How to Scrape Vinted Listings with Python

Описание и применение

Скрипт на Python использует Apify Actor для сбора объявлений с Vinted Spain, возвращая структурированные JSON‑данные за 19,2 секунд.

Задача

Manually searching Vinted catalog and copying listings into a spreadsheet is slow and repetitive, and each search result page shows up to 96 items.

Результат

The benchmark run with searchQueries:["nike"], conditions:["Muy bueno","Bueno"], minPrice:10, maxPrice:40, sortBy:"relevance", requireKeywordMatch:true, maxItems:200 finished in 19.2 seconds and returned 200 items.

Рабочий процесс

• Install Python 3.11+ and the Apify API client with pip install apify-client
• Create an Apify account and copy your API token
• Write a Python script that imports ApifyClient, sets run_input with searchQueries, conditions, minPrice, maxPrice, sortBy, requireKeywordMatch, and maxItems
• Call the actor reventadata/vinted-scraper with the run_input
• Iterate over the returned dataset items and print or process the JSON fields

Доказательства

By the end of this tutorial, you will have a Python script that pulls second‑hand fashion listings from Vinted Spain (vinted.es) into structured JSON: title, item asking price, buyer protection service fee, total price in EUR, brand, item condition, size, photo URL, favourite count, and seller type.

Источник

Our benchmark run (configured with searchQueries: ["nike"], conditions: ["Muy bueno", "Bueno"], minPrice: 10, maxPrice: 40, sortBy: "relevance", requireKeywordMatch: true, and maxItems: 200) finished in 19.2 seconds and returned 200 items.

Источник

The scraper extracts item records directly from the server‑rendered catalog pages, so individual listing pages do not need to be opened separately.

Источник