Start Your Project with Us

Whatever your project size is, we will handle it well with all the standards fulfilled! We are here to give 100% satisfaction.

  • Any feature, you ask, we develop
  • 24x7 support worldwide
  • Real-time performance dashboard
  • Complete transparency
  • Dedicated account manager
  • Customized solutions to fulfill data scraping goals
Careers

For job seekers, please visit our Career Page or send your resume to hr@actowizsolutions.com

How-to-Scrape-the-Best-Deals-Data-from-Discounts-and-Promo-Codes-Websites-Using-Web-Scraping

Have you thought about getting the discounted prices earlier? This blog discusses how to scrape the best deals data from discounts and promo code websites using web scraping on a smaller Raspberry Pi device.

Basic Requirements

Raspberry Pi

Raspberry-Pi

Many Raspberry Pi projects are available online, and most of those projects need some electrical engineering. In our use cases, we have just used Raspberry Pi as a web scraping server, which works 24x7.

Python 3

Python-3

Python is the language with numerous powerful libraries that are easy to use and prototype new applications. We have used Python 3 here.

Scrapy

Scrapy

Scrapy is among the most acceptable open-source scraping frameworks of Python. Scrapy is powerful and fast and is the central part of our toolset. Though many new versions are available, the main mechanisms haven’t changed much. This blog uses the latest version of Python 3.6.10 and Scrapy 2.0.1.

Modern Browser

Modern-Browser

A modern browser has developed tools that help inspect objects and scrape HTML tags very quickly.

Website

Website

Many websites offer promo codes and discounts, for instance, SlickDeals, DealMoon, and Dealnews. There would be different mechanisms on HTML to scrape, but choosing a website you are interested in is not reserved here. An essential part of data scraping to succeed is to select a website with sufficient traffic. In this blog, we have used SlickDeals as a scraping website.

Using a Developer Tool for Scraping Context

1. Go to a website called SlickDeals.

2. The majority of great deals are available on the section named Frontpage Slickdeals. Every item has the given data, including product titles, images, website or store, current pricing, original pricing, likes, shipping details, and more.

3. Open a developer’s tool on a browser or check the element on a website. Most developer tools should highlight the selection and concentrate on your selected HTML tags. An important step is finding a parallel pattern to scrape data in Python’s loop. Moving toward the following items, you may see similar titles again. Here, a div tag using the class “fpItem” is known for every product

3.-Open-a-developers-tool-on-a-browser

4. After identifying , we have to get the rest of the data from the parent. To get the name of every class, you could repeat the mentioned steps here using Developer Tools in a browser, find all the exciting fields and scrape them.

4.-After-identifying

Scrapy Code

Scrapy-Code

We have all the data on which class to scrape data from. We can put everything in the Python Scrapy project to do a trial run. Just go through the code to know more.

The given code is the spider.py file provided in the Scrapy Spider folder. Initially, we define a crawler’s name called — “slickdeals.” After that, as discussed here, we have to get the list item using Selector & calling

Then, we can iterate them and scrape data. Here, we have used XPath to check if a class has the keyword we are searching for.

Eventually, we store data in the CSV file to do more investigation. You can send an email with the keyword you need. Python’s email module could be used here. Here is the sample without content.

Eventually,-we-store-data-in-the-CSV-file-to-do-more

To test this program, in a project root directory, just execute

And the results would look like the given, and you’d observe the data fields we scraped.

And-the-results-would-look-like-the-given

Schedule

Schedule

As the program will run 24x7, the energy-efficient Raspberry Pi makes more sense to achieve the goal. When the code gets verified for execution, we can use a web crawler to run using Linux’s crontab.

You can begin with crontab -e and add the given command. We will execute the data crawler every 15 minutes using crontab */15 * * * *

Conclusion

Congratulations! We have got a data scraping program working 24x7 with the requests you have asked. It doesn’t matter what the objective is getting good deals, coupons, and freebies. Our small program runs very hard and silently in the back office to monitor the most satisfactory sales and send alerts on its results. We hope this blog can offer you insights and the ability to do web scraping to help you start building advanced programs on smaller devices like Raspberry Pi.

For more information about how to scrape the best deals data from discounts and promo code websites using web scraping, contact Actowiz Solutions now!

You can also discuss all your mobile app scraping and web scraping services requirements with us!

RECENT BLOGS

View More

How to Scrape Singapore Food Delivery Data for Offer & Fee Benchmarking?

Learn how to Scrape Singapore Food Delivery Data to analyze offers, delivery fees, and gain a competitive edge across platforms like Grab and FoodPanda.

Tracking Uber Eats, DoorDash & Grubhub in the U.S. Using Real-Time Pricing Data Extraction

Discover how Real-Time Pricing Data Extraction helps monitor Uber Eats, DoorDash & Grubhub to analyze trends, pricing shifts & delivery strategies in the U.S.

RESEARCH AND REPORTS

View More

Research Report - Grocery Chain Data USA - Top 10 Leading Grocery Retailers in the U.S. for 2025

Explore the latest insights from Grocery Chain Data USA, revealing the top 10 leading grocery retailers in the U.S. for 2025 by size, reach, and trends.

Kohl’s Store Count USA 2025 - Kohl’s Store Count in the United States for 2025

Discover the latest Kohl’s Store Count USA 2025 data, revealing the total number of Kohl’s locations across the United States and market trends.

Case Studies

View More

Case Study - How UAE-Based Real Estate Platform Achieved 5x Faster Listing Sync with Actowiz UAE Real Estate Data Scraping

Discover how Actowiz's UAE Real Estate Data Scraping helped a leading platform achieve 5x faster listing sync and better accuracy across Bayut, Dubizzle & more.

Case Study - Restaurant Franchise Uses Actowiz Real-Time Menu Analysis to Analyze 5,000 Menus Across U.S. Delivery Apps

Discover how a restaurant franchise leveraged Actowiz’s Real-Time Menu Analysis to analyze 5,000+ menus from U.S. delivery apps and boost pricing accuracy.

Infographics

View More

Tracking E-Commerce Price Change Frequency with Real-Time Data

Track how often prices change on Amazon, Flipkart, and Walmart with real-time data from Actowiz. Optimize pricing strategies with smart analytics and alerts.

City-Wise Grocery Cost Index in the USA – Powered by Real-Time Data

Discover real-time grocery price trends across U.S. cities with Actowiz. Track essentials, compare costs, and make smarter decisions using live data scraping.