Wallapop Scraper

A Python scraper for extracting product listings from Wallapop using the ScrapingAnt API.

Features

• Scrapes product listings from Wallapop category pages
• Extracts: title, price, description, listing URL, category
• Supports multiple categories (phones, computers, gaming, fashion, etc.)
• Handles "Ver más" (Show More) pagination via JavaScript execution
• Exports results to CSV and JSON formats
• Automatic deduplication of listings

Prerequisites

• Python 3.10+
• ScrapingAnt API key (Get one here)

Note: The ScrapingAnt free plan has a concurrency limit of 1 thread. For faster scraping with multiple concurrent requests, consider upgrading to a paid plan.

Installation

1. Clone the repository:

git clone https://github.com/kami4ka/wallapop-scraper.git
cd wallapop-scraper

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Set your ScrapingAnt API key:

export SCRAPINGANT_API_KEY="your-api-key-here"

Usage

Basic Usage

Scrape default categories (iPhone + Samsung):

python main.py -v

Scrape Specific Categories

python main.py --categories "moviles-telefonos/iphone" -v

Scrape All Categories

python main.py --all-categories -v

Load More Listings

Click "Ver más" button multiple times to load more listings:

python main.py --show-more 3 -v

List Available Categories

python main.py --list-categories

Custom Output Paths

python main.py --output-csv my_listings.csv --output-json my_listings.json -v

Available Categories

Phones

• iPhone: moviles-telefonos/iphone
• Samsung: moviles-telefonos/samsung
• Xiaomi: moviles-telefonos/xiaomi

Computers

• Laptops: informatica/portatiles
• Desktop Computers: informatica/ordenadores-sobremesa
• Tablets: informatica/tablets

Gaming

• PlayStation: consolas-videojuegos/playstation
• Xbox: consolas-videojuegos/xbox
• Nintendo: consolas-videojuegos/nintendo

Fashion

• Men's Clothing: moda-accesorios/ropa-hombre
• Women's Clothing: moda-accesorios/ropa-mujer
• Sneakers: moda-accesorios/zapatillas

Home

• Furniture: hogar-jardin/muebles
• Appliances: hogar-jardin/electrodomesticos

Sports

• Bicycles: bicicletas
• Fitness Equipment: deportes-ocio/fitness

Output Format

CSV Fields

• title - Product name
• price - Listed price (e.g., "900 €")
• description - Product description
• location - Seller location (when available)
• listing_url - Direct link to the listing
• category - Category name
• image_count - Number of images
• seller_type - Type of seller (when available)
• scraped_at - UTC timestamp of when data was scraped

Sample Output

title,price,description,location,listing_url,category,image_count,seller_type,scraped_at
iPhone 16 Pro Max,900 €,Como nuevo sin arañazos...,,https://es.wallapop.com/item/iphone-1234567,iPhone,5,,2025-01-12T12:00:00+00:00

Project Structure

WallapopScraper/
├── main.py           # CLI entry point
├── scraper.py        # Main scraper class
├── models.py         # Data models (Listing, ListingCollection)
├── config.py         # Configuration settings
├── utils.py          # Utility functions
├── requirements.txt  # Python dependencies
├── output/           # Output directory for CSV/JSON files
└── README.md

How It Works

1. API Request: Uses ScrapingAnt's browser rendering with Spanish residential proxy to access Wallapop
2. Wait for Content: Waits for listing cards to load using CSS selector a[href*="/item/"]
3. Pagination: Optionally clicks "Ver más" button via JavaScript injection to load additional listings
4. Parsing: Extracts listing data from card elements using BeautifulSoup
5. Deduplication: Removes duplicate listings based on URL
6. Export: Saves results to CSV and JSON formats

Rate Limiting

The scraper includes built-in delays between requests to respect rate limits. For the ScrapingAnt free tier with 1 thread concurrency, expect approximately 30-60 seconds per category (depending on Show More clicks).

License

MIT License