[FIXED] How can I ignore (Bypass) an "Unable to locate element" exception?

Issue

I use Python Selenium for scraping a website, but my crawler stopped because of an exception:

selenium.common.exceptions.NoSuchElementException: Message: no such element: Unable to locate element: {"method":"css selector","selector":"[id="priceblock_ourprice"]"}

How can I continue to crawl even if the element is not attached?

My code:

from selenium import webdriver
browser = webdriver.Chrome()
#Product1
browser.get('https://www.amazon.com.tr/Behringer-High-Precision-Crossover-Limiters- 
Adjustable/dp/B07GSGYRK1/ref=sr_1_1?dchild=1&keywords=behringer+cx3400+v2&qid=1630311885&sr=8- 
1')
price = price = browser.find_element_by_id('priceblock_ourprice')
price.text
import numpy as np
import pandas as pd
df = pd.DataFrame([["info", "info", price.text]], columns=["Product", "Firm", "Price"])
df.to_csv('info.csv', encoding="utf-8", index=False, header=False)
df_final = pd.read_csv('info.csv')
df_final.head()
browser.quit()

Solution

If you want to continue scraping even if element is not found, you can use try-except block.

try:
   price = browser.find_element_by_id(id_).text
except:
   print("Price is not found.")
   price = "-"     # for dataframe

Alternatively you can create a function to check for the existence and act accordingly. One way to do it:

from selenium import webdriver
browser = webdriver.Chrome()
import numpy as np
import pandas as pd

def check_if_exists(browser, id_):
    return len(browser.find_elements_by_css_selector("#{}".format(id_))) > 0

browser.get('https://www.amazon.com.tr/Behringer-High-Precision-Crossover-Limiters-Adjustable/dp/B07GSGYRK1/ref=sr_1_1?dchild=1&keywords=behringer+cx3400+v2&qid=1630311885&sr=8-1')

id_ = 'priceblock_ourprice'
price =  browser.find_element_by_id(id_).text if check_if_exists(browser, id_) else "-"

df = pd.DataFrame([["info", "info", price]], columns=["Product", "Firm", "Price"])
df.to_csv('info.csv', encoding="utf-8", index=False, header=False)
df_final = pd.read_csv('info.csv')
df_final.head()
browser.quit()

Answered By - Muhteva