//text()'))
self.data.append([self.job, self.location, self.posted, self.link, self.company])
sc.Database(('job', 'location', 'posted', 'link', 'company')).push_data(self.data)
def get_matches_data(self):
self.data = []
mount = int(
self.tree.xpath(
'count(//div[@data-type="container"]/div[@data-type="evt"])'))
for i in range(1, mount + 1):
element = self.tree.xpath(
'//div[@data-type="container"]//div[@data-type="evt"][' +
str(i) + ']')[0]
date = sc.get_text(
element.xpath(
'.//preceding::div[@class="right fs11"][1]/text()'))
time = sc.get_text(
element.xpath('.//div[@class="min "]/span/text()'))
home_name = sc.get_text(
element.xpath('.//div[@class="ply tright name"]/span/text()'))
away_name = sc.get_text(
element.xpath('.//div[@class="ply name"]/span/text()'))
score_home = sc.get_text(
element.xpath('.//span[@class="hom"]/text()'))
score_away = sc.get_text(
element.xpath('.//span[@class="awy"]/text()'))
print(date, time, home_name, score_home, score_away, away_name)
self.data.append(
[date, time, home_name, score_home, away_name, score_away])
sc.Database(('data', 'time', 'home_name', 'score_home', 'away_name',
'score_away'), 'matches.db').database(self.data)
def write(Bing_Results, Google_Results, Queries, n):
results = open('results2.txt', 'a')
results.write('Query Kendall Jaccard B_Sub B_Pol B_pos B_neg B_Class G_Sub G_Pol G_pos G_neg G_Class\n')
kd, jc = 0, 0
bs, bp, bpos, bneg, bcl = 0, 0, 0, 0, 0
gs, gp, gpos, gneg, gcl = 0, 0, 0, 0, 0
# Missed: 13, 14, 15, 16, 17, 18, 19
for query in Queries[42:50]:
query = query[:-1]
curr_kd = kendall.Kendall(Bing_Results[query], Google_Results[query])
curr_jc = jaccard.Jaccard(Bing_Results[query], Google_Results[query])
curr_bs = subjectivity.Subjectivity([scraper.get_text(x) for x in Bing_Results[query]])
curr_gs = subjectivity.Subjectivity([scraper.get_text(x) for x in Google_Results[query]])
print(query)
kd += curr_kd
jc += curr_jc
bs += curr_bs[0]
bp += curr_bs[1]
bpos += curr_bs[2]
bneg += curr_bs[3]
bcl += 1 if curr_bs[4] == 'pos' else 0
gs += curr_gs[0]
gp += curr_gs[1]
gpos += curr_gs[2]
gneg += curr_gs[3]
gcl += 1 if curr_gs[4] == 'pos' else 0
msg = (query + ' ' + str(round(curr_kd, 4)) + ' ' + str(round(curr_jc, 4)) + ' '
+ str(round(curr_bs[0], 4)) + ' ' + str(round(curr_bs[1], 4)) + ' ' + str(round(curr_bs[2], 4))
+ ' ' + str(round(curr_bs[3], 4)) + ' ' + str(curr_bs[4]) + ' '
+ str(round(curr_gs[0], 4)) + ' ' + str(round(curr_gs[1], 4)) + ' ' + str(round(curr_gs[2], 4))
+ ' ' + str(round(curr_gs[3], 4)) + ' ' + str(curr_gs[4]) + '\n')
results.write(msg)
msg = (f'Average {round(kd/n, 4)} {round(jc/n, 4)} {round(bs/n, 4)} {round(bp/n, 4)} {round(bpos/n, 4)} {round(bneg/n, 4)}'
+ f' {round(bcl/n, 4)} {round(gs/n, 4)} {round(gp/n, 4)} {round(gpos/n, 4)} {round(gneg/n, 4)} {round(gcl/n, 4)}')
results.write(msg)
def get_data(self, words):
words = words.split('\n')
for word in words:
self.data[word] = []
try:
self.source = requests.get(self.url+word)
except requests.exceptions.ConnectionError:
FindWords.create_connection_error_label()
self.tree = lxml.html.fromstring(self.source.content)
for option in self.options:
self.etree = self.tree.xpath(option)
for element in self.etree:
self.translation = sc.get_text(element.xpath('./text()'))
self.data[word].append(self.translation)
def is_url_relevant(url):
"""Check if a url is relevant
This function will check if a url is classified as relevant and
if it has relevent keyword.
"""
driver = create_driver()
driver.get(url)
print("Checking:", url)
urltext = scraper.get_text(driver.page_source)
value = classifier.predict([urltext])
keyword_relevance = isKeywordPresent(urltext)
relevant = value and keyword_relevance
print("Relavent: ", relevant)
return relevant
def get_data(self):
self.etree = self.tree.xpath(
'//table[@class="table"]//tr[following-sibling::tr]')
self.name = sc.get_text(
self.tree.xpath(
'//div[@class="row bottom-margin-1x"][1]/div[1]/h1/text()[4]'))
for element in self.etree:
self.date = sc.get_text(element.xpath('./td[1]/text()'))
self.open = sc.get_text(element.xpath('./td[2]/text()'))
self.high = sc.get_text(element.xpath('./td[3]/text()'))
self.low = sc.get_text(element.xpath('./td[4]/text()'))
self.close = sc.get_text(element.xpath('./td[5]/text()'))
self.volume = sc.get_text(element.xpath('./td[6]/text()'))
self.market_cap = sc.get_text(element.xpath('./td[7]/text()'))
self.list = [
self.date, self.open, self.high, self.low, self.close,
self.volume, self.market_cap
]
self.data.append(self.list)
sc.Database(
('date', 'open', 'high', 'low', 'close', 'volume', 'market_cap'),
file_name=self.name + '.db').push_data(self.data)
def calc_key_count(url):
"""Count key terms in url
This function will count the number of key terms for each url by analyzing its web page content.
"""
lem = WordNetLemmatizer()
driver = create_driver()
driver.get(url)
keywords = keywordFetcher.fetchKeyTerms()
urltext = scraper.get_text(driver.page_source)
urltext = urltext.split()
urltext = [lem.lemmatize(plural).lower() for plural in urltext]
key_count = 0
for i in range(len(keywords)):
key_count += urltext.count(keywords[i])
print(key_count)
return key_count