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How to Scrape Amazon Product Data Using Python ??

This Tutorial will explain you how we can extract product data from amazon. com using python amazon scraper

This Tutorial will explain you how we can extract product data from using python amazon scraper

Have you heard about amazon Data Scraping ?? It is a way to Scrape amazon Products data from by Automated way using python.

amazon data scraper provides updated product information along with changing prices, reviews ,and more..

We can perform amazon data scraping and Extract Following Data using python amazon data scraper.

  • Product title
  • URL
  • ASIN
  • UPC
  • Item Model Number
  • No Of Reviews
  • Sales Rank Final
  • No Of Ratings
  • product Description
  • Product Dimensions
  • Best Seller Rank
  • Shipping Weight
  • Category
  • Price

Screen shot of product page from we can extract data.

Inspecting element for data extractions from

To find appropriate data from website first we have to  inspecting and understanding html tag  which is associated with given data ..

please follow below steps to finding tags

  • Open browser (Google Chrome , Mozilla )
  • Copy and paste url you want to scrape.
  • Press F12 to view HTML structure of given site.,
  • find html tags for  require data and implement in python coding

Here we have explained for finding price tag how can we find it , like this  other tags can easily find…

How to set up your computer for web scraper development

We will use Python 3 for this tutorial. The code will not run if you are using Python 2.7. To start, you need a computer with Python 3 and PIP installed in it.

Let’s check your python version. Open a terminal ( in Linux and Mac OS ) or Command Prompt ( on Windows ) and type

python –version

and press enter. If the output looks something like Python 3.x.x, you have Python 3 installed. If it says Python 2.x.x you have Python 2. If it prints an error, you don’t probably have python installed.

If you don’t have Python 3, install it first.

Install Python 3 and Pip

Linux –

Mac Users can follow this guide –

Windows Users go here –

For PIP installation   visit this link  –

Install Packages

  • Python Requests, to make requests and download the HTML content of the pages (
  • Python LXML, for parsing the HTML Tree Structure using Xpath (Learn how to install that here –

Python Code to Scrape

import requests
from lxml import html
import requests.packages.urllib3.exceptions
import json
from urllib3.exceptions import InsecureRequestWarning
import urllib3
from lxml import etree

# below code send http get request to
# return content in form of string
# lib Refernce
# 1 :- request

def getRequest(url):
headers = {‘Accept’‘text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8’,
‘Accept-Encoding’‘gzip, deflate, br’,
‘User-Agent’‘Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/64.0.3282.140 Safari/537.36’
response = requests.get(url, verify=False, headers=headers)
return response.text

# This method is use to parse data from string
# Return object with data
# lib Refrence
# 1 :- lxml
# 2 : json

def parseData(strHtml):
parser = html.fromstring(strHtml)

# Parse Data Using
URL = parser.xpath(‘//link[@rel=”canonical”]’)[0].attrib[‘href’]
ASIN = parser.xpath(‘//div[@id=”cerberus-data-metrics”]’)[0].attrib[‘data-asin’]
nodes = parser.xpath(‘//div[@class=”content”]/ul/li’)
for node in nodes:
if ‘UPC’ in .join(node.itertext()):
UPC = .join(node.itertext()).replace(‘UPC:’).strip()
for node in nodes:
if ‘Item model number’ in .join(node.itertext()):
ItemModelNumber = .join(node.itertext()).replace(
‘Item model number:’).strip()
for node in nodes:
if ‘Average Customer Review’ in .join(node.itertext()):
NoofReviews = .join(node.itertext()).replace(
‘Average Customer Review:’).strip()

SalesrankFinal = .join(parser.xpath(‘//ul[@class=”zg_hrsr”]’)[0].itertext()).strip()
NoofRatings = parser.xpath(‘//span[@id =”acrPopover”]/span[1]/a/i[1]/span’)[0].text.strip()
productDescription = .join(parser.xpath(‘//div[@id=”productDescription”]’)[0].itertext()).strip()
for node in nodes:
if ‘Product Dimensions’ in .join(node.itertext()):
Productdimensions = .join(node.itertext()).replace(
‘Product Dimensions:’).strip()
#Availability = parser.xpath(‘//span[@id=”availability”]’)[0].text.strip()
BSR = parser.xpath(‘//li[@id=”SalesRank”]/text()’)[1].strip()
for node in nodes:
if ‘Shipping Weight’ in .join(node.itertext()):
ShippingWeight = .join(node.itertext()).replace(‘Shipping Weight:’).strip()
Category = parser.xpath(‘//span[@id=”productTitle”]’)[0].text.strip()
Price = parser.xpath(‘//span[@class=”a-color-price”]’)[0].text.strip()
product_title = parser.xpath(‘//span[@id=”productTitle”]’)[0].text.strip()
#Shippingcost = parser.xpath(‘//span[@id=”ourprice_shippingmessage”]/span’)[0].text.strip()

return {
‘Item Model Number’: ItemModelNumber,
‘No Of Reviews’: NoofReviews,
‘Sales Rank Final’: SalesrankFinal,
‘No Of Ratings’: NoofRatings,
‘product Description’: productDescription,
‘Product Dimensions’: Productdimensions,
#’Availability’: Availability,
‘Best Seller Rank’: BSR,
‘Shipping Weight’: ShippingWeight,
‘Category’: Category,
‘Price’: Price,
‘product_title’: product_title
#’Shippingcost’: Shippingcost

if __name__ == “__main__”:
print(‘Scraping Data from yellow Pages’)
url = ‘’
print(‘Url :- ‘ + url)
strHtml = getRequest(url)
result = parseData(strHtml)

Above code is developed for Python 3.X  .. Run in any IDE  like PyCharm , sublime text etc…  We got here json file , we can also extract these data into sql database , export in CSV , Excel with modification in coding..

Here  using lxml library  data is extracted , you can do using beautifulsoup 4 also we can extract data from any website..

Run above code in any IDE of python and you will get result in JSON..  for test you can use another url from eBay..

Clarification :- This  code available in this tutorial is  only learning purpose . We are not responsible for how it is used and assume no liability for any detrimental usage of the source code. This code is only  use for knowledge expansion regarding programming field.. by this tutorial we are not encourage eBay scraping or web scraping but will help to understand scraping.. also we are not responsible to provide any support for this code .. user can modify for learning purpose..

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