tigerqueen-lester-sparks/hepsiburada-product-search-scraper
Hepsiburada product market intelligence
Hepsiburada Product Search Scraper
A production-ready data extraction tool for collecting rich product intelligence from Hepsiburada search and category pages. It transforms large-scale product listings into structured datasets for analysis, monitoring, and strategic decision-making in Turkey’s e-commerce market.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for hepsiburada-product-search-scraper you've just found your team — Let’s Chat. 👆👆
Introduction
This project extracts comprehensive product data from Hepsiburada listing pages using URLs or dynamic search filters.
It solves the challenge of manually collecting and maintaining up-to-date market data across millions of products.
It is built for analysts, retailers, researchers, and businesses operating in or entering the Turkish market.
Market Intelligence at Scale
- Covers all major product categories across Hepsiburada
- Supports URL-based and filter-based product discovery
- Collects pricing, reviews, merchants, variants, and campaigns
- Designed for high-volume, repeatable data collection
- Optimized for stability with retries and proxy support
Features
| Feature | Description |
|---|---|
| Dual Scraping Modes | Scrape via category/search URLs or keyword-based filters. |
| Rich Product Coverage | Extracts prices, variants, campaigns, images, and reviews. |
| Scalable Extraction | Handles large result sets with configurable limits. |
| Retry Logic | Automatically retries failed requests for stability. |
| Proxy Ready | Supports residential proxies for uninterrupted access. |
| Structured Output | Returns clean, analysis-ready product records. |
What Data This Scraper Extracts
| Field Name | Field Description |
|---|---|
| product_id | Unique identifier of the product. |
| brand | Manufacturer or brand name. |
| definition | Product title and classification details. |
| main_category | Primary category information. |
| variant_list | Available product variants and SKUs. |
| price_info | Current, original, and discounted prices. |
| campaign_price_info | Basket or campaign-based discounts. |
| customer_review_count | Total number of reviews. |
| customer_review_score | Average customer rating score. |
| customer_review_rating | Detailed rating metrics. |
| merchant_name | Seller or merchant information. |
| images | Product image URLs and metadata. |
| properties | Key product attributes (e.g., color). |
| from_url | Source listing URL. |
Example Output
[
{
"product_id": "HBC000054VRE5",
"brand": "Fissler",
"customer_review_count": 1298,
"customer_review_score": 5,
"customer_review_rating": 4.6,
"main_category": {
"id": 17006471,
"name": "Düdüklü Tencereler"
},
"variant_list": [
{
"sku": "HBCV000054VRE6",
"name": "Fissler Vitaquick Premium Düdüklü Tencere 4,5L",
"listing": {
"price": 9924,
"discounted_price": 8435.4,
"merchant_name": "İRONTECH TEKNOLOJİ"
}
}
],
"from_url": "https://www.hepsiburada.com/pisirme-c-80667013"
}
]
Directory Structure Tree
Hepsiburada Product Search Scraper/
├── src/
│ ├── main.py
│ ├── crawler/
│ │ ├── listing_collector.py
│ │ └── product_parser.py
│ ├── filters/
│ │ └── query_builder.py
│ ├── utils/
│ │ ├── retries.py
│ │ └── http_client.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── input.sample.json
│ └── output.sample.json
├── requirements.txt
└── README.md
Use Cases
- Market researchers use it to analyze category trends, so they can identify high-growth product segments.
- Retailers use it to monitor competitor pricing, so they can optimize their pricing strategies.
- Brand managers use it to track brand visibility, so they can measure market presence.
- Sourcing teams use it to discover top-performing products, so they can improve procurement decisions.
- Academic researchers use it to study consumer behavior, so they can publish data-driven insights.
FAQs
Can I scrape using keywords instead of URLs?
Yes. Leave the URL list empty and provide keyword, sorting, and pagination options to build dynamic product queries.
What happens if some pages fail during scraping?
Retry logic handles transient failures, and optional settings allow the process to continue even if some pages fail.
Does it support large categories with thousands of products?
Yes. Item limits and pagination controls allow safe, incremental data collection at scale.
Is the output suitable for analytics tools?
Absolutely. The structured JSON format is ready for databases, BI tools, and dashboards.
Performance Benchmarks and Results
Primary Metric: Processes an average of 20–30 product listings per second per category page.
Reliability Metric: Maintains a successful extraction rate above 97% under normal conditions.
Efficiency Metric: Optimized request handling minimizes redundant calls and resource usage.
Quality Metric: Captures over 95% of visible product attributes per listing, including pricing and review data.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
|
"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
|
"Exceptional results, clear communication, and flawless delivery. Syed
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