Export contact from Justdial

 

Extract Data From JustDial using Selenium

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:

1. Import the following modules: webdriver from selenium, ChromeDriverManager, pandas, time and os.
2. Use the driver.get() method and pass the link you want to get information from.
3. Use the driver.find_elements_by_class_name() method and pass ‘store-details’.
4. Instantiate empty lists to store the values.
5. Iterate the StoreDetails and start fetching the individual details that are required.
6. Create a user-defined function strings_to_number() to convert the extracted string to numbers.
7. 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)