def caronaInfo(self):
resp = requests.get('https://www.worldometers.info/coronavirus/')
values = {
'world': 'N/A',
'india': 'N/A',
'deathCases': 'N/A',
'recCases': 'N/A',
'newCases': 'N/A',
'totalDeath': 'N/A',
'totalRec': 'N/A'
}
sel = Selector(resp)
soup = BeautifulSoup(sel.get(), "html.parser")
world = soup.find(id="main_table_countries_today").find(
"td", string="World").parent.td.next_sibling.next_sibling.string
india = soup.find(id="main_table_countries_today").find(
"a",
string="India").parent.parent.td.next_sibling.next_sibling.string
deathCases = soup.find(id="main_table_countries_today").find(
"a", string="India"
).parent.parent.td.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.string
recCases = soup.find(id="main_table_countries_today").find(
"a", string="India"
).parent.parent.td.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.next_sibling.string
newCases = soup.find(id="main_table_countries_today").find(
"a", string="India"
).parent.parent.td.next_sibling.next_sibling.next_sibling.next_sibling.string
totalDeath = soup.find_all(id="maincounter-wrap")[1].span.string
totalRec = soup.find_all(id="maincounter-wrap")[2].span.string
values.update({"world": world})
values.update({"totalDeath": totalDeath})
values.update({"totalRec": totalRec})
values.update({"india": india})
values.update({"deathCases": deathCases})
values.update({"recCases": recCases})
values.update({"newCases": newCases})
return values
def parse(self, response):
"""
abstract method from Spider object overwritten in script - see documentation
:param response: callback of request to handle generated responses
:return:
"""
# inspect_response(response, self)
es = ElementSelectors()
item_batch = response.css(es.sale_items_batch).getall()
# batch_len = len(item_batch)
# batch_sel = Selector(text=item_batch[71])
# print("DEBUG1: {}".format(batch_sel.get()))
dict_items_num = {}
dict_items_name = {}
for _ in range(len(item_batch)):
dict_item_info = {}
item_link = Selector(text=item_batch[_]).css('body >' +
es.item_link)
item_link_elem = item_link.get()
item_link_sel = Selector(text=item_link_elem)
dict_item_info['item_link'] = item_link.attrib['href']
dict_item_info['item_old_price'] = item_link_sel.css(
es.item_old_cost).get()
dict_item_info['item_sale_price'] = item_link_sel.css(
es.item_current_cost).get()
dict_items_num[_] = dict_item_info
for _ in range(len(dict_items_num.keys())):
print("ITEM {}: {} {} {} ".format(
_, dict_items_num[_]['item_link'],
dict_items_num[_]['item_old_price'],
dict_items_num[_]['item_sale_price']))
def parse(self, response):
# Find out post number (id)
try:
match = re.search(r't=(\d*)', response.url)
post_number = match.group(1)
except Exception as e:
print(response.url)
print(e)
folder_path = "download/" + str(post_number)
# Keep track of all the visited pages
if (post_number not in visited):
visited[post_number] = {
"comments": [],
"n_pages": 0
}
not_found = Selector(response).xpath("//table[@class='forumline']//td[@class='row1']/table/tr[2]/td/span[@class='gen']").extract()
if len(not_found) > 0:
print("ERROR PAGE")
return
# Create folder if doesn't exist
try:
if not os.path.isdir(folder_path):
os.mkdir(folder_path)
except Exception as e:
print(e)
# Save page N of the current post id
with open(folder_path + "/" + str(visited[post_number]['n_pages']) + ".html", "wb") as f:
f.write(response.body)
# Start scrapping of data
row = Selector(response).xpath("//table[@class ='forumline']/tr").extract()
title = Selector(response).xpath("///a[@class ='maintitle']/text()").get()
next_page = Selector(response).xpath("//span[@class='nav']//a[contains(text(),'Next')]/@href")
for item in row[2:]:
author_1 = Selector(text=item).xpath("//td[1]//b/span/text()").get()
author_2 = Selector(text=item).xpath("//td[1]//b/text()").get()
author = author_1 if author_1 is not None else author_2
if author:
date_text = Selector(text=item).xpath("//td[2]/table//span[@class='postdetails']/text()").get().replace("Posted: ", "").strip()
comment_content = Selector(text=item).xpath("//td[2]/table/tr[3]/td").get()
visited[post_number]['comments'].append(Comment(author, dateparser.parse(date_text), comment_content))
# If has more comment pages, queue them up to be visited
if(len(next_page) > 0):
visited[post_number]['n_pages'] += 1
next_page_url = BASE_URL + next_page.get()
yield scrapy.Request(next_page_url, callback=self.parse)
# For the last page, store the accumulated json in a file and delete the content of comments to not clog RAM
else:
post = visited[post_number]['comments'][0]
new_post = Post(post_number, title, post.author, post.content, post.date, visited[post_number]['comments'][1:])
with open(folder_path + "/items.json", "w") as f:
f.write(json.dumps(new_post.toJson()))
del visited[post_number]['comments']
