Chips Price Comparison: A101 vs Şok (Educational Web Scraping Project)

Attention :

Legality & Risk

• Web scraping can be restricted by website terms of service.
• Always check robots.txt and site policies before scraping.
• This project is educational only:
  • Scrapes only a limited number of products (≤60).
  • Results are stored locally for learning purposes.
  • No commercial use or repeated high-frequency scraping.

Risks: Sites may block your IP if scraping is excessive. Legal consequences are unlikely for small-scale educational scraping but should always respect website policies.

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1️⃣ What is Web Scraping?

Web Scraping is the process of automatically extracting information from websites. Instead of manually visiting pages and copying data, a program can access the site, read its content, and save it in a structured format (CSV, JSON, database, etc.).

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2️⃣ Why We Do Web Scraping

Web scraping is useful for:

• Collecting product prices for comparison.
• Monitoring stock or promotions.
• Gathering datasets for analysis or educational purposes.
• Automating repetitive tasks that involve data collection.

In this project, the goal is to collect chips prices from two popular Turkish stores (A101 and Şok) and compare them for the same products.

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3️⃣ Problem Definition

Title: Compare prices of chips products between A101 and Şok.

Plan & Steps:

1. Scrape products from A101 using their JSON API endpoint.
2. Scrape products from Şok using HTML scraping.
3. Normalize product names for consistency.
4. Match similar products using fuzzy string matching.
5. Compare prices and determine the cheapest store.
6. Save results to a CSV for easy analysis.

Libraries Used:

• requests — for sending HTTP requests.
• BeautifulSoup4 (bs4) — for HTML parsing (Şok).
• pandas — for data manipulation and CSV handling.
• rapidfuzz — for fuzzy string matching (finding similar product names).
• os — for handling directories and file paths.

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4️⃣ HTML Scraping vs API Scraping

Method	Definition	Use Case
HTML Scraping	Extracts data directly from a website’s HTML structure (tags, classes, ids).	When the site does not have a public API or the API is protected.
API Scraping	Uses a website’s JSON or REST API endpoints to get structured data.	Faster and more reliable if a site provides an API.

In this project:

• Şok: HTML scraping — Let's show this method.
• A101: API scraping — JSON API is available and easier to parse.

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5️⃣ User Manual: How to Use the Python Files

1️⃣ Scraping A101

Call : python a101_scraper.py

• Fetches chips products from A101’s JSON API.
• Saves results to data/a101_chips.csv.

2️⃣ Scraping Şok

Call : python sok_scraper.py

• Scrapes chips products from Şok’s website HTML.
• Saves results to data/sok_chips.csv.

3️⃣ Comparing Prices

Call : python compare_prices.py

• Loads a101_chips.csv and sok_chips.csv.
• Normalizes product names and matches similar products.
• Creates data/compare_chips.csv with:
  • Product name
  • A101 price
  • Şok price
  • Cheapest stor

6️⃣ Results

After running the scraping scripts:

• A101: 60 chips products scraped successfully (with price, old price, and category).
• Şok: 20 chips products scraped successfully from HTML page (name, price, store, URL, date).
• Comparison: Products with similar names are matched, and the cheapest store is highlighted in data/compare_chips.csv.

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