Hello I'm trying to scrap some info from t he following page:
http://verify.sos.ga.gov/verification/
My code is the following:
import sys
reload(sys)
sys.setdefaultencoding('utf8')
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.support.ui import Select
import time
import csv
url = 'http://verify.sos.ga.gov/verification/'
def init_Selenium():
global driver
driver = webdriver.Chrome("/Users/rodrigopeniche/Downloads/chromedriver")
driver.get(url)
def select_profession():
select = Select(driver.find_element_by_name('t_web_lookup__profession_name'))
options = select.options
for index in range(1, len(options) - 1):
select = Select(driver.find_element_by_name('t_web_lookup__profession_name'))
select.select_by_index(index)
select_license_type()
def select_license_type():
select = Select(driver.find_element_by_name('t_web_lookup__license_type_name'))
options = select.options
for index in range(1, len(options) - 1):
select = Select(driver.find_element_by_name('t_web_lookup__license_type_name'))
select.select_by_index(index)
search_button = driver.find_element_by_id('sch_button')
driver.execute_script('arguments[0].click();', search_button)
scrap_licenses_results()
def scrap_licenses_results():
table_rows = driver.find_elements_by_tag_name('tr')
for index, row in enumerate(table_rows):
if index < 9:
continue
else:
attributes = row.find_elements_by_xpath('td')
try:
name = attributes[0].text
license_number = attributes[1].text
profession = attributes[2].text
license_type = attributes[3].text
status = attributes[4].text
address = attributes[5].text
license_details_page_link = attributes[0].find_element_by_id('datagrid_results__ctl3_name').get_attribute('href')
driver.get(license_details_page_link)
data_rows = driver.find_elements_by_class_name('rdata')
issued_date = data_rows[len(data_rows) - 3].text
expiration_date = data_rows[len(data_rows) - 2].text
last_renewal_day = data_rows[len(data_rows) - 1].text
print name, license_number, profession, license_type, status, address, issued_date, expiration_date, last_renewal_day
driver.back()
except:
pass
init_Selenium()
select_profession()
When I execute the script it works for the first iteration but fails in the second one. The exact place where the error is raised is in the scrap_licenses_results() function, in the attributes = row.find_elements_by_xpath('td') line.
Any help will be appreciated
The staleElementReferenceException is due to the list of rows gathered before loop iteration. Initially, You created a list of all rows ,named table_rows.
table_rows = driver.find_elements_by_tag_name('tr')
Now in loop, during first iteration, your first row element is fresh and can be found by the driver. At the end of first iteration, you are doing driver.back(), your page changes/refreshes HTML DOM . All the previously gathered references are lost now. All the rows in your table_rows list are now stale. Hence, in 2nd iteration you are facing such exception.
You have to move the find row operation in the loop, so that everytime a fresh reference is found on target application. The psuedocode shall do Something like this.
total_rows = driver.find_elements_by_tag_name('tr').length()
for i in total_rows
driver.find_element_by_xpath('//tr[i]')
.. further code..
Related
I'm quite new to python and have written a script using selenium to scrape a website. I've tried everything but can't get the loop to cycle through pages. It currently just repeats the data on the first page 5 times. I want to scrape all the pages for 'BR1' any help would be great, currently the script below only scrapes the first page 5 times.
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import time
with open('rightmove.csv', 'w') as file:
file.write('PropertyCardcontent \n')
PATH = ("/usr/local/bin/chromedriver")
driver = webdriver.Chrome(PATH)
driver.get("https://www.rightmove.co.uk/house-prices.html")
print(driver.title)
elem = driver.find_element(By.NAME, 'searchLocation') # Find the search box
elem.send_keys('BR1' + Keys.RETURN)
try:
content = WebDriverWait(driver, 15).until(
EC.presence_of_element_located((By.ID,'content'))
)
finally:
time.sleep(3)
for p in range(5):
sold = content.find_elements(By.CLASS_NAME, 'sold-prices-content-wrapper ')
for solds in sold:
address = solds.find_elements(By.CLASS_NAME, 'sold-prices-content ')
for addresses in address:
result = addresses.find_elements(By.CLASS_NAME, 'results ')
for results in result:
card = results.find_elements(By.CLASS_NAME,'propertyCard')
for propertyCard in card:
header = propertyCard.find_elements(By.CLASS_NAME,'propertyCard-content')
for propertyCardcontent in header:
road = propertyCardcontent.find_elements(By.CLASS_NAME,'title')
for propertyCardcontent in header:
road = propertyCardcontent.find_elements(By.CLASS_NAME,'subTitle')
for subtitle in road:
bed = subtitle.find_elements(By.CLASS_NAME, 'propertyType')
with open('rightmove.csv', 'a') as file:
for i in range(len(result)):
file.write(header[i].text + '\n')
button = driver.find_element(By.XPATH, '//*[#id="content"]/div[2]/div[2]/div[4]/div[27]/div[3]/div')
button.click()
file.close()
time.sleep(3)
driver.quit()
Since the website link has page number on it, I recommend you put the base url as "https://www.rightmove.co.uk/house-prices/br1.html?page=1", and loop through the pages while changing the last index of the url with methods like format string.
One other thing, you don't need to implement all those for loops, you can simply assign each variable to its specific value since everything you need is inside an html block which is easy to navigate on it.
Update:
I'm sorry for being late, had unexpected stuff(...).
I've made some changes as I use Brave, so make sure you select your browser, Chrome I believe, the chromedriver(ver:102) stays the same (or depending your Chrome version).
I've also got the Price and Date and stored them in a tuple.
Every record is stored in a list[Title, propertyType, tupleof(Price_Date)]
At the end, it creates a csv and stores everything inside with a ";" as delimter.
You can if you prefer split the price and date for later use, up to you.
Note: This looping method only applies to websites in which the number of page is included within the URL. In this case, both the key and number of page is included in the URL.
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.chrome.service import Service
import time
import random
import itertools
options = Options()
options.binary_location = r'C:\Program Files\BraveSoftware\Brave-Browser\Application\brave.exe'
driver = webdriver.Chrome(options = options, service = Service("chromedriver.exe"))
key_word = "BR1".lower()
base_url = f"https://www.rightmove.co.uk/house-prices/{key_word}.html?page=1"
driver.get(base_url)
#Number of pages
pages = driver.find_element(By.XPATH, '//span[#class="pagination-label"][2]').text
pages = int(pages.strip('of'))
WebDriverWait(driver, 15).until(
EC.presence_of_element_located((By.CLASS_NAME, 'results '))
)
data = []
pc = 0
for p in range(1,pages+1):
driver.get(f"https://www.rightmove.co.uk/house-prices/{key_word}.html?page={p}")
WebDriverWait(driver, 10).until(
EC.presence_of_element_located((By.XPATH, '//div//div[#class="propertyCard"]'))
)
propertyCards = driver.find_elements(By.XPATH, '//div//div[#class="propertyCard"]')
for propertyCard in propertyCards:
title = propertyCard.find_element(By.CLASS_NAME, 'title').text
propertyType = propertyCard.find_element(By.CLASS_NAME, 'propertyType').text
price_list = propertyCard.find_elements(By.CLASS_NAME, 'price')
date_list = propertyCard.find_elements(By.CLASS_NAME, 'date-sold')
data.append([title,propertyType])
for p, d in itertools.zip_longest(price_list, date_list , fillvalue = None):
try:
price = p.text
date = d.text
data[pc].append((price, date))
except Exception as e:
print(e)
pc+=1
time.sleep(random.randint(1,4))
print(data)
with open('rightmove.csv', 'w') as file:
header = "Title;propertyType;Price_Date\n"
file.write(header)
for record in data:
file.write("{};{};{}\n".format(record[0],record[1],record[2:]))
driver.quit()
You don't have to go down to dom elem by elem, you can just use xpath or class_name (if it's unique, otherwise it's better xpath or css-selector) and get the item you are looking for.
Anyway follow this:
import time
import selenium.webdriver as webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
driver = webdriver.Chrome("/usr/local/bin/chromedriver")
driver.get("https://www.rightmove.co.uk/house-prices.html")
# send query
query = "BR1"
search_bar = driver.find_element(By.XPATH, '//input[#class="searchBox ac_input"]')
search_bar.send_keys(query)
search_bar.send_keys(Keys.ENTER)
# wait to result been loaded
WebDriverWait(driver, 10).until(
EC.presence_of_element_located((By.CLASS_NAME, 'propertyCard'))
)
#get amount of pages
pages = driver.find_element(By.XPATH, '//span[#class="pagination-label"][2]').text
pages = int(pages.replace('of ', ''))
data = []
i = 1
while i <= pages:
WebDriverWait(driver, 10).until(
EC.element_to_be_clickable((By.XPATH, '//div[contains(text(), "Next")]'))
).click()
# wait page load result
WebDriverWait(driver, 10).until(
EC.presence_of_element_located((By.XPATH, '//div//div[#class="propertyCard"]'))
)
propertyCards = driver.find_elements(By.XPATH, '//div//div[#class="propertyCard"]')
# loop over result and store data
for propertyCard in propertyCards:
title = propertyCard.find_element(By.CLASS_NAME, 'title').text
propertyType = propertyCard.find_element(By.CLASS_NAME, 'propertyType').text
data.append((title, propertyType))
time.sleep(1)
i += 1
print("you reach the last page")
#get number of results
printf(data)
driver.close()
I use a list of tuple cause in your example you want store 2 item, if you want store more data you can use a dict and then convert into csv with Dictwriter directly. Enjoy.
I am currently learning Python in order to webscrape and am running into an issue with my current script. After closing the pop-up on Page 2 of Indeed and cycling through the pages, the script only returns one page into the data frame to CSV. However, it does print out each page in my terminal area. It also on occasion only returns part of the data from a page. EX page 2 will return info for the first 3 jobs as part of my print(df_da), but nothing for the next 12. Additionally, it seems to take a very long time to run the script (averaging around 6 minutes and 45 seconds for the 5 pages, around 1 minute to 1.5 minutes per page). Any suggestions? I've attached my script and can also attach the return I get from my Print(df_da) if needed below. Thank you in advance!
import pandas as pd
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
options = Options()
options.add_argument("window-size=1400,1400")
PATH = "C://Program Files (x86)//chromedriver.exe"
driver = webdriver.Chrome(PATH)
for i in range(0,50,10):
driver.get('https://www.indeed.com/jobs?q=chemical%20engineer&l=united%20states&start='+str(i))
driver.implicitly_wait(5)
jobtitles = []
companies = []
locations = []
descriptions = []
jobs = driver.find_elements_by_class_name("slider_container")
for job in jobs:
jobtitle = job.find_element_by_class_name('jobTitle').text.replace("new", "").strip()
jobtitles.append(jobtitle)
company = job.find_element_by_class_name('companyName').text.replace("new", "").strip()
companies.append(company)
location = job.find_element_by_class_name('companyLocation').text.replace("new", "").strip()
locations.append(location)
description = job.find_element_by_class_name('job-snippet').text.replace("new", "").strip()
descriptions.append(description)
try:
WebDriverWait(driver, 5).until(EC.visibility_of_element_located((By.CSS_SELECTOR, "button.popover-x-button-close.icl-CloseButton"))).click()
except:
pass
df_da=pd.DataFrame()
df_da['JobTitle']=jobtitles
df_da['Company']=companies
df_da['Location']=locations
df_da['Description']=descriptions
print(df_da)
df_da.to_csv('C:/Users/Dan/Desktop/AZNext/file_name1.csv')
You are defining the df_da inside the outer for loop so that the df_da will contain the data from the last page only.
You should define it out of the loops and put the total data there only after all the data have been collected.
I guess you are getting not all the jobs on the second page because of the pop-up. So, you should close it before collecting the job details on that page.
Also, you can reduce waiting for the pop-up element from all the loop iterations and leave it for the second loop iteration only.
Your code can be something like this:
import pandas as pd
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
options = Options()
options.add_argument("window-size=1400,1400")
PATH = "C://Program Files (x86)//chromedriver.exe"
driver = webdriver.Chrome(PATH)
jobtitles = []
companies = []
locations = []
descriptions = []
for i in range(0,50,10):
driver.get('https://www.indeed.com/jobs?q=chemical%20engineer&l=united%20states&start='+str(i))
driver.implicitly_wait(5)
jobs = driver.find_elements_by_class_name("slider_container")
for idx, job in enumerate(jobs):
if(idx == 1):
try:
WebDriverWait(driver, 5).until(EC.visibility_of_element_located((By.CSS_SELECTOR, "button.popover-x-button-close.icl-CloseButton"))).click()
except:
pass
jobtitle = job.find_element_by_class_name('jobTitle').text.replace("new", "").strip()
jobtitles.append(jobtitle)
company = job.find_element_by_class_name('companyName').text.replace("new", "").strip()
companies.append(company)
location = job.find_element_by_class_name('companyLocation').text.replace("new", "").strip()
locations.append(location)
description = job.find_element_by_class_name('job-snippet').text.replace("new", "").strip()
descriptions.append(description)
df_da=pd.DataFrame()
df_da['JobTitle']=jobtitles
df_da['Company']=companies
df_da['Location']=locations
df_da['Description']=descriptions
print(df_da)
df_da.to_csv('C:/Users/Dan/Desktop/AZNext/file_name1.csv')
I placed the code of a complete and properly functioning scraping that I own. Successfully scrapes all elements on the page.
However, I would like to scrape only a small limited section of the page with the same elements as scraping. This limited section is already scraped correctly along with all elements of the page, but I would like to scrape only it and not "all + it". The link is here
There are 4 tables on the page, but I would like to scrape just one, that is the table called "Programma", ie the html section "event-summary event" or "leagues-static event-summary-leagues ". But of this section only the elements of the last round (Matchday 14). Matchday 14 only. No round 15. So obviously that with each update of the page rounds, the last round is always scraped as well.
So I would need to insert something that makes scraping understand to download only the elements (which it already owns and scrapes) of of that section and the last round.
The code is already complete and works fine, so I'm not looking for code services, but for a little hint to tell me how to limit the scraping to just the section mentioned above. Scraping is in Selenium. I would like to stick with Selenium and my code as it is already functional and complete. Thanks
import selenium
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
driver = webdriver.Firefox()
driver.get("url")
driver.implicitly_wait(12)
#driver.minimize_window()
wait = WebDriverWait(driver, 10)
all_rows = driver.find_elements(By.CSS_SELECTOR, "div[class^='event__round'],div[class^='event__match']")
current_round = '?'
for bundesliga in all_rows:
classes = bundesliga.get_attribute('class')
#print(classes)
if 'event__round' in classes:
#round = row.find_elements(By.CSS_SELECTOR, "[class^='event__round event__round--static']")
#current_round = row.text # full text `Round 20`
current_round = bundesliga.text.split(" ")[-1] # only `20` without `Round`
else:
datetime = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__time']")
#Divide la data e l'ora
date, time = datetime.text.split(" ")
date = date.rstrip('.') # right-strip to remove `.` at the end of date
team_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__participant event__participant--home']")
team_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__participant event__participant--away']")
score_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--home']")
score_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--away']")
bundesliga = [current_round, date, time, team_home.text, team_away.text, score_home.text, score_away.text]
bundesliga.append(bundesliga)
print(bundesliga)
I think all you need to do is limit all_rows variable. One way to do this is finding the tab you are looking for with text and then getting the parent elements.
import selenium
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import TimeoutException, NoSuchElementException
driver = webdriver.Firefox()
driver.get("https://www.someurl/some/other/page")
driver.implicitly_wait(12)
#driver.minimize_window()
wait = WebDriverWait(driver, 10)
# all_rows = driver.find_elements(By.CSS_SELECTOR, "div[class^='event__round'],div[class^='event__match']")
############### UPDATE ####################
def parent_element(element):
return element.find_element(By.XPATH, './..')
programma_element = WebDriverWait(driver, 10).until(
EC.visibility_of_element_located((By.XPATH, "//div[text()='Programma']")))
programma_element_p1 = parent_element(programma_element)
programma_element_p2 = parent_element(programma_element_p1)
programma_element_p3 = parent_element(programma_element_p2)
all_rows = programma_element_p3.find_elements(By.CSS_SELECTOR, "div[class^='event__round'],div[class^='event__match']")
filter_rows = []
for row in all_rows:
if "event__match--last" in row.get_attribute('class'):
filter_rows.append(row)
break
else:
filter_rows.append(row)
############### UPDATE ####################
current_round = '?'
for bundesliga in filter_rows:
classes = bundesliga.get_attribute('class')
#print(classes)
if 'event__round' in classes:
#round = row.find_elements(By.CSS_SELECTOR, "[class^='event__round event__round--static']")
#current_round = row.text # full text `Round 20`
current_round = bundesliga.text.split(" ")[-1] # only `20` without `Round`
else:
datetime = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__time']")
#Divide la data e l'ora
date, time = datetime.text.split(" ")
date = date.rstrip('.') # right-strip to remove `.` at the end of date
team_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__participant event__participant--home']")
team_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__participant event__participant--away']")
# score_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--home']")
# score_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--away']")
try:
score_home = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--home']")
except (TimeoutException, NoSuchElementException):
MyObject = type('MyObject', (object,), {})
score_home = MyObject()
score_home.text = "-"
try:
score_away = bundesliga.find_element(By.CSS_SELECTOR, "[class^='event__score event__score--away']")
except (TimeoutException, NoSuchElementException):
MyObject = type('MyObject', (object,), {})
score_away = MyObject()
score_away.text = "-"
bundesliga = [current_round, date, time, team_home.text, team_away.text, score_home.text, score_away.text]
bundesliga.append(bundesliga)
print(bundesliga)
So i am working on a custom web scraper for any kind of ecommerce site, i want it to scrape names and prices of listings on a site and then export them to csv, but the problem is it exports only one line of (name, price) and it prints it on every line of csv, i couldnt find a good solution for this, i hope im not asking an extremely stupid thing, although i think the fix is easy. I hope someone will read my code and help me, thank you !
###imports
from selenium.webdriver.common.keys import Keys
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import time
import csv
import pandas as pd
#driver path
driver = webdriver.Firefox(executable_path="D:\Programy\geckoDriver\geckodriver.exe")
#init + search
driver.get("https://pc.bazos.sk/pc/")
time.sleep(1)
nazov = driver.find_element_by_name("hledat")
nazov.send_keys("xeon")
cenamin = driver.find_element_by_name("cenaod")
cenamin.send_keys("")
cenamax = driver.find_element_by_name("cenado")
cenamax.send_keys("300")
driver.find_element_by_name("Submit").click()
##cookie acceptor
driver.find_element_by_xpath("/html/body/div[1]/button").click()
##main
x = 3
for i in range(x):
try:
main = WebDriverWait(driver, 7).until(
EC.presence_of_element_located((By.XPATH, "/html/body/div[1]/table/tbody/tr/td[2]"))
)
##find listings in table
inzeraty = main.find_elements_by_class_name("vypis")
for vypis in inzeraty:
nadpis = vypis.find_element_by_class_name("nadpis")
##print listings to check correctness
nadpist = nadpis.text
print(nadpist)
##find the price and print
for vypis in inzeraty:
cena = vypis.find_element_by_class_name("cena")
cenat = cena.text
print(cenat)
##export to csv - not working
time.sleep(1)
print("Writing to csv")
d = {"Nazov": [nadpist]*20*x,"Cena": [cenat]*20*x}
df = pd.DataFrame(data=d)
df.to_csv("bobo.csv")
time.sleep(1)
print("Writing to csv done !")
##next page
dalsia = driver.find_element_by_link_text("Ďalšia")
dalsia.click()
except:
driver.quit()
i want the csv to look like:
name,price
name2, price2
it would be great is the csv had only two columns and x rows depending on the number of listings
from selenium.webdriver.common.keys import Keys
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import time
import pandas as pd
#driver path
driver = webdriver.Chrome()
#init + search
driver.get("https://pc.bazos.sk/pc/")
time.sleep(1)
nazov = driver.find_element_by_name("hledat")
nazov.send_keys("xeon")
cenamin = driver.find_element_by_name("cenaod")
cenamin.send_keys("")
cenamax = driver.find_element_by_name("cenado")
cenamax.send_keys("300")
driver.find_element_by_name("Submit").click()
##cookie acceptor
time.sleep(10)
driver.find_element_by_xpath("/html/body/div[1]/button").click()
##main
x = 3
d = []
for i in range(x):
try:
main = WebDriverWait(driver, 7).until(
EC.presence_of_element_located(
(By.XPATH, "/html/body/div[1]/table/tbody/tr/td[2]")))
##find listings in table
inzeraty = main.find_elements_by_class_name("vypis")
for vypis in inzeraty:
d.append({"Nazov": vypis.find_element_by_class_name("nadpis").text,
"Cena": vypis.find_element_by_class_name("cena").text
})
##next page
dalsia = driver.find_element_by_link_text("Ďalšia")
dalsia.click()
except:
driver.quit()
time.sleep(1)
print("Writing to csv")
df = pd.DataFrame(data=d)
df.to_csv("bobo.csv",index=False)
this gives me 59 items with price. first added to dict then to list, then send that to pandas.
All you need to do is create two empty lists nadpist_l, cenat_l and append data to that lists, finally save the lists as a dataframe.
UPDATED as per the comment
Check if this works
###imports
from selenium.webdriver.common.keys import Keys
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
import time
import pandas as pd
#driver path
driver = webdriver.Chrome()
#init + search
driver.get("https://pc.bazos.sk/pc/")
time.sleep(1)
nazov = driver.find_element_by_name("hledat")
nazov.send_keys("xeon")
cenamin = driver.find_element_by_name("cenaod")
cenamin.send_keys("")
cenamax = driver.find_element_by_name("cenado")
cenamax.send_keys("300")
driver.find_element_by_name("Submit").click()
##cookie acceptor
time.sleep(10)
driver.find_element_by_xpath("/html/body/div[1]/button").click()
##main
x = 3
d = {}
for i in range(x):
try:
main = WebDriverWait(driver, 7).until(
EC.presence_of_element_located(
(By.XPATH, "/html/body/div[1]/table/tbody/tr/td[2]")))
##find listings in table
inzeraty = main.find_elements_by_class_name("vypis")
nadpist_l = []
for vypis in inzeraty:
nadpis = vypis.find_element_by_class_name("nadpis")
##print listings to check correctness
nadpist = nadpis.text
nadpist_l.append(nadpist)
# print(nadpist)
##find the price and print
cenat_l = []
for vypis in inzeraty:
cena = vypis.find_element_by_class_name("cena")
cenat = cena.text
cenat_l.append(cenat)
print(len(cenat_l))
##export to csv - not working
d.update({"Nazov": [nadpist_l] * 20 * x, "Cena": [cenat_l] * 20 * x})
##next page
dalsia = driver.find_element_by_link_text("Ďalšia")
dalsia.click()
except:
driver.quit()
time.sleep(1)
print("Writing to csv")
df = pd.DataFrame(data=d)
df.to_csv("bobo.csv")
time.sleep(1)
print("Writing to csv done !")
Actually i want to get the value from here. Getting product hyper link is working fine. i want to get product information, price etc.. from above link in same in for loop. How to put result data into CSV file. please help me.
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.common.by import By
import time
chrome_path = r"C:\Users\Venkatesh\AppData\Local\Programs\Python\Python35\chromedriver.exe"
driver = webdriver.Chrome(chrome_path)
driver.get("https://www.flipkart.com/mobiles")
search = driver.find_element_by_xpath("""//*[#id="container"]/div/div[2]/div/div[2]/div/div/div[1]/section/div[3]/div/div/a""").click()
delay = 20 # seconds
try:
WebDriverWait(driver, delay).until(EC.presence_of_element_located((By.XPATH, "//*[#id='container']/div/div[2]/div[2]/div/div[2]/div/div[3]/div[1]/div/div[1]/a/div[2]/div[1]/div[1]")))
driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
print("Page is ready")
except TimeoutException:
print("Loading took too much time")
time.sleep(10)
for post in driver.find_elements_by_class_name("_1UoZlX"):
print(post.get_attribute("href"))
time.sleep(2)
driver.quit()
Output:
Page is ready
https://www.flipkart.com/moto-g5-plus-fine-gold-32-gb/p/itmes2zjvwfncxxr?pid=MOBEQHMGED7F9CZ2&srno=b_1_1&otracker=browse
&lid=LSTMOBEQHMGED7F9CZ2KHTBI8
https://www.flipkart.com/moto-g5-plus-lunar-grey-32-gb/p/itmes2zjvwfncxxr?pid=MOBEQHMGMAUXS5BF&srno=b_1_2&otracker=brows
e&lid=LSTMOBEQHMGMAUXS5BFVCF0ZO
https://www.flipkart.com/moto-e3-power-black-16-gb/p/itmekgt2fbywqgcv?pid=MOBEKGT2HGDGADFW&srno=b_1_3&otracker=browse&li
d=LSTMOBEKGT2HGDGADFWP5NHBY
https://www.flipkart.com/micromax-bolt-q381-plus-coffee-16-gb/p/itmeskgycnfghsat?pid=MOBESAMDG2GNUBC5&srno=b_1_4&otracke
r=browse&lid=LSTMOBESAMDG2GNUBC5KRPH8Q
https://www.flipkart.com/lenovo-k6-power-grey-dark-grey-32-gb/p/itmezenfhm4mvptw?pid=MOBEZENFZBPW8UMF&srno=b_1_5&otracke
r=browse&lid=LSTMOBEZENFZBPW8UMF7P8NY0
https://www.flipkart.com/lenovo-k6-power-gold-32-gb/p/itmezenfhm4mvptw?pid=MOBEZEMYH7FQBGBQ&srno=b_1_6&otracker=browse&l
id=LSTMOBEZEMYH7FQBGBQRHVU0S
https://www.flipkart.com/lenovo-k6-power-silver-32-gb/p/itmezenfhm4mvptw?pid=MOBEZEMX6CZHCJVY&srno=b_1_7&otracker=browse
&lid=LSTMOBEZEMX6CZHCJVYOIBM0E
https://www.flipkart.com/lenovo-vibe-k5-note-grey-64-gb/p/itmepcfqfdx9bdxs?pid=MOBEPCFQRJ6KFYZS&srno=b_1_8&otracker=brow
se&lid=LSTMOBEPCFQRJ6KFYZSI4DRRB
https://www.flipkart.com/lenovo-vibe-k5-note-gold-64-gb/p/itmepcfqfdx9bdxs?pid=MOBEPCFQ3ZSYTRUZ&srno=b_1_9&otracker=brow
se&lid=LSTMOBEPCFQ3ZSYTRUZGFSZCU
https://www.flipkart.com/samsung-galaxy-nxt-gold-32-gb/p/itmemzd4gepexjya?pid=MOBEMZD4KHRF5VZX&srno=b_1_10&otracker=brow
se&lid=LSTMOBEMZD4KHRF5VZX7FNU5S
https://www.flipkart.com/moto-e3-power-white-16-gb/p/itmekgt23fgwdgkg?pid=MOBEKGT2SVHPAHTM&srno=b_1_11&otracker=browse&l
id=LSTMOBEKGT2SVHPAHTMJA8RQ1
https://www.flipkart.com/lenovo-k6-power-silver-32-gb/p/itmezenfghddrfmc?pid=MOBEZENFKXZ4HSCG&srno=b_1_12&otracker=brows
e&lid=LSTMOBEZENFKXZ4HSCGC1OOAM
https://www.flipkart.com/lenovo-k6-power-gold-32-gb/p/itmezenfghddrfmc?pid=MOBEZENFSZGTQGWF&srno=b_1_13&otracker=browse&
lid=LSTMOBEZENFSZGTQGWFUR1LY1
https://www.flipkart.com/lenovo-k6-power-dark-gray-32-gb/p/itmezenfghddrfmc?pid=MOBEZENFG8BPDPSU&srno=b_1_14&otracker=br
owse&lid=LSTMOBEZENFG8BPDPSUUANLO6
https://www.flipkart.com/lava-arc-blue/p/itmezgyfszhmwfzt?pid=MOBEF6D24ZT6YHFJ&srno=b_1_15&otracker=browse&lid=LSTMOBEF6
D24ZT6YHFJZ6N7XC
https://www.flipkart.com/lenovo-vibe-k5-plus-3-gb-silver-16-gb/p/itmektn3t9rg9hnn?pid=MOBEKEF8ATFZZ8GN&srno=b_1_16&otrac
ker=browse&lid=LSTMOBEKEF8ATFZZ8GNY7WZBU
https://www.flipkart.com/lenovo-vibe-k5-plus-3-gb-gold-16-gb/p/itmektn3t9rg9hnn?pid=MOBEKEF8JYGKZCTF&srno=b_1_17&otracke
r=browse&lid=LSTMOBEKEF8JYGKZCTFUTCYS4
https://www.flipkart.com/lenovo-vibe-k5-plus-3-gb-dark-grey-16-gb/p/itmektn3t9rg9hnn?pid=MOBEKEF86VVUE8G2&srno=b_1_18&ot
racker=browse&lid=LSTMOBEKEF86VVUE8G2YCW5OP
https://www.flipkart.com/samsung-galaxy-nxt-black-32-gb/p/itmemzd4byrufyu7?pid=MOBEMZD4G83T5HKZ&srno=b_1_19&otracker=bro
wse&lid=LSTMOBEMZD4G83T5HKZVMFKK6
https://www.flipkart.com/samsung-galaxy-on8-gold-16-gb/p/itmemvarkqg5dyay?pid=MOBEMJR2NDM4EAHQ&srno=b_1_20&otracker=brow
se&lid=LSTMOBEMJR2NDM4EAHQ8BMJIN
https://www.flipkart.com/samsung-galaxy-on7-black-8-gb/p/itmedhx3jgmu2gps?pid=MOBECCA5SMRSKCNY&srno=b_1_21&otracker=brow
se&lid=LSTMOBECCA5SMRSKCNYWC8DYC
https://www.flipkart.com/samsung-galaxy-on7-gold-8-gb/p/itmedhx3jgmu2gps?pid=MOBECCA5Y5HBYR3Q&srno=b_1_22&otracker=brows
e&lid=LSTMOBECCA5Y5HBYR3QPDPGLJ
https://www.flipkart.com/samsung-galaxy-on5-gold-8-gb/p/itmedhx3uy3qsfks?pid=MOBECCA5FHQD43KA&srno=b_1_23&otracker=brows
e&lid=LSTMOBECCA5FHQD43KAFXOZYB
https://www.flipkart.com/lenovo-p2-gold-32-gb/p/itmeq5ygvgq9vyfn?pid=MOBEZFHHURMWYSFN&srno=b_1_24&otracker=browse&lid=LS
TMOBEZFHHURMWYSFNBBG6L0
https://www.flipkart.com/asus-zenfone-max-black-32-gb/p/itmege3d5pjpmknc?pid=MOBEGE3DYZM3ZYWB&srno=b_1_25&otracker=brows
e&lid=LSTMOBEGE3DYZM3ZYWBPCOZHP
https://www.flipkart.com/lenovo-vibe-k5-note-grey-32-gb/p/itmejj6kmhh2khk9?pid=MOBEJJ6KYARZGWJC&srno=b_1_26&otracker=bro
wse&lid=LSTMOBEJJ6KYARZGWJCCV4LRX
https://www.flipkart.com/swipe-elite-sense-4g-volte/p/itmeh6yfycypxfdz?pid=MOBEH6YFZYZZNCZK&srno=b_1_27&otracker=browse&
lid=LSTMOBEH6YFZYZZNCZKWVY6ES
https://www.flipkart.com/swipe-elite-sense-4g-volte/p/itmeh6yfycypxfdz?pid=MOBEH6YFZRTEMDBG&srno=b_1_28&otracker=browse&
lid=LSTMOBEH6YFZRTEMDBGYJNCJI
https://www.flipkart.com/xolo-era-1x-4g-volte-black-gun-metal-8-gb/p/itmerhq8uhtehukg?pid=MOBEHMEKGCZCGMB8&srno=b_1_29&o
tracker=browse&lid=LSTMOBEHMEKGCZCGMB8DCWHIY
https://www.flipkart.com/swipe-konnect-grand-black-8-gb/p/itmeqcgxvkyfzsgj?pid=MOBEQCGXN6HTZE2C&srno=b_1_30&otracker=bro
wse&lid=LSTMOBEQCGXN6HTZE2CXUT5W1
https://www.flipkart.com/lenovo-vibe-k5-note-gold-32-gb/p/itmejj6kczvxej4g?pid=MOBEJJ6K5A3GQ9SU&srno=b_1_31&otracker=bro
wse&lid=LSTMOBEJJ6K5A3GQ9SUZERSAR
https://www.flipkart.com/lyf-water-f1-black-32-gb/p/itmezh76z9jqsa8z?pid=MOBEZH76AFWSZVNH&srno=b_1_32&otracker=browse&li
d=LSTMOBEZH76AFWSZVNHOOBURN
https://www.flipkart.com/samsung-galaxy-j5-6-new-2016-edition-black-16-gb/p/itmegmrnzqjcpfg9?pid=MOBEG4XWHJDWMQDF&srno=b
_1_33&otracker=browse&lid=LSTMOBEG4XWHJDWMQDFZIWO93
https://www.flipkart.com/samsung-galaxy-j5-6-new-2016-edition-white-16-gb/p/itmegmrnzqjcpfg9?pid=MOBEG4XWJG7F9A6Z&srno=b
_1_34&otracker=browse&lid=LSTMOBEG4XWJG7F9A6ZHJOVBG
https://www.flipkart.com/samsung-galaxy-j5-6-new-2016-edition-gold-16-gb/p/itmegmrnzqjcpfg9?pid=MOBEG4XWFTBRMMBY&srno=b_
1_35&otracker=browse&lid=LSTMOBEG4XWFTBRMMBYZPYEGS
https://www.flipkart.com/moto-m-grey-64-gb/p/itmenqavgcezzk2y?pid=MOBENQATHQTKG7AV&srno=b_1_36&otracker=browse&lid=LSTMO
BENQATHQTKG7AVGFQI4N
https://www.flipkart.com/moto-m-gold-64-gb/p/itmenqavgcezzk2y?pid=MOBENQAVANRMEGAP&srno=b_1_37&otracker=browse&lid=LSTMO
BENQAVANRMEGAPHWU47I
https://www.flipkart.com/moto-m-silver-64-gb/p/itmenqavgcezzk2y?pid=MOBENQAVFTG6FPXX&srno=b_1_38&otracker=browse&lid=LST
MOBENQAVFTG6FPXXHZBIGV
https://www.flipkart.com/apple-iphone-6-silver-16-gb/p/itme8dvfeuxxbm4r?pid=MOBEYHZ2NUZGCHKN&srno=b_1_39&otracker=browse
&lid=LSTMOBEYHZ2NUZGCHKN7PMDIN
https://www.flipkart.com/samsung-galaxy-on8-black-16-gb/p/itmemvarprh8hegn?pid=MOBEMJRFZXZBESQW&srno=b_1_40&otracker=bro
wse&lid=LSTMOBEMJRFZXZBESQWCFHWJ0
https://www.flipkart.com/panasonic-eluga-tapp-silver-grey-16-gb/p/itmezf54ey3gf8ne?pid=MOBENRHGWZWKEGGF&srno=b_1_41&otra
cker=browse&lid=LSTMOBENRHGWZWKEGGFMJELY2
https://www.flipkart.com/panasonic-eluga-tapp-champagne-gold-16-gb/p/itmezf54ey3gf8ne?pid=MOBENRHGEQEJHSZM&srno=b_1_42&o
tracker=browse&lid=LSTMOBENRHGEQEJHSZMD8R5FE
https://www.flipkart.com/apple-iphone-6s-rose-gold-32-gb/p/itmen2yymnfcrxsz?pid=MOBEN2XYK8WFEGM8&srno=b_1_43&otracker=br
owse&lid=LSTMOBEN2XYK8WFEGM8QJW5XA
https://www.flipkart.com/lenovo-p2-grey-graphite-grey-32-gb/p/itmeq5ygvgq9vyfn?pid=MOBEZFHH2JYGXSNF&srno=b_1_44&otracker
=browse&lid=LSTMOBEZFHH2JYGXSNFNWKEAD
https://www.flipkart.com/forme-n1/p/itmeff8s2hdrfhyg?pid=MOBEFF8SHZPYKCRY&srno=b_1_45&otracker=browse&lid=LSTMOBEFF8SHZP
YKCRYEKQPPR
https://www.flipkart.com/forme-n1/p/itmeff8s2hdrfhyg?pid=MOBEFF8SSZNHCUND&srno=b_1_46&otracker=browse&lid=LSTMOBEFF8SSZN
HCUNDRC6GLT
https://www.flipkart.com/samsung-galaxy-on5-black-8-gb/p/itmekszmsqgpgygy?pid=MOBECCA5BJUVUGNP&srno=b_1_47&otracker=brow
se&lid=LSTMOBECCA5BJUVUGNPRKEGMG
https://www.flipkart.com/lenovo-p2-grey-graphite-grey-32-gb/p/itmeq5ygebzgqgfb?pid=MOBEZFHHVD8KXE7G&srno=b_1_48&otracker
=browse&lid=LSTMOBEZFHHVD8KXE7GB0OS6I
https://www.flipkart.com/lenovo-p2-gold-32-gb/p/itmeq5ygebzgqgfb?pid=MOBEZFHHGE2RXQUY&srno=b_1_49&otracker=browse&lid=LS
TMOBEZFHHGE2RXQUY2XDB97
https://www.flipkart.com/samsung-galaxy-j7-gold-16-gb/p/itmeafbfjhsydbpw?pid=MOBE93GWSMGZHFSK&srno=b_1_50&otracker=brows
e&lid=LSTMOBE93GWSMGZHFSKT6OZOB
https://www.flipkart.com/samsung-z2-gold-8-gb/p/itmenkygvprd5dwt?pid=MOBENKYGHFUHT6BH&srno=b_1_51&otracker=browse&lid=LS
TMOBENKYGHFUHT6BHVSHMDE
https://www.flipkart.com/leeco-le-2-grey-32-gb/p/itmejeucxaxmnk8k?pid=MOBEJFTH4C9Z2YZR&srno=b_1_52&otracker=browse&lid=L
STMOBEJFTH4C9Z2YZRVVL0EL
https://www.flipkart.com/lyf-water-10-black-16-gb/p/itmemj7d8qfkfu4r?pid=MOBEMJ7C7YMDMVDQ&srno=b_1_53&otracker=browse&li
d=LSTMOBEMJ7C7YMDMVDQPCFALX
https://www.flipkart.com/micromax-canvas-nitro-2-grey-silver-16-gb/p/itme7nhzw56hv2ga?pid=MOBE7NHZP7GHZ7SG&srno=b_1_54&o
tracker=browse&lid=LSTMOBE7NHZP7GHZ7SGCYGNI3
https://www.flipkart.com/moto-g-turbo-white-16-gb/p/itmecc4uhbue7ve6?pid=MOBECC4UQTJ5QZFR&srno=b_1_55&otracker=browse&li
d=LSTMOBECC4UQTJ5QZFR9CAUPO
https://www.flipkart.com/moto-g-turbo-black-16-gb/p/itmecc4uhbue7ve6?pid=MOBECC4UZTSGKWWZ&srno=b_1_56&otracker=browse&li
d=LSTMOBECC4UZTSGKWWZOQKAIZ
https://www.flipkart.com/apple-iphone-6-space-grey-16-gb/p/itme8dvfeuxxbm4r?pid=MOBEYHZ2YAXZMF2J&srno=b_1_57&otracker=br
owse&lid=LSTMOBEYHZ2YAXZMF2JEVWVNC
https://www.flipkart.com/yu-yunicorn-rush-silver-32-gb/p/itmenffyjfp8ubyg?pid=MOBEJ3MFUQAF8XJS&srno=b_1_58&otracker=brow
se&lid=LSTMOBEJ3MFUQAF8XJSBPC8L4
https://www.flipkart.com/yu-yunicorn-gold-rush-32-gb/p/itmenffyjfp8ubyg?pid=MOBEJ3MF23Q9MGMH&srno=b_1_59&otracker=browse
&lid=LSTMOBEJ3MF23Q9MGMHZ49MG2
https://www.flipkart.com/micromax-canvas-nitro-2-white-gold-16-gb/p/itme7nhzw56hv2ga?pid=MOBE8TJBHGQYHNPT&srno=b_1_60&ot
racker=browse&lid=LSTMOBE8TJBHGQYHNPTVL3HS0
Used openpyxl to create a csv for each run with the filename+timestamp. Links that are fetched are written to the csv file eventually.
I couldn't find the exact links that have been given and hence I chose my own links which are similar in case. This code has different links per se, but the solution scales up to be same for your case #venkatesh
One more thing: Try to keep xpaths as relative as possible, and the classes with such gibberish as _13oc-S Would not hold good as they tend to change dynamically for each DOM refresh or each browser instance.
from webdriver_manager.chrome import ChromeDriverManager
from selenium import webdriver
from selenium.webdriver.common.by import By
import time
import openpyxl
current_time = time.strftime('%Y%m%d%H%M%S')
xlpath = "linktracker" + current_time + ".csv"
driver = webdriver.Chrome(ChromeDriverManager().install())
driver.get("https://www.flipkart.com/mobiles")
driver.maximize_window()
# Searches for a certain brand of phpnes (POCO). Inefficient way of locator finding though
search = driver.find_element(By.XPATH, "(//*[#alt='Shop Now'])[2]").click()
time.sleep(10) # bad practice, but used for now. Webdriverwait to be used instead.
each_element = "//a[#rel='noopener noreferrer']" # locates each desired element in the search page (each phone block)
posts = driver.find_elements(By.XPATH, each_element)
print(len(posts))
ls=[]
for post in range(len(posts)-1): # len-1 because the last item is a footer and not the desired link in my view
# concatanates the subscript to element xpath: e.g.: (//*[#element = 'ele'])[1] ... (//*[#element = 'ele'])[n]
each_post = driver.find_element(By.XPATH, '(' + each_element + ')' + '[' + str(post + 1) + ']')
each_link = each_post.get_attribute("href")
ls.append(each_link)
wb = openpyxl.Workbook() # creates a workbook
sheet = wb.active
c=0
# looping through the created list and writing the values to the created workbook
for i in ls:
sheet.cell(row=c+1, column=1).value = i
c+=1 # incrementing the row for each iteration of i
wb.save(xlpath) # saving the workbook with the name as given in the xlpath variable above
driver.quit()
Result in csv - image