Scrape amazon.in

Web Scrape e-commerce site complete.py

#importing libraries
import selenium
from selenium import webdriver as wb
from selenium.webdriver.support.ui import Select
import pandas as pd
import time

#Opening Chrome browser
wbD=wb.Chrome('chromedriver.exe')

#Opening webpage
wbD.get('https://www.amazon.in/s?bbn=1389396031&rh=n%3A976419031%2Cn%3A%21976420031%2Cn%3A1389375031%2Cn%3A1389396031%2Cn%3A15747864031&dc&fst=as%3Aoff&qid=1596287247&rnid=1389396031&ref=lp_1389396031_nr_n_1')

#Running loop to store the product links in a list
listOflinks =[]
condition =True
while condition:
    time.sleep(3)
    productInfoList=webD.find_elements_by_class_name('a-size-mini')
    for el in productInfoList:
        if(el.text !="" and el.text !="Sponsored"):
            pp2=el.find_element_by_tag_name('a')
            listOflinks.append(pp2.get_property('href'))
    try:
        wbD.find_element_by_class_name('a-last').find_element_by_tag_name('a').get_property('href')
        wbD.find_element_by_class_name('a-last').click()
    except:
        condition=False

len(listOflinks)

#scraping individual product details
from tqdm import tqdm
alldetails=[]
brand=""
model=""

for i in tqdm(listOflinks):
    wbD.get(i)
    time.sleep(3)
    sku = wbD.find_element_by_xpath('//*[@id="productTitle"]').text
    category= wbD.find_element_by_xpath('//*[@id="wayfinding-breadcrumbs_feature_div"]/ul/li[7]/span/a').text
    try:
        try:
            price = wbD.find_element_by_xpath('//*[@id="priceblock_ourprice"]').text
        except:
            price = wbD.find_element_by_xpath('//*[@id="priceblock_dealprice"]').text
    except:
        price=""
        
    pp=wbD.find_element_by_class_name('pdTab')
    pp1=pp.find_elements_by_tag_name('tr')
    for el in range(len(pp1)-1):
        if (pp1[el].find_element_by_class_name("label").text) == 'Brand':
            brand= pp1[el].find_element_by_class_name("value").text
        if (pp1[el].find_element_by_class_name("label").text) == 'Model':
            model= pp1[el].find_element_by_class_name("value").text
        
    temp ={
        'SKU':sku,
        'Category':category,
        'Price':price,
        'Brand':brand,
        'Model':model,
        'linkofproduct':i}
    alldetails.append(temp)
    
#printing the DataFrame
pd.DataFrame(alldetails)

#export the DataFrame as .csv
data = pd.DataFrame(alldetails)
data.to_csv('Amazon_tv.csv')