Create Scraping Flipkart Websit.py

Scraping Flipkart Websit.py

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+# gedit fk-web-s.py
+import requests 
+import sys 
+from bs4 import BeautifulSoup 
+import time
+from selenium import webdriver
+from bs4 import BeautifulSoup
+import pandas as pd
+# driver = webdriver.Chrome("/usr/lib/chromium-browser/chromedriver")
+# products=[] #List to store name of the product
+# prices=[] #List to store price of the product
+# ratings=[] #List to store rating of the product
+# driver.get("https://www.flipkart.com/laptops/~buyback-guarantee-on-laptops-/pr?sid=6bo%2Cb5g&uniq")
+# content = driver.page_source
+# soup = BeautifulSoup(content)
+# for a in soup.findAll('a',href=True, attrs={'class':'_31qSD5'}):
+#  name=a.find('div', attrs={'class':'_3wU53n'})
+#  price=a.find('div', attrs={'class':'_1vC4OE _2rQ-NK'})
+#  rating=a.find('div', attrs={'class':'hGSR34 _2beYZw'})
+#  products.append(name.text)
+#  prices.append(price.text)
+#  ratings.append(rating.text)
+# df = pd.DataFrame({'Product Name':products,'Price':prices,'Rating':ratings}) 
+# df.to_csv('products.csv', index=False, encoding='utf-8')
+
+
+payload = {'q':'laptop'} 
+r = requests.get('http://www.flipkart.com/search', params = payload) 
+data = r.content.decode(encoding='UTF-8') 
+f = open("flipkartdata.txt","w+",encoding='UTF-8') 
+f.write(data)
+soup = BeautifulSoup(r.content.decode(encoding='UTF-8'), "lxml")
+collection = soup.find_all("div", {"class": "_2kHMtA"})#input your class of the required search
+href = []
+for c in collection:
+ a = c.find("a")
+ href.append(a['href'])
+ #can store the data as such you want