Extract Data From JustDial using Selenium

Last Updated : 24 Oct, 2021

Let us see how to extract data from Justdial using Selenium and Python. Justdial is a company that provides local search for different services in India over the phone, website and mobile apps. In this article we will be extracting the following data:

Phone number
Name
Address

We can then save the data in a CSV file.

Approach:

Import the following modules: webdriver from selenium, ChromeDriverManager, pandas, time and os.
Use the driver.get() method and pass the link you want to get information from.
Use the driver.find_elements_by_class_name() method and pass ‘store-details’.
Instantiate empty lists to store the values.
Iterate the StoreDetails and start fetching the individual details that are required.
Create a user-defined function strings_to_number() to convert the extracted string to numbers.
Display the details and save them as a CSV file according to the requirements.

Python3

# importing the modules
from selenium import webdriver
from webdriver_manager.chrome import ChromeDriverManager
driver = webdriver.Chrome(ChromeDriverManager().install())
import pandas as pd
import time
import os
 
# driver.get method() will navigate to a page given by the URL address
driver.get("https://www.justdial.com/Delhi/Ceiling-Tile-Dealers-Armstrong/nct-11271379")
 
# the user-defined function
def strings_to_num(argument): 
     
    switcher = { 
        'dc': '+',
        'fe': '(',
        'hg': ')',
        'ba': '-',
        'acb': '0', 
        'yz': '1', 
        'wx': '2',
        'vu': '3',
        'ts': '4',
        'rq': '5',
        'po': '6',
        'nm': '7',
        'lk': '8',
        'ji': '9'
    } 
    return switcher.get(argument, "nothing")
 
# fetching all the store details
storeDetails = driver.find_elements_by_class_name('store-details')
 
# instantiating empty lists
nameList = []
addressList = []
numbersList = []
 
# iterating the storeDetails
for i in range(len(storeDetails)):
     
    # fetching the name, address and contact for each entry
    name = storeDetails[i].find_element_by_class_name('lng_cont_name').text
    address = storeDetails[i].find_element_by_class_name('cont_sw_addr').text
    contactList = storeDetails[i].find_elements_by_class_name('mobilesv')
     
    myList = []
     
    for j in range(len(contactList)):
         
        myString = contactList[j].get_attribute('class').split("-")[1]
     
        myList.append(strings_to_num(myString))
 
    nameList.append(name)
    addressList.append(address)
    numbersList.append("".join(myList))
     
# initialize data of lists.
data = {'Company Name': nameList,
        'Address': addressList,
        'Phone': numbersList}
 
# Create DataFrame
df = pd.DataFrame(data)
print(df)
 
# Save Data as .csv
df.to_csv('demo1.csv', mode = 'a', header = False)