def serializar_ocorrencias(lista_urls, palavra):
#Armazenara o array de todas as ocorrencias de cada link
ocorrencias = []
#Para cada link na lista sera feito o bloco de codigo
for link in lista_urls:
#formatando a pagina para html
pag_url = str(uReq(link).read())
pag_soup = soup(pag_url, "html.parser")
#qtd de paragrafos <p> no html
ct = paragrafos(pag_soup,palavra)
#cria um dicionario com o link e a quantidade de ocorrencias
ocorrencia = {"url":link, "qtd_de_ocorrencias": str(ct)}
#adiciona o dicionario a lista de ocorrencias
ocorrencias.append(ocorrencia)
#printando no console a troca da url
print("*************************************************************************")
#retornando o array de dicionarios serializado no formato json
#return json.dumps(ocorrencias, indent=4)
return ocorrencias
def crawl(href,count):
print(get_time() + ", Parsing Link: " + href)
req = Request(href, headers={'User-Agent': 'Mozilla/5.0'})
uClient = uReq(req)
page_html = uClient.read()
uClient.close()
page_soup = soup(page_html, "html.parser")
heading = page_soup.find('center')
content_container = page_soup.find('table', attrs={'style' : "background:transparent; text-align:justify;"}).prettify()
table = soup(content_container,"html.parser")
para = table.find_all('p')
#name = str(count)+".html"
with io.open("para_hn.html", "a", encoding="utf-8") as fout:
#fout.write("\n\n" + heading.text + "\n\n")
# for i in para:
#print(para[i])
fout.write(str(para))
link = page_soup.find('img', attrs={'alt' : 'Next.png'})
next_link = link.findPrevious('a')['href']
complete_link = "http://hi.krishnakosh.org" + quote(next_link, safe='%,/')
return complete_link
# -*- coding: utf-8 -*-
import bs4
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
my_url = 'https://www.newegg.com/Desktop-Graphics-Cards/SubCategory/ID-48'
#grabs my URL in a variable. Opens a client then closes it to not keep using resources
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
#Holds my HTML parsing
page_soup = soup(page_html, "html.parser").encode("utf-8")
#Grabs each product. Used for Graphics Card atm.
containers = page_soup.findAll("div",{"class":"item-container"})
#Export into a CSV file now.
filename = "GraphicsCards.csv"
f = open(filename, "w")
headers = "brand, product_name, shipping \n"
f.write(headers)
# Goes through the whole page, grabbing certain things i'm looking for.
# TO DO:
# ADD IMAGE RECOGNITION FOR TITLE OF PRODUCT
# ADD IN REVIEWED ONLY DEVICES FOR THIS ONE
for container in containers:
brand = container.div.div.a.img["title"]
# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as uReq
#Steam URL... self explainitory
STEAM_URL = 'https://store.steampowered.com/search/?os=win&specials=1&page='
CONTAINERS = []
#Grab, and hold all the selected pages for steam special sales
for i in range(10):
print ("grabbing page #" + str(i+1))
uClient = uReq(STEAM_URL + str(i+1))
page_html = uClient.read()
uClient.close()
parsed_html = soup(page_html, "html.parser")
containers = CONTAINERS + parsed_html.findAll("div", {"class":"responsive_search_name_combined"})
filename = "SteamSpecialSale.csv"
f = open(filename, "w")
headers = "Game_Title, Original_Price, Sale_Price \n"
f.write(headers)
#Go through a whole page, looping through all entries needed.
#then write them into CSV.
for container in containers:
game_title = container.findAll("span", {"class":"title"})[0].text.strip()
game_price = container.findAll("div", {"class":"search_price"})[0].text.strip()
original_price = game_price[:game_price.rfind("$")].strip()
# downloads the MTG json database to a sister directory.
print("Calling function download_json_db()...\n")
# this function requires....
# from io import BytesIO
# import zipfile
# from urllib.request import urlopen as uReq
# import os
# fields
host_url = 'https://mtgjson.com/json/AllCards.json.zip'
internal_filename = 'AllCards.json'
# downloads the file
print("Downloading JSON library from mtgjson.com...")
client = uReq(host_url)
zip_byte_file = client.read()
client.close()
print("Download... Done!\n")
# Extract the file
print("Extracting zip folder....")
zip_folder = zipfile.ZipFile(BytesIO(zip_byte_file))
json_file = zip_folder.read(internal_filename)
# Converts to JSON
json_file = json_file.decode("utf-8")
json_file = json.loads(json_file)
json_file = json.dumps(json_file)
print("Extraction... Complete!\n")
# )
# ################# insert to DB code ############################
print("Scrapping data from: Zappa.co.il")
myurl = "https://www.zappa-club.co.il/content/the-show-must-go-on/"
#Write path depending if on Linux Azure VM or Win laptop
if path.exists("C:/Users/omerm/Desktop/Hackorona/Data-Scrapping"):
the_path = "C:/Users/omerm/Desktop/Hackorona/Data-Scrapping"
else:
the_path = "/root/bin/datascrape"
#Grapping page
req = Request(myurl, headers={'User-Agent': 'Mozilla/5.0'})
uClient = uReq(req)
page_html = uClient.read()
uClient.close()
#parses the info
page_soup = soup(page_html, "html.parser")
#create csv file
filename = the_path + "/data/Zappa.csv"
with open(filename, "w", encoding="utf=16") as f:
#csv headers
headers = "Date., Time., Title., Caterogies., Url\n"
f.write(headers)
### URL ###
from urllib.request import Request, urlopen as uReq
from bs4 import BeautifulSoup as soup
req = Request(
'https://freelancehunt.com/projects/skill/parsing-dannyih/169.html?page=1',
headers={'User-Agent': 'Mozilla/5.0'})
response = uReq(req)
page_html = response.read()
response.close()
page_soup = soup(page_html, 'html.parser')
tr_list = page_soup.findAll('tr', {'style': 'vertical-align: top'})
td_list = page_soup.findAll('td', {'class': 'text-center'})
titles = []
for tr in tr_list:
title = tr.td.a.text
titles.append(title)
price_list = []
for td in td_list:
remainder = td_list.index(td) % 4
if remainder == 0:
price_list.append(td.span.text.strip())
def final(titles, prices):
x = 0
lines = []
def redesextract():
from settings import my_url, name, doc, last, RH, COD_PRODUCTO
import init, bs4, logging, sys, re
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
global contredes
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
auto = ""
vincula = ""
insti = ""
vinculain = ""
page_soup = soup(page_html, "html.parser")
containers = page_soup.findAll("table")
for a in range(0, len(containers)):
buscaReds = containers[a].h3
#print(buscaReds)
try:
if buscaReds.text == "Redes de conocimiento especializado":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("blockquote")
for x in range(0, len(container)):
cont = container[x]
info_red = cont.text
#Nombre de la red
index1 = info_red.find("Nombre de la red ") + 17
index2 = info_red.find(
"\xa0\r\n Tipo de red")
Nombrered = info_red[index1:index2]
# Tipo de Red
index1 = info_red.find("Tipo de red") + 11
index2 = info_red.find(
",\xa0\r\n Creada el:")
Tipored = info_red[index1:index2]
# Lugar Red
index1 = info_red.find(
"\xa0\r\n en ") + 42
index2 = info_red.find(" \xa0 \r\n")
LugarRed = info_red[index1:index2]
#Fecha de Realización inicio y fin
index1 = info_red.find("Creada el:") + 10
index2 = index1 + 4
AnoRedini = info_red[index1:index2]
if AnoRedini == "," or AnoRedini == ",\xa0\r\n":
MesRedini = ""
AnoRedini = ""
FechaRedini = ""
MesRedfin = ""
AnoRedfin = ""
FechaRedfin = ""
else:
index1 = index1 + 5
index2 = index1 + 2
MesRedini = info_red[index1:index2]
index1 = info_red.find("Creada el:") + 10
index2 = index1 + 10
FechaRedini = info_red[index1:index2]
index1 = info_red.find(",", index1, index1 + 58) + 40
index2 = index1 + 4
AnoRedfin = info_red[index1:index2]
if AnoRedfin == " " or AnoRedfin == ",":
MesRedfin = ""
AnoRedfin = ""
FechaRedfin = ""
else:
index1 = index1 + 5
index2 = index1 + 2
MesRedfin = info_red[index1:index2]
index1 = info_red.find("Creada el:") + 10
index1 = info_red.find(",", index1, index1 + 58) + 40
index2 = index1 + 10
FechaRedfin = info_red[index1:index2]
init.rel_persona_producto_colciencias.append(str(RH) + ";"\
+ str(COD_PRODUCTO) + ";"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',"1".replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',Nombrered.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "0" + ","\
+ "" + ";"\
+ "" + ";"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',LugarRed.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "" + ";"\
+ "\n")
init.inrel_personas_producto_colciencias.append( \
"REPLACE INTO `uapa_db`.`rel_personas_producto_colciencias`(`cod_rel_per_prod_col`,`cod_producto`,`cod_rh`,`cod_tipo_producto`,`nombre_producto`,`evento_asociado`,`datos_complementarios`,`lugar`,`ano`,`ambito`,`palabras_clave`,`areas`,`sectores`,`coautores`,`vincula_coautores`,`editorial`,`volumen`,`paginas`,`doi`,`finalidad`,`instituciones_asociadas`,`tipo_vinculacion_institucion`) VALUES"
+ "('"+ str(RH) + str(COD_PRODUCTO) + "',"
+ str(COD_PRODUCTO) + ","\
+ "'" + str(RH) + "',"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',"7".replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',Nombrered.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "null" + ","\
+ "null" + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',LugarRed.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ");\n")
init.colciencias_apropiacion.append(str(RH) + str(COD_PRODUCTO) + ";"\
+ str(RH) + ";"\
+ str(COD_PRODUCTO) + ";"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaRedini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoRedini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',MesRedini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaRedfin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoRedfin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',MesRedfin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "\n")
init.incolciencias_apropiacion.append( \
"REPLACE INTO `uapa_db`.`colciencias_apropiacion`(`cod_colciencias_apropiacion`,`cod_rh`,`cod_rel_per_prod_col`,`fecha_ini`,`fecha_fin`,`cod_tipo_evento`) VALUES"
+ "('" + str(COD_PRODUCTO) + "',"\
+ "'" + str(RH) + "',"\
+ "'" + str(RH) + str(COD_PRODUCTO) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaRedini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaRedfin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "0" + ");\n")
COD_PRODUCTO = COD_PRODUCTO + 1
else:
logging.info(' El Docente ' + name + ' ' + last +
' no tiene Redes Asociadas')
contredes = [COD_PRODUCTO]
def main():
database = r"C:\Users\Kenny\Documents\webscrape\Phish.db"
#create a database connection
conn = create_connection(database)
with conn:
cur = conn.cursor()
#These are the variables responsible for tracking ID in each respective table.
songCount = 1
venueCount = 1
showCount = 1
setCount = 0
setlistEntryCount = 1
#Set-up with the first URL
url = "https://phish.net/setlists/phish-december-02-1983-harris-millis-cafeteria-university-of-vermont-burlington-vt-usa.html"
while (url !=
"https://phish.net/setlist/jump/next?showdate=2020-02-23"):
uClient = uReq(url)
page_html = uClient.read()
uClient.close()
#Hold the parsed-HTML in a BeautifulSoup data structure
page_soup = soup(page_html, "html.parser")
#gets the URL for the next show
urlDivContainer = page_soup.findAll("div",
{"class": "well clearfix"})
urlDiv = urlDivContainer[1]
aTag = urlDiv.find_all('a')[1]
url = "https://phish.net" + aTag["href"]
#Get the date from the site-header
dateDiv = page_soup.find("div", {"class": "setlist-date-long"})
aTag = dateDiv.find_all('a')[1]
dateString = str(aTag)
date = dateString[len(dateString) - 14:len(dateString) -
4] #Formatted in "MM/DD/YYYY"
#Reorganizes date-format to "YYYY-MM-DD"
year = date[len(date) - 4:len(date)]
month = date[0:2]
day = date[3:5]
date = year + "-" + month + "-" + day
#Get the Venue
venueDiv = page_soup.find("div", {"class": "setlist-venue"})
aTag = venueDiv.find('a').contents[0]
venue = str(aTag.contents[0]).title()
#Get the Location
locDiv = page_soup.find("div", {"class": "setlist-location"})
aTag = locDiv.find_all("a")
city = aTag[0].contents[0]
state = aTag[1].contents[0]
#Iterate through sets
setlistBody = page_soup.find("div", {"class": "setlist-body"})
p = setlistBody.find("p")
#Works through and gets the set or song information
setlistSongCount = 1
setInfo = ""
for tag in p.find_all(["a", "span"]):
#If next tag is span tag, it will hold the setInfo instead of a song
if (tag.name == "span"):
setInfo = tag.contents[0]
setlistSongCount = 1
setCount += 1
else: #Otherwise, the next tag will be an <a>, which holds a song.
song = tag.contents[0]
songID = 1
#Check whether or not to add song to Song table
val = valueCheck.checkSong(conn, song)
if (val == False):
songToInsert = (songCount, song)
SQLInsert.insert_song(conn, songToInsert)
songID = songCount
songCount += 1
else:
cur.execute(
"SELECT songID FROM Songs WHERE songName LIKE (?)",
(song, ))
songID = cur.fetchall()[0][0]
#Handles whether songs are separated by ",", ">", or "->"
sib = tag.next_sibling
sibString = str(sib)
while (sibString[0] == "<"):
sib = sib.next_sibling
sibString = str(sib)
segue = False
transition = False
if ("->" in sibString):
transition = True
elif (">" in sibString):
segue = True
setlistEntryToInsert = (setlistEntryCount, showCount,
setCount, setInfo,
setlistSongCount, songID, segue,
transition)
SQLInsert.insert_setlist(conn, setlistEntryToInsert)
setlistSongCount += 1
setlistEntryCount += 1
#Check the Venues table if this Venue already exists
val = valueCheck.checkVenue(conn, venue)
if (val == False):
venueToInsert = (venueCount, venue, city, state)
SQLInsert.insert_venue(conn, venueToInsert)
venueID = venueCount
venueCount += 1
#Otherwise, get the venueID from the Venues table
else:
cur.execute(
"SELECT venueID FROM Venues WHERE venueName LIKE (?)",
(venue, ))
venueID = cur.fetchall()[0][0]
#Add the Show to the Shows table
showToInsert = (showCount, date, venueID)
SQLInsert.insert_show(conn, showToInsert)
showCount += 1
def index(request):
this_user = User.objects.get(id=request.session['id'])
site_links = []
site_headlines = []
user_list = this_user.news.all()
first_item = this_user.news.first()
if first_item != None:
categories = [first_item.list_name]
else:
categories = []
links_dict = {}
#Generate list of all of the users news categories
for list_name in user_list:
for category in categories:
if categories == [] or category != list_name.list_name:
print('in IF')
categories.append(list_name.list_name)
else:
print('in ELSE')
continue
# print('////////////////////////////////////', categories)
#Generate an object where there is a key for each category and it's value will be a list of valuable links
for category in categories:
content_list = []
for entry in user_list:
site_list = []
site_links = []
site_headlines = []
if entry.list_name == category:
#open connection to page, copy html as local variable, close connection
uClient = uReq(f'{ entry.site }')
page_html = uClient.read()
uClient.close()
site_list.append(entry.site)
#BeautifulSoup Magic
soup = bsoup(page_html, 'html.parser')
for story in soup.find_all('a'):
# print('//////////// entry.site = ', entry.site)
# print(story.get('href'))
if story.get('href') == None:
continue
if entry.site in story.get('href') and re.search(
r'\b[0-9]{4}\b', story.get('href')) != None:
site_links.append(story.get('href'))
# print('{{{{{{{{{{{{', story.text)
for h1 in soup.find_all('a'):
for h1 in story.find_all('h1'):
values = h1.text
for h2 in soup.find_all('a'):
for h2 in story.find_all('h2'):
values = h2.text
for h3 in soup.find_all('a'):
for h3 in story.find_all('h3'):
values = h3.text
for h4 in soup.find_all('a'):
for h4 in story.find_all('h4'):
values = h4.text
if values != '':
site_headlines.append(values)
#Write the links and headlines to the context.
print('================', len(site_headlines), len(site_links))
for content in range(len(site_headlines)):
content_list.append(
[site_headlines[content], site_links[content]])
links_dict.update({f'{category}': content_list})
# context.update({ f'{i}_links': site_links })
# context.update({ f'{i}_headlines': site_headlines})
context = {'links_dict': links_dict, 'categories': categories}
print('/////////////context = ', context)
return render(request, 'tracker/dashboard.html', context)
def evenextract():
from settings import my_url, name, doc, last, RH, COD_PRODUCTO
import init, bs4, logging, sys, re
global conteventos
LOG_FILENAME = './Logs/Registros.log'
logging.basicConfig(filename=LOG_FILENAME,
level=logging.DEBUG,
format="%(asctime)s:%(levelname)s:%(message)s")
LEVELS = {
'debug': logging.DEBUG,
'info': logging.INFO,
'warning': logging.WARNING,
'error': logging.ERROR,
'critical': logging.CRITICAL
}
if len(sys.argv) > 1:
level_name = sys.argv[1]
level = LEVELS.get(level_name, logging.NOTSET)
logging.basicConfig(level=level)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
all = 0
a = 0
x = 0
y = 0
conteventos = 0
auto = ""
vincula = ""
insti = ""
vinculain = ""
page_soup = soup(page_html, "html.parser")
containers = page_soup.findAll("table")
for a in range(0, len(containers)):
buscaeventos = containers[a].h3
#print(buscaeventos)
try:
if buscaeventos.text == "Eventos científicos":
all = a
#print(all)
break
except AttributeError:
pass
if all != 0:
containerb = containers[all]
container = containerb.findAll("table")
for x in range(0, len(container)):
cont = container[x]
info_evento = cont.td.text
#Nombre del evento
index1 = info_evento.find("Nombre del evento:") + 18
index2 = info_evento.find("Tipo de evento:")
NombreEvento = info_evento[index1:index2]
# Tipo de Evento
index1 = info_evento.find("Tipo de evento:") + 15
index2 = info_evento.find(" Ámbito:")
TipoEvento = info_evento[index1:index2]
if TipoEvento.strip() == "Otro":
TipoEvento = "1"
elif TipoEvento.strip() == "Taller":
TipoEvento = "2"
elif TipoEvento.strip() == "Congreso":
TipoEvento = "3"
elif TipoEvento.strip() == "Encuentro":
TipoEvento = "4"
elif TipoEvento.strip() == "Seminario":
TipoEvento = "5"
elif TipoEvento.strip() == "Simposio":
TipoEvento = "6"
else:
logging.critical('Añadir a Tipo_Evento: ' + TipoEvento)
print("ALERTA: Revisar el archivo Registros.log")
#Ambito
index1 = info_evento.find(
"\xa0\r\n Ámbito: "
) + 51
index2 = info_evento.find(
"\xa0 \r\n Realizado el:"
)
Ambito = info_evento[index1:index2]
#Fecha de Realización inicio y fin
index1 = info_evento.find("Realizado el:") + 13
index2 = index1 + 4
AnoEventoini = info_evento[index1:index2]
if AnoEventoini == "," or AnoEventoini == ",\xa0\r\n":
MesEventoini = ""
AnoEventoini = ""
FechaEventoini = ""
MesEventofin = ""
AnoEventofin = ""
FechaEventofin = ""
else:
index1 = index1 + 5
index2 = index1 + 2
MesEventoini = info_evento[index1:index2]
index1 = info_evento.find("Realizado el:") + 13
index2 = index1 + 10
FechaEventoini = info_evento[index1:index2]
index1 = info_evento.find(",", index1, len(info_evento)) + 48
index2 = index1 + 4
AnoEventofin = info_evento[index1:index2]
if AnoEventofin == " \xa0\r\n" or AnoEventofin == ",":
MesEventofin = ""
AnoEventofin = ""
FechaEventofin = ""
else:
index1 = index1 + 5
index2 = index1 + 2
MesEventofin = info_evento[index1:index2]
index1 = info_evento.find("Realizado el:") + 13
index1 = info_evento.find(",", index1,
len(info_evento)) + 48
index2 = index1 + 10
FechaEventofin = info_evento[index1:index2]
#Lugar Evento
index1 = info_evento.find(
" \xa0\r\n en "
) + 51
index2 = info_evento.find(" \xa0 - \xa0\r\n")
LugarEvento = info_evento[index1:index2]
b_eventos = cont.findAll("td")
#Autores
autores = b_eventos[3].findAll("li")
if len(autores) == 0:
auto = ""
vincula = ""
else:
for z in range(0, len(autores)):
autor = autores[z].text
index1 = autor.find("Nombre:") + 8
index2 = autor.find(
"\r\n Rol en el evento: "
)
if len(auto) == 0:
auto = autor[index1:index2]
else:
auto = auto + ", " + autor[index1:index2]
index1 = autor.find("Rol en el evento: ") + 18
index2 = autor.find("\r\n ", index1, len(autor))
if len(vincula) == 0:
vincula = autor[index1:index2]
else:
vincula = vincula + ", " + autor[index1:index2]
#Instituciones
Instituciones = b_eventos[2].findAll("li")
if len(Instituciones) == 0:
insti = ""
vinculain = ""
else:
for z in range(0, len(Instituciones)):
institu = Instituciones[z].text
index1 = institu.find("Nombre de la institución:") + 25
index2 = institu.find(
"\r\n Tipo de vinculación"
)
if len(insti) == 0:
insti = institu[index1:index2]
else:
insti = insti + ", " + institu[index1:index2]
index1 = institu.find("Tipo de vinculación") + 19
index2 = institu.find("'", index1, len(institu))
if len(vinculain) == 0:
vinculain = institu[index1:index2]
else:
vinculain = vinculain + ", " + institu[index1:index2]
#Productos Asociados
productos = b_eventos[1].findAll("li")
if len(productos) == 0:
init.rel_persona_producto_colciencias.append(str(RH) + ";"\
+ str(COD_PRODUCTO) + ";"\
+ "0" + ";"\
+ "" + ";"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',TipoEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',NombreEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "" + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',LugarEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',Ambito.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "" + ";" \
+ "" + ";" \
+ "" + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',auto.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',vincula.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "" + ";" \
+ "" + ";" \
+ "" + ";" \
+ "" + ";" \
+ "" + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',insti.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',vinculain.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "\n")
init.colciencias_apropiacion.append(str(RH) + str(COD_PRODUCTO) + ";"\
+ str(RH) + ";"\
+ str(COD_PRODUCTO) + ";"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',MesEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaEventofin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoEventofin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',MesEventofin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "\n")
init.inrel_personas_producto_colciencias.append( \
"REPLACE INTO `uapa_db`.`rel_personas_producto_colciencias`(`cod_rel_per_prod_col`,`cod_producto`,`cod_rh`,`cod_tipo_producto`,`nombre_producto`,`evento_asociado`,`datos_complementarios`,`lugar`,`ano`,`ambito`,`palabras_clave`,`areas`,`sectores`,`coautores`,`vincula_coautores`,`editorial`,`volumen`,`paginas`,`doi`,`finalidad`,`instituciones_asociadas`,`tipo_vinculacion_institucion`) VALUES"
+ "('"+ str(RH) + str(COD_PRODUCTO) + "',"
+ str(COD_PRODUCTO) + ","\
+ "'" + str(RH) + "',"\
+ "0" + ","\
+ "null" + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',NombreEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',LugarEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',Ambito.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',auto.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',vincula.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',insti.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',vinculain.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "');\n")
init.incolciencias_apropiacion.append( \
"REPLACE INTO `uapa_db`.`colciencias_apropiacion`(`cod_colciencias_apropiacion`,`cod_rh`,`cod_rel_per_prod_col`,`fecha_ini`,`fecha_fin`,`cod_tipo_evento`) VALUES"
+ "('" + str(COD_PRODUCTO) + "',"\
+ "'" + str(RH) + "',"\
+ "'" + str(RH) + str(COD_PRODUCTO) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaEventofin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "null" + ");\n")
COD_PRODUCTO = COD_PRODUCTO + 1
else:
for y in range(0, len(productos)):
prod = productos[y].text
index1 = prod.find("Nombre del producto:") + 20
index2 = prod.find("Tipo de producto:")
NombreProducto = prod[index1:index2]
index1 = prod.find("Tipo de producto:") + 17
index2 = prod.find("\r\n", index1, len(prod))
Tipopub = prod[index1:index2]
if Tipopub == "Producción bibliográfica - Trabajos en eventos (Capítulos de memoria) - Completo":
Tipopub = "2"
elif Tipopub == "Producción técnica - Presentación de trabajo - Comunicación":
Tipopub = "3"
elif Tipopub == "Demás trabajos - Demás trabajos - Póster":
Tipopub = "4"
elif Tipopub == "Producción técnica - Presentación de trabajo - Conferencia":
Tipopub = "5"
elif Tipopub == "Producción técnica - Presentación de trabajo - Ponencia":
Tipopub = "6"
elif Tipopub == "Producción bibliográfica - Trabajos en eventos (Capítulos de memoria) - Resumen":
Tipopub = "12"
elif Tipopub == "Producción técnica - Presentación de trabajo - Congreso":
Tipopub = "13"
elif Tipopub == "Producción técnica - Presentación de trabajo - Simposio":
Tipopub = "14"
elif Tipopub == "Producción técnica - Presentación de trabajo - Seminario":
Tipopub = "15"
elif Tipopub == "Producción técnica - Presentación de trabajo - Otro":
Tipopub = "16"
else:
logging.critical('Añadir a Tipo_Producto: ' +
TipoEvento)
print("ALERTA: Revisar el archivo Eventos.log")
init.rel_persona_producto_colciencias.append(str(RH) + ";"\
+ str(COD_PRODUCTO) + ";"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',Tipopub.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',NombreProducto.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',TipoEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',NombreEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "" + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',LugarEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoEventofin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',Ambito.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "" + ";" \
+ "" + ";" \
+ "" + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',auto.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',vincula.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "" + ";" \
+ "" + ";" \
+ "" + ";" \
+ "" + ";" \
+ "" + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',insti.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',vinculain.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "\n")
init.inrel_personas_producto_colciencias.append( \
"REPLACE INTO `uapa_db`.`rel_personas_producto_colciencias`(`cod_rel_per_prod_col`,`cod_producto`,`cod_rh`,`cod_tipo_producto`,`nombre_producto`,`evento_asociado`,`datos_complementarios`,`lugar`,`ano`,`ambito`,`palabras_clave`,`areas`,`sectores`,`coautores`,`vincula_coautores`,`editorial`,`volumen`,`paginas`,`doi`,`finalidad`,`instituciones_asociadas`,`tipo_vinculacion_institucion`) VALUES"
+ "('"+ str(RH) + str(COD_PRODUCTO) + "',"
+ str(COD_PRODUCTO) + ","\
+ "'" + str(RH) + "',"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',Tipopub.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',NombreProducto.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',NombreEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "null" + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',LugarEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',Ambito.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',auto.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',vincula.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "null" + ","\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',insti.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',vinculain.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "');\n")
init.colciencias_apropiacion.append(str(RH) + str(COD_PRODUCTO) + ";"\
+ str(RH) + ";"\
+ str(COD_PRODUCTO) + ";"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',TipoEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ","\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',MesEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaEventofin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',AnoEventofin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',MesEventofin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ";" \
+ "\n")
init.incolciencias_apropiacion.append( \
"REPLACE INTO `uapa_db`.`colciencias_apropiacion`(`cod_colciencias_apropiacion`,`cod_rh`,`cod_rel_per_prod_col`,`fecha_ini`,`fecha_fin`,`cod_tipo_evento`) VALUES"
+ "('" + str(COD_PRODUCTO) + "',"\
+ "'" + str(RH) + "',"\
+ "'" + str(RH) + str(COD_PRODUCTO) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaEventoini.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ "'" + re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',FechaEventofin.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + "',"\
+ re.sub(r'[^A-Za-z0-9éèáàéñèíìúùó ò]',r'',re.sub(' +',' ',TipoEvento.replace('"',"").replace("'","").strip().replace(";" , "|").replace("\r\n","").replace("\n","").replace("\r",""))) + ");\n")
COD_PRODUCTO = COD_PRODUCTO + 1
auto = ""
vincula = ""
insti = ""
vinculain = ""
else:
logging.info(' El Docente ' + name + ' ' + last +
' no tiene Eventos Asociados')
conteventos = [COD_PRODUCTO]
import csv
from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as uReq
Url = 'https://karki23.github.io/Weather-Data/Albury.html'
pageHtml = uReq(Url)
soup = soup(pageHtml,"html.parser")
table = soup.find_all("table", { "class" : "tablepress tablepress-id-10 tablepress-responsive-phone" })
with open('Albury.csv', 'w',newline='') as csvfile:
f = csv.writer(csvfile)
f.writerow(['Date', 'Location', 'MinTemp','MaxTemp','Rainfall','Evaporation','Sunshine','WindGustDir','WindGustSpeed','WindDir9am','WindDir3pm','WindSpeed9am','WindSpeed3pm','Humidity9am','Humidity3pm','Pressure9am','Pressure3pm','Cloud9am','CLoud3pm','Temp9am','Temp3pm','RainToday','RISK_MM','RainTomorrow'])
for x in table:
table_body = x.find('tbody')
rows = table_body.find_all('tr')
for tr in rows:
data=[]
cols = tr.find_all('td')
for td in cols:
data.append(td.text.strip())
f.writerow(data)
print(data)
price_list = []
address1_list = []
address2_list = []
room_list = []
shower_list = []
car_list = []
size_list = []
for i in tqdm(range(1,7)):
# sleep is used to make sure that I dont spam the server too much
time.sleep(2)
try:
my_url = "https://www.domain.com.au/sale/?suburb=caulfield-vic-3162,elsternwick-vic-3185,gardenvale-vic-3185,glen-huntly-vic-3163,mckinnon-vic-3204,murrumbeena-vic-3163,ormond-vic-3204,carnegie-vic-3163,bentleigh-vic-3204,bentleigh-east-vic-3165&ptype=apartment&bedrooms=2-any&price=0-750000&excludeunderoffer=1&carspaces=1-any&ssubs=0&page={}".format(i)
req = urllib.request.Request(my_url,headers={'User-Agent': "Magic Browser"})
con = uReq(req)
page_html = con.read()
con.close()
# html parsing
page_soup = soup(page_html, 'html.parser')
containers = page_soup.find_all(class_="css-qrqvvg")
for container in containers:
# Get price
try:
price_container = container.find_all('p', class_="css-mgq8yx")
price = price_container[0].text.strip().encode('ascii', 'ignore').decode("utf-8")
price_list.append(price)
print(price)
except IndexError:
print('None')
price_list.append('NG')
from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as uReq
from time import ctime as ct
# This file aims at scrapping a youtube channel in order to get data as:
# the number of subscribers, the number of views and the starting date of this
# particular channel.
channelName="Mister Geopolitix"
channelUrl="https://www.youtube.com/channel/UCX9lsdsTKfTi1eqoyL-RS-Q/about"
#Opening connection, grabbing the page
uClient = uReq(channelUrl)
pageHtml = uClient.read()
uClient.close()
# Using beautifulsoup module we parse the source code of the webpage
pageSoup = soup(pageHtml, "html.parser")
# We are seeking the 'about-stat' span section:
stats = pageSoup.findAll("span", {"class", "about-stat"})
# Values Extraction
nbSubs = stats[0].find("b").text.replace('\xa0', ' ')
nbViews = stats[1].find("b").text.replace('\xa0', ' ')
startDate = stats[2].text.replace('\xa0', ' ')
# Save data in a file with the current date
record = open("log.txt", "a")
date = ct() #current time
"KKTC-GİRNE": "85",
"TÜRKİSTAN-KAZAKİSTAN": "86",
"KKTC-GÜZELYURT": "87",
"BİŞKEK-KIRGIZİSTAN": "88",
"KOMRAT-MOLDOVA": "89",
"KKTC-LEFKE": "90",
"ÜSKÜP-MAKEDONYA": "91",
}
return switcher.get(cityName, "0")
f = open("university-data.txt", "a")
mainUrl = 'https://www.basarisiralamalari.com/universite-taban-puanlari-2020-ve-basari-siralamalari-osym/'
# Opens up the connection and gets the html page from it
uClient = uReq(mainUrl)
pageHtml = uClient.read()
# Closes the connection
uClient.close()
pageSoup = soup(pageHtml.decode('utf-8', 'ignore'), 'html.parser')
uniTable = pageSoup.find('table', {'id': 'basaritable'})
wholeTbody = uniTable.tbody
allRows = wholeTbody.findAll('tr')
allURLs = []
for row in allRows:
if row.find('tr', attrs={'style': 'height: 46px;'}):
from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as uReq
#from textblob import TextBlob
#input item name from user and remove spaces
print("Search for item..?")
item_name_full = input()
item_name = item_name_full.replace(' ', '')
#link to scrap data from
my_url = 'https://www.flipkart.com/search?q=' + item_name + '&otracker=search&otracker1=search&marketplace=FLIPKART&as-show=on&as=off'
#open connection
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
#Use BeautigulSoup to parse the html site
page_soup = soup(page_html, "html.parser")
#on web browser 'inspect element' to get the class of part which we want to scrap
no_page_soup = page_soup.findAll("div", {"class": "_2zg3yZ"})
#print total no of page like 'Page 1 of 8'
'''print(no_page_soup[0].span.text)'''
#Find only total no. of pages. like '8' and then convert to int
num_pages_str = no_page_soup[0].span.text
#['Page', '1', 'of', '8']
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
my_url = ["https://www.theravive.com/cities/ma/"]
#opening up connection, grabbing the page
for i in my_url:
uClient = uReq(i)
page1_html = uClient.read()
uClient.close()
#html parsing
page1_soup = soup(page1_html, "html.parser")
#grabs each product
containers = page1_soup.findAll("div", {"class": "profile-info"})
container = containers[0]
filename = "ma.csv"
f = open(filename, "w")
headers = "Name, Profession, Contact_Info\n"
f.write(headers)
for container in containers:
address_container = container.findAll("div",
{"class": "profile-address"})
address = address_container[0].text.strip()
name_container = container.findAll("h4", {"class": "green-text"})
a = 0
while (choice != 4):
print("1.DO YOU WANT TO SEE PRODUCTS PREVAILING IN FLIPKART?")
print("2.DO YOU WANT TO SEE PRODUCTS PREVAILING IN SNAPDEAL?")
print("3.DO YOU WANT TO SEE WHICH E-SITE IS EFFICIENT?")
print("4.EXIT")
print(
"***********************************************************************"
)
choice = int(input())
if (choice == 1):
i = 0
print("NOW YOU ARE IN FLIPKART")
my_url = 'https://www.flipkart.com/search?q=kurti&otracker=search&otracker1=search&marketplace=FLIPKART&as-show=on&as=off'
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
page_soup = soup(page_html, "html.parser")
containers = page_soup.findAll("div", {"class": "_3liAhj _1R0K0g"})
print("total number of dresses in this page:", len(containers))
container = containers[0]
for container in containers:
name1 = container.findAll("a", {"class": "_2cLu-l"})
name = name1[0].text.strip()
print(name)
price1 = container.findAll("div", {"class": "_1vC4OE"})
price = price1[0].text.strip()
print(price)
rat1 = container.findAll("span", {"class": "_2_KrJI"})
try:
def index():
if request.method == 'POST':
try:
searchString = request.form['content'].replace(" ", "")
flipkart_url = "https://www.flipkart.com/search?q=" + searchString
uClient = uReq(flipkart_url)
flipkartPage = uClient.read()
uClient.close()
flipkart_html = bs(flipkartPage, "html.parser")
bigboxes = flipkart_html.findAll("div", {"class": "bhgxx2 col-12-12"})
del bigboxes[0:3]
box = bigboxes[0]
productLink = "https://www.flipkart.com" + box.div.div.div.a['href']
print(productLink)
prodRes = requests.get(productLink)
prod_html = bs(prodRes.content, "html.parser")
prod = prod_html.find('div', {'class': '_29OxBi'}).h1.span.get_text()
data = prod_html.find('div', {'class': 'swINJg _3nrCtb'})
parent = data.find_parent()
url = parent.get('href')
url = 'https://www.flipkart.com' + url
req_data = requests.get(url)
all_reviews = bs(req_data.content, 'html.parser')
pages = all_reviews.find_all('div', {'class': '_2zg3yZ _3KSYCY'}) # extracts all the pages url info
page = int(pages[0].span.get_text().split()[-1])
if page > 3:
page = 3
reviews = []
for i in range(0, page): # we iterate through all the pages
commentboxes = all_reviews.find_all('div', {'class': "_1PBCrt"})
for commentbox in commentboxes:
try:
name = commentbox.div.div.find_all('p', {'class': '_3LYOAd _3sxSiS'})[0].text
except:
name = 'No Name'
try:
rating = commentbox.div.div.div.div.text
except:
rating = 'No Rating'
try:
commentHead = commentbox.div.div.div.p.text
except:
commentHead = 'No Comment Heading'
try:
comtag = commentbox.div.div.find_all('div', {'class': ''})
custComment = comtag[0].div.text
except Exception as e:
print("Exception while creating dictionary: ", e)
mydict = {"Product": prod, "Name": name, "Rating": rating, "CommentHead": commentHead,
"Comment": custComment}
reviews.append(mydict)
return render_template('results.html', reviews=reviews[0:(len(reviews) - 1)])
except Exception as e:
print('The Exception message is: ', e)
return 'something is wrong'
else:
return render_template('index.html')
def add_box_office(csv_in, csv_out):
ratings = pd.read_csv(csv_in, encoding='ISO-8859-1')
ratings['Box Office Gross USA'] = 0
ratings['Box Office Gross USA'].fillna(value=0, inplace=True)
infl_string = 'Inflation Adjusted Box Office Gross USA'
ratings[infl_string] = 0
ratings[infl_string].fillna(value=0, inplace=True)
context = ssl._create_unverified_context()
for i in range(len(urls)):
url = urls[i]
# Open connection, read html, close connection
uClient = uReq(url, context=context)
page_html = uClient.read()
uClient.close()
# html parser
page_soup = soup(page_html, 'html.parser')
# print(page_soup.body.span)
title = page_soup.title.get_text()
print(title)
movie_year = '2020'
if (not 'TV Series' in title and not 'TV Mini-Series' in title):
open_paren = title.find('(')
close_paren = title.find(')')
movie_year = title[open_paren + 1:close_paren]
print('Year: ', movie_year)
box_office_gross = page_soup.find('div', {'id': 'main_bottom'})
box_office_gross = box_office_gross.find('div', {'id': 'titleDetails'})
box_office_gross = box_office_gross.findAll('div',
{'class': 'txt-block'})
print('num divs: ', len(box_office_gross))
j = 0
has_gross_usa = False
for j in range(4, len(box_office_gross)):
if ('Gross USA' in box_office_gross[j].get_text()):
has_gross_usa = True
break
if (has_gross_usa):
box_office_gross = box_office_gross[j].get_text()
dollar_index = box_office_gross.find('$')
box_office_gross = box_office_gross[dollar_index + 1:]
box_office_gross = box_office_gross.replace(',', '')
else:
box_office_gross = 0
t = datetime.now().year - int(movie_year)
# Inflation adjusted box office gross
infl_adj_gross = float(box_office_gross) * (pow(
(1 + 1.84545 / 100), t))
box_off_loc = ratings.columns.get_loc('Box Office Gross USA')
ratings.iat[i, box_off_loc] = float(box_office_gross)
ratings.iat[i, box_off_loc + 1] = float(infl_adj_gross)
# Format numbers to $xxx,xxx,xxx.xx
infl_adj_gross = '${:,.2f}'.format(infl_adj_gross)
box_office_gross = '${:,.2f}'.format(float(box_office_gross))
print("Box office gross: ", box_office_gross)
print("Box office gross (inflation adjusted): ", infl_adj_gross)
print()
print('----------------------------------')
print()
ratings.to_csv(csv_out)
set_url = root_url + set_name_url
print("url: " + set_url)
# spoof header
req = Request(set_url)
req.add_header("User-Agent", "Mozilla/5.0")
###################################
# download and parse page into soup
###################################
scrape_date = str(datetime.now())
web_client = uReq(req)
print("web_client: " + str(web_client.getcode()))
soup = soup(web_client.read(), "html.parser")
web_client.close()
#######################
# isolate pricing table
#######################
html_tables = soup.find_all("table")
# lots of tables. We only need the pricing table
html_table = html_tables[8]
c = 0
while True:
if c == 0:
cf_id = input("Enter your codeforces id : ")
c += 1
else:
cf_id = input("Enter your codeforces id again\n")
link = 'https://www.codeforces.com/profile/' + cf_id
check = requests.get(link)
display = "INVALID Codeforces ID"
if check.url == "https://codeforces.com/":
print(display.center(40, '*'))
else:
break
uClient = uReq(link)
link = "https://codeforces.com/api/user.info?handles=" + cf_id
ml = requests.get(link)
page_html = uClient.read()
uClient.close()
page_soup = soup(page_html, "html.parser")
c = page_soup.find_all('li')
p = json.loads(ml.text)
dic = p['result']
ls = dic[0]
#user-id
print("User-ID:", cf_id)
#User Name
print("Name:", ls['firstName'], ls['lastName'])
review_date = item.select("small")[0].text
review_title = item.select("strong a[id^=ctl00_ctl00_ContentPlaceHolderFooter_ContentPlaceHolderBody_rptreviews]")[0].text
review_data = ' '.join([' '.join(items.text.split()) for items in item.select(".reviewdata")])
print("Name:", name)
print("Location:", location)
print("Review_date:", review_date)
print("Review_Title:", review_title)
print("Review_Data:", review_data)
row = [name, location, review_date, review_title, review_data]
csv_writer.writerow(row)
# --- get next url ---
uclient = uReq(url)
page_html = uclient.read()
uclient.close()
soup = BeautifulSoup(page_html, "html.parser")
container = soup.find("ul", {"class": "pages table"})
all_li = container.findAll("li")
if all_li:
last_div = all_li[-1]
content = last_div.getText()
content = int(content)
container = soup.findAll("li", {"class": "next"})
li = container[0].find("a", {"class": "btn btn-link"}).attrs['href']
# ---- get data ---
"div", {
"id":
"ctl00_ctl00_ctl00_MainContent_SubContent_SubContent_ctl04_nameRow"
})
transName = transDiv.find("div", {"class": "value"})
csvDict['Trans_Card'] = transName.text.strip()
with open('cards.csv', 'a', encoding='utf8', newline='') as csvfile:
scrapeTo = csv.DictWriter(csvfile, fieldnames=card_values)
scrapeTo.writerow(csvDict)
return
my_url = 'http://gatherer.wizards.com/Pages/Search/Default.aspx?text=+%5Btransform%5D'
# opening connection, grabbing page
uClient = uReq(my_url)
page_html = uClient.read()
# html parsing
page_soup = soup(page_html, "lxml")
page_nums = page_soup.find("div", {"class": "paging"})
# grabs cardInfo div
siteURL = "http://gatherer.wizards.com"
# scrapeTo = csv.writer(open('card.csv', 'wb'))
cardCount = 0
current_page = 0
from bs4 import BeautifulSoup
from urllib.request import urlopen as uReq
# Url of page to scrape
my_url = "http://magic.wizards.com/en/events/coverage/gpman16/mono-blue-prison-with-martin-muller-2016-05-28"
# Grab page html form URL
web_client = uReq(my_url)
# convert raw html to a soup object
page_soup = BeautifulSoup(web_client.read(), "html.parser")
# Extract deck
deck_soup = page_soup.find_all("div", {"class": "deck-list-text"})
# Extract card count quantities from deck
card_counts = page_soup.find_all("a", {"class": "card-name"})
# Extract card information from deck
input("Press any key to end.")
def index():
searchString = request.form['content'].replace(
" ", "") # obtaining the search string entered in the form
try:
# dbConn = pymongo.MongoClient("mongodb://localhost:27017/") # opening a connection to Mongo
#db = dbConn['crawlerDB'] # connecting to the database called crawlerDB
# reviews = db[searchString].find({}) # searching the collection with the name same as the keyword
# if reviews.count() > 0: # if there is a collection with searched keyword and it has records in it
# return render_template('results.html',reviews=reviews) # show the results to user
#else:
flipkart_url = "https://www.flipkart.com/search?q=" + searchString # preparing the URL to search the product on flipkart
uClient = uReq(
flipkart_url) # requesting the webpage from the internet
flipkartPage = uClient.read() # reading the webpage
uClient.close() # closing the connection to the web server
flipkart_html = bs(flipkartPage,
"html.parser") # parsing the webpage as HTML
bigboxes = flipkart_html.findAll("div", {
"class": "bhgxx2 col-12-12"
}) # seacrhing for appropriate tag to redirect to the product link
del bigboxes[
0:
3] # the first 3 members of the list do not contain relevant information, hence deleting them.
box = bigboxes[0] # taking the first iteration (for demo)
productLink = "https://www.flipkart.com" + box.div.div.div.a[
'href'] # extracting the actual product link
prodRes = requests.get(
productLink) # getting the product page from server
prod_html = bs(prodRes.text,
"html.parser") # parsing the product page as HTML
commentboxes = prod_html.find_all(
'div',
{'class': "_3nrCtb"
}) # finding the HTML section containing the customer comments
#table = db[searchString] # creating a collection with the same name as search string. Tables and Collections are analogous.
#filename = searchString+".csv" # filename to save the details
#fw = open(filename, "w") # creating a local file to save the details
#headers = "Product, Customer Name, Rating, Heading, Comment \n" # providing the heading of the columns
#fw.write(headers) # writing first the headers to file
reviews = [] # initializing an empty list for reviews
# iterating over the comment section to get the details of customer and their comments
for commentbox in commentboxes:
try:
name = commentbox.div.div.find_all(
'p', {'class': '_3LYOAd _3sxSiS'})[0].text
except:
name = 'No Name'
try:
rating = commentbox.div.div.div.div.text
except:
rating = 'No Rating'
try:
commentHead = commentbox.div.div.div.p.text
except:
commentHead = 'No Comment Heading'
try:
comtag = commentbox.div.div.find_all('div', {'class': ''})
custComment = comtag[0].div.text
except:
custComment = 'No Customer Comment'
#fw.write(searchString+","+name.replace(",", ":")+","+rating + "," + commentHead.replace(",", ":") + "," + custComment.replace(",", ":") + "\n")
mydict = {
"Product": searchString,
"Name": name,
"Rating": rating,
"CommentHead": commentHead,
"Comment": custComment
} # saving that detail to a dictionary
# x = table.insert_one(mydict) #insertig the dictionary containing the rview comments to the collection
reviews.append(
mydict) # appending the comments to the review list
return render_template(
'results.html', reviews=reviews) # showing the review to the user
except:
return 'something is wrong'
def parse_deck(mtggoldfish_url):
# grab and soup page
page_client = uReq(mtggoldfish_url)
print("Grabbing the html through the blind eternities...")
page_soup = BeautifulSoup(
page_client.read(), "html.parser"
)
page_client.close()
# Grabs the paper decklist with the prices
print("Extracting table...")
deck_table = page_soup.find_all(
"div", {"id": "tab-paper"}
)
# discards things around the table
deck_table = deck_table[0].div.div.table
# gets all the rows from the html table
table_rows = deck_table.find_all("tr")
decklist = {}
# Loops through the rows
print("Parsing rows...")
for row in table_rows:
columns = row.find_all("td")
if(len(columns) == 4):
# extracts features from each column
quantity = columns[0].text.strip()
card_name = columns[1].text.strip()
color = ""
try:
color = columns[2].span.img['alt'].strip()
except AttributeError:
pass
price = round(
float(
columns[3].text.strip()
),
2 # two decimal places
)
card_key = card_name.lower()
decklist[card_key] = {
"card_name": card_name,
"color": color,
"price_amt": price,
"price_date_utc": str(datetime.datetime.utcnow()),
"deck_qty": quantity,
}
print("Parsed..." +
card_name + ", " +
color + ", " +
quantity + ", " +
str(price)
)
print("Printing card names.")
card_names = list(decklist.keys())
card_names.sort()
print(card_names)
print("Printing dictionary.")
print(decklist)
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
from email.mime.text import MIMEText
import smtplib
import sys
MY_URL = 'http://www.secretflying.com/posts/category/error-fare/'
USER_CLIENT = uReq(MY_URL)
PAGE_HTML = USER_CLIENT.read()
USER_CLIENT.close()
PAGE_SOUP = soup(PAGE_HTML, "html.parser")
ERROR_FARES_CONTENT = PAGE_SOUP.findAll(
"div", {"class": "article-content-wrapper entry-main-content"})
ORIGINAL_TEXT_FILE = "errorfarelist.txt"
DIFFERENCES_TEXT_FILE = "errorfaresdiffs.txt"
# This writes the previous data from a text file into a list prior to the next function potentially finding updates.
def store_existing_deals_in_mem():
with open(ORIGINAL_TEXT_FILE, "r") as F:
current_deals_file = []
for word in F:
current_deals_file.append(word.strip('\n'))
return current_deals_file
# The website page 'titles' are parsed then the content is written to a text file (overwrites all data in the file).
def parse_and_write_to_file():
with open(ORIGINAL_TEXT_FILE, "w+") as F:
for deals in ERROR_FARES_CONTENT:
try:
def main():
# Uses tweepy to access twitter to allow the ability to tweet
consumer_key = #consumer key
consumer_secret = #consumer secret
access_token = #enter access token
access_token_secret = #enter access password
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tweepy.API(auth)
# Stores URL
my_url = 'https://www.snopes.com/category/facts/'
# Opening connection, grab the page
uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
# parse
page_soup = soup(page_html, "html.parser")
# get specific part of html
containers = page_soup.findAll("a", {"class": "article-link"})
title = [15]
url = [15]
validity = [15]
# Grabs title from Snopes web page
for container in containers[:10]:
try:
# Grabs the title of article
x = 0
title.insert(x, str(container.h2.text))
except(NameError, IndexError, AttributeError):
print("Error")
# print(title[x])
x += 1
# Grabs validity from Snopes web page
for container in containers[:10]:
try:
validity_container = container.findAll("span", {"itemprop": "reviewRating"})
x = 0
for valid in validity_container:
validity.insert(x, valid.span.text)
except(NameError, IndexError, AttributeError):
print("Error")
x += 1
# Creates link list that stores all url on web page
links = []
# URL's we are actually interested in start here
ind = 94
# # Grabs url from Snopes web page
for container in containers[:10]:
try:
# Grabs all url tags on web page
y = 0
for link in page_soup.findAll('a', attrs={'href': re.compile("^https://www.snopes.com")}):
links.append(link.get('href'))
# Iterates to corresponding url
url.insert(y, links[ind])
ind += 1
except(NameError, IndexError, AttributeError):
print("Error")
# Test print to make sure three
# for x in range(10):
# print(title[x] + " " + validity[x] + " " + url[x])
# Creates tweet with articles found false by Snopes
for x in range(10):
if validity[x] in ('FALSE', 'MOSTLY FALSE'):
api.update_status("FAKE NEWS ALERT!! \n" +
title[x] + " " + url[x]
+ " #FAKENEWS #RESISTTRUMP #RESIST"
" #STOPHATE #REALNEWS #TRUMP "
"#POLITICS #RESIST #NEWS"
" #RUSSIA" "ANTIRUSSIA"
" #INVESTIGATE"
)
else:
continue
print("--- %s seconds ---" % (time.time() - start_time))
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
current_date = date.today()
filename = "results {}_{}_{}.csv".format(current_date.day, current_date.month,
current_date.year)
f = open(filename, "w")
headers = "suburb,address,bed,result,price,link\n"
f.write(headers)
all_letters = [
"a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o",
"p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"
]
for letter in all_letters:
RE_url = 'https://www.realestateview.com.au/sales-and-auction-results/victoria/' + letter + '/'
# opens a connection to URL
uClient = uReq(RE_url)
# puts all the HTML into a container
page_html = uClient.read()
# closes connection
uClient.close()
# stores html as soup
page_soup = soup(page_html, "html.parser")
#finds relevant info on page
containers = page_soup.findAll("tr", {"class": "auction-result-item"})
#things you want: Suburb, address, bedrooms, result, price
for container in containers:
#suburb
suburb_container = container.findAll("meta",
{"itemprop": "addressLocality"})
from bs4 import BeautifulSoup
from urllib.request import urlopen as uReq
# URL to be scraped. Has to be an edhrec page.
target_url = "https://edhrec.com/sets/akh/"
# Open connection, download page
web_client = uReq(target_url)
# Parse page into a soup data structure
print("Grabbing website: " + target_url)
page_soup = BeautifulSoup(web_client.read(), "html.parser")
# Close the web client
web_client.close()
card_frames = page_soup.find_all("div", {"class": "nw"})
out_filename = "scrape_edhrec_output.tsv"
f = open(out_filename, "w")
headers = "card_name\tin_decks\tprice\n"
f.write(headers)
for card_frame in card_frames:
name_frame = card_frame.find_all("div", {"class": "nwname"})
card_name = name_frame[0].text
quantity_frame = card_frame.find_all("div", {"class": "nwdesc ellipsis"})
quantity = quantity_frame[0].text
quantity = quantity.replace(" decks", "")
"""Script created by following tutorial here: https://www.youtube.com/watch?v=XQgXKtPSzUI"""
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
myurl = 'https://www.newegg.com/Video-Cards-Video-Devices/Category/ID-38?Tpk=graphics%20cards'
filename = "products.csv"
f = open(filename, "w")
headers = "brand, product_name, shipping\n"
f.write(headers)
# Open connection and download page.
uClient = uReq(myurl) # Download URL.
page_html = uClient.read() # Downloaded HTML.
uClient.close() # Close the client after downloading.
# Parse HTML
pagesoup = soup(page_html, "html.parser") # Parse the file as HTML.
# Grab each product
containers = pagesoup.findAll("div", {"class": "item-container"})
container = containers[0]
#print(container.div.div.a.img["title"]) # Item title example.
for container in containers:
brand = container.div.div.a.img["title"]
title_container = container.findAll("a", {"class": "item-title"})
product_name = title_container[0].text
