Scraping Python books data from Amazon using Scrapy Framework

We learned how we can scrape twitter data using BeautifulSoup. But BeautifulSoup is slow and we need to take care of multiple things.

Here we will see how to scrape data from websites using scrapy. I tried scraping Python books details from using scrapy and I found it extremely fast and easy.

We will see how to start working with scrapy, create a scraper, scrape data and save data to Database.

Scraper code is available on Github.

Let's start building a scraper.


First create a virtual environment and activate it. Once virtual environment is activated, install the below listed dependencies in it.


Now create a scrapy project.

scrapy startproject amazonscrap

A new folder with below structure will be created.

--- amazonscrap
|   ---
|   ---
|   ---
|   ---
|   ---
|   --- spiders
|     ---
--- scrapy.cfg

Writing spider:

Spider are the classes which are written by us and scrapy uses those classes to get data from websites.

Inside spiders folder, create a spider class BooksSpider and start writing your code in it. Define the name of the spider. Create a list of starting URLs and Generate parse method.

We will also maintain a list of books already scrapped to avoid duplicate requests, although scrapy can take care of this itself.

class BooksSpider(scrapy.Spider):
    name = "book-scraper"
    start_urls = [

    books_already_scrapped = list()
    def parse(self, response):

Since we will be fetching the top 10 comments as well, we are starting with product review URL. After details of one book is scraped, we fetch the other related books on same page and then scrape data for those books. But before we see the code in parse method which parse data from page, we should know what is an Item class.

Scrapy Item:

One good thing about scrapy is that it help in structuring the data. We can define our Item class in file. This will work as a container for our data.

import scrapy

class AmazonscrapItem(scrapy.Item):
    book_id = scrapy.Field()
    title = scrapy.Field()
    author = scrapy.Field()
    rating = scrapy.Field()
    review_count = scrapy.Field()
    reviews = scrapy.Field()

Now let's go back to the parse method.

Parsing the response:

Parse method accept the response as parameter. We will use css or xpath selectors to fetch the data from response. We will be fetching book title, author's name, rating, review count and book Id.

    def parse(self, response):
        book = AmazonscrapItem()
        book["title"] = response.css('a[data-hook="product-link"]::text').extract_first()
        book["title"] = self.escape(book["title"])
        rating = response.css('i[data-hook="average-star-rating"]')
        rating = rating.css('span[class="a-icon-alt"]::text').extract_first()
        book["rating"] = float(rating.replace(" out of 5 stars",""))
        review_count = response.css('span[data-hook="total-review-count"]::text').extract_first()
        review_count = review_count.replace(",","")
        book["review_count"] = int(review_count)
        book["author"] = response.css('a[class="a-size-base a-link-normal"]::text').extract_first()
        book["book_id"] = self.get_book_id(response)
        reviews = self.get_reviews(response)
        book["reviews"] = reviews

Now since we are interested only in Python books, we will try to filter other books out. For this I have created a simple utility function is_python_book , which checks if there is python or Django or flask word in either title or comments.

    def is_python_book(item):
        keywords = ("python", "django", "flask",)
        if any(x in item["title"].lower() for x in keywords):
            return True
        review_subjects = [x["subject"] for x in item["reviews"]]
        if any(x in review_subjects for x in keywords):
            return True
        review_comments = [x["review_body"] for x in item["reviews"]]
        if any(x in review_comments for x in keywords):
            return True

        return False

Returning scraped item:

Once a book's data is scraped along with review comments, we set that in Item and yield it. What happens to the yielded data, is explained in next paragraph. So we make sure that scrapped data is of python book? if yes we return the data for further processing else data is lost.

if self.is_python_book(book):
    yield book

Generating next request:

Once first page is processed, we need to generate the next URL and generate a new request to parse second URL. This process goes on until manually terminated or some condition in code is satisfied.


more_book_ids = self.get_more_books(response)
for book_id in more_book_ids:
    if book_id not in self.books_already_scrapped:
        next_url = self.base_url + book_id + "/"
        yield scrapy.Request(next_url, callback=self.parse)

Storing scrapped data in Database:

When we yielded processed Item, it is sent for further processing in Item Pipeline. We need to define our pipeline class in file.

This class is responsible for further processing of data, be it cleaning the data, storing in DB or string in text files.

class AmazonscrapPipeline(object):

    conn = None
    cur = None

    def process_item(self, item, spider):
        # save book
        sql = "insert into books (book_id, title, author, rating, review_count) " \
              "VALUES ('%s', '%s', '%s', '%s', '%s' )" % \
              (item["book_id"], item["title"], item["author"], item["rating"], item["review_count"])
        except Exception as e:

We can write connection creation and closing part in pipeline's methods, open_spider  and close_spider .

    def open_spider(self, spider):
        self.conn = MySQLdb.connect(host="localhost",  # your host
                             user="root",  # username
                             passwd="root",  # password
                             db="anuragrana_db")  # name of the database

        # Create a Cursor object to execute queries.
        self.cur = self.conn.cursor()

    def close_spider(self, spider):

Points to Remember:

  • Be polite on sites you are scraping. Do not send too many concurrent requests.
  • Respect robot.txt file.
  • If API is available use it instead of scraping data.


Spider wide settings are defined in file.
  • Make sure obeying Robot.txt file is set to True.
# Obey robots.txt rules
  • You should add some delay between requests and limit the concurrent requests.
# The download delay setting will honor only one of:
  • To process the item in pipeline, enable the pipeline.
# Configure item pipelines
# See
    'amazonscrap.pipelines.AmazonscrapPipeline': 300,
  • If you are testing the code and need to hit the same page frequently, better enable cache. It will speed up the process for you and will be good for website as well.
# Enable and configure HTTP caching (disabled by default)
# See

Avoiding 503 error:

You may encounter 503 response status code in some requests. This is because scraper send the default value of user-agent header. Update the user-agent value in settings file to something more common.

# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'amazonscrap (+'
USER_AGENT = "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/27.0.1453.93 Safari/537.36"

Feel free to download the code from Github and experiment with it. Try to scrape data for books of another genre. 

scraping python books data from amazon using scrapy framework  

Read more :

Programming on Raspberry Pi with Python: Sending IP address on Telegram channel on Raspberry Pi reboot

In first article we completed the Raspberry Pi Setup, installed OS on SD card and updated the packages. We were connected to Raspberry Pi using LAN cable and external monitor via HDMI cable.

In second article we configured WIFI and enabled SSH. We were not using LAN cable to connect the system. We were able to ssh into Raspberry Pi from our laptop. 

Programming on Raspberry Pi with Python: Raspberry Pi Setup

Programming on Raspberry Pi with Python: WIFI and SSH configuration

But there was one problem. How do we know the local IP address of Raspberry Pi when it reboots. We will address the same issue in this article.

We will create a python script which will run on every reboot and will send the IP address to a telegram channel.

We are using Raspberry Pi 3 B+ model.

Telegram Channel and Bot:

 - First we need to create a telegram bot and add it as administrator to the desired telegram channel where you wish to receive the messages.

 - Follow this step by step article on how to create a telegram channel and add a telegram bot to it as administrator

Python Script:

 - Login to your Raspberry pi.

 - First create a virtual environment using python3. We will install all the required packages and dependencies in this virtual environment using pip.

 - Please refer this article to create virtual environment, to activate it and intalling the packages.

 - Create a file, requirements.txt and paste below content in it. It is a list of packages you will require for your future python programms.


 - Activate the virtual environment and install the telegram package in it using the command pip install -r requirements.txt.

 - Now create a python script with below content.

import telegram
import subprocess
import time

bot = telegram.Bot(token="YOUR BOT TOKEN GOES HERE")
msg = subprocess.check_output("hostname -I", shell=True).decode('ascii')
status = bot.send_message(chat_id="@YOUR CHANNEL ID", text=msg, parse_mode=telegram.ParseMode.HTML)

We are using telegram package.

Since this script will be executed after Raspberry pi reboot, we introduced sleep time of 60 seconds in the scripts so that by then Raspberry Pi is connected to the available network.

Then in next line we created the bot. Use your bot token. Refer this article to find out how to get the bot token.

Then run the command hostname -I and collect its output and send it to the channel.

Scheduling Script:

 - Once script is ready, run it manually inside the virtual environment using python3 to test the output.

 - Now edit the crontab using command crontab -e.

 - Append the below line in crontab.

@reboot ~/py3venv/bin/python3 ~/practice/startup_scripts/

Use the python3 path and script path accordingly.

Now this script will be executed at every reboot of Raspberry pi and the newly assigned IP address will be sent to you on your telegram channel which you can use to SSH into it.

In the screenshot below you can see, IP address reported by Python script and temprature of Raspberry Pi every 10 minutes.

telegram channel raspberry pi ip address and temprature


 - How to create completely automated telegram channel with python

Purchase Raspberry Pi Starter Kit Here.

Print statement in Python vs other programming languages

In this article we are simply presenting the code blocks required in different programming laguages to print '' on terminal. This shows the amount of code you need to write to print a simple string. 


#include <stdio.h>
int main()
  return 0;


#include <iostream>
using namespace std;

int main() 
    cout << "";
    return 0;


  echo "";


using System;
namespace HelloWorld
    class Hello 
        static void Main() 


public class HelloWorld {
    public static void main(String[] args) {

And now



That is all you need in python to print a statement. This shows the simplicity of Python. 

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