Wallapop Scraper

Wallapop Scraper is a lightweight data extraction tool that searches Wallapop for specific items and returns all matching products for sale in a structured format. It helps developers, analysts, and resellers turn Wallapop listings into actionable product data with speed and consistency.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
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Introduction

Wallapop Scraper automates the process of searching items on Wallapop and collecting detailed product listings at scale. It solves the problem of manual browsing and data collection by providing clean, structured outputs ready for analysis or integration. This project is ideal for developers, data analysts, and marketplace researchers working with resale or second-hand product data.

Marketplace Product Discovery

• Searches Wallapop using keyword-based queries
• Collects all matching product listings across result pages
• Extracts structured listing, seller, and pricing data
• Designed for scalable and repeatable data collection

Features

Feature	Description
Keyword Search	Search Wallapop listings using custom item keywords.
Pagination Handling	Automatically processes multiple result pages.
Structured Output	Returns consistent, analysis-ready product data.
Lightweight Parsing	Uses fast HTML parsing for efficient extraction.
Configurable Limits	Control how many pages or items are scraped.

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What Data This Scraper Extracts

Field Name	Field Description
productId	Unique identifier of the Wallapop listing.
title	Product title as shown on the listing.
price	Listed product price.
currency	Currency used for the product price.
condition	Item condition (e.g., new, used).
description	Full product description text.
category	Category or section of the product.
location	Seller location or city.
sellerName	Public name of the seller.
images	Array of product image URLs.
productUrl	Direct URL to the product listing.
publishedAt	Listing publication timestamp.

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Example Output

[
      {
        "productId": "842193847",
        "title": "iPhone 13 Pro 128GB",
        "price": 720,
        "currency": "EUR",
        "condition": "Used - Like New",
        "category": "Mobile Phones",
        "location": "Barcelona, Spain",
        "sellerName": "Carlos M.",
        "images": [
              "https://cdn.wallapop.com/images/iphone13-front.jpg",
              "https://cdn.wallapop.com/images/iphone13-back.jpg"
        ],
        "productUrl": "https://es.wallapop.com/item/iphone-13-pro-842193847",
        "publishedAt": "2024-05-12T10:42:18Z"
      }
]

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Directory Structure Tree

Wallapop Scraper/
├── src/
│   ├── main.js
│   ├── crawler.js
│   ├── routes/
│   │   └── search.js
│   ├── extractors/
│   │   └── productExtractor.js
│   ├── utils/
│   │   ├── pagination.js
│   │   └── helpers.js
│   └── config/
│       └── input.schema.json
├── data/
│   └── sample-output.json
├── package.json
└── README.md

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Use Cases

• E-commerce analysts use it to monitor resale prices so they can track market trends accurately.
• Product researchers use it to collect second-hand listings to analyze demand and availability.
• Developers use it to power dashboards and APIs with Wallapop product data.
• Resellers use it to identify profitable items and pricing opportunities faster.

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FAQs

Does this scraper support multiple search keywords? Yes, you can configure it to run searches for different items sequentially, collecting results for each keyword.

Can I limit how many listings are collected? Yes, the scraper supports configurable page and result limits to control data volume.

What output format does it produce? The scraper outputs structured JSON objects with consistent fields for easy processing and storage.

Is it suitable for large-scale data collection? It is designed for efficient pagination and lightweight parsing, making it suitable for medium to large datasets.

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Performance Benchmarks and Results

Primary Metric: Processes an average of 40–60 product listings per minute per keyword under normal conditions.

Reliability Metric: Maintains a successful extraction rate above 97% across multi-page searches.

Efficiency Metric: Low memory footprint due to non-browser HTML parsing and minimal runtime overhead.

Quality Metric: Consistently captures complete listing metadata including pricing, seller, and media fields.

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"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza SEO Affiliate Expert ★★★★★

"Exceptional results, clear communication, and flawless delivery. Bitbash nailed it." Syed Digital Strategist ★★★★★