Aladin Scraper — Korean Bookstore Bestsellers 📖

Scrape live bestseller rankings from Aladin (알라딘) — one of Korea's big-3 bookstores and the country's largest used-book marketplace — as clean, structured JSON. Get rank, title, author, publisher, new price (KRW), category, and cover image for every book on any bestseller list in one run.

Aladin is the go-to name in Korea for used books (중고책): it runs both a huge online used marketplace and dozens of offline used-book stores. That makes its bestseller list uniquely useful for used-book arbitrage and second-hand pricing research — you get the titles with the highest resale demand, straight from the source.

Try it free. Apify's free plan includes $5 of monthly platform credit — at $2.00 / 1,000 results that's roughly 2,500 books from this actor, no credit card required. Set your input, click Start, and export JSON/CSV/Excel.

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What it does

This actor reads Aladin's own public bestseller pages (the same server-rendered pages any visitor sees), so results are fast and complete — no fragile full-page scraping, no headless browser, and no API key required. You can scrape:

• The overall bestseller list (종합), or
• Any category list — e.g. fiction (소설/시/희곡), business (경제경영), self-help (자기계발), humanities (인문학), essays (에세이), history (역사), and 20+ more.

Aladin publishes up to ~1,000 ranks per list, so you can pull a shallow Top-100 or a deep Top-1,000 snapshot.

Why Aladin? Alongside Kyobo and Yes24, Aladin is one of Korea's big-3 bookstores — but it's the one that built its brand on the used-book market. Its bestseller list is a live demand signal for both new and second-hand books, which is exactly what resellers, publishers, and rights scouts want. This actor turns that list into a structured dataset you can filter, price-model, and pipe into your own tools.

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Input

Field	Type	Description
mode	string	What to scrape. Currently only bestseller (Aladin's bestseller ranking). Default bestseller.
category	string	Which bestseller list. A Korean category name (e.g. 종합, 소설/시/희곡, 경제경영, 자기계발, 인문학, 에세이, 역사) or a raw Aladin category id (CID) — e.g. 0 = overall, 1 = fiction, 170 = business. Blank = 종합 (overall).
maxItems	integer	Max books to collect. Default 100, max 1000.
proxyConfiguration	object	Proxy settings (see below). Defaults to a direct connection.

Input example

{
  "mode": "bestseller",
  "category": "종합",
  "maxItems": 100
}

{
  "mode": "bestseller",
  "category": "경제경영",
  "maxItems": 200
}

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Output

Each bestseller book is one dataset record. price_krw is the new-book selling price in Korean won (Aladin's discounted 판매가 — the price you actually pay for a new copy). rank is the book's position on the chosen bestseller list. category echoes the list you scraped.

{
  "source": "aladin",
  "rank": 1,
  "item_id": "312732931",
  "title": "파쇄",
  "author": "구병모",
  "publisher": "위즈덤하우스",
  "price_krw": 11700,
  "used_price_krw": null,
  "category": "종합",
  "url": "https://www.aladin.co.kr/shop/wproduct.aspx?ItemId=312732931",
  "image_url": "https://image.aladin.co.kr/product/31273/29/cover200/k592832565_1.jpg",
  "scraped_at": "2026-07-14T14:41:44+09:00"
}

A full 40-item sample from a real run is in samples/sample-output.json.

Field	Meaning
source	Always "aladin".
rank	Position on the bestseller list (1 = top).
item_id	Aladin product ItemId.
title	Full book title.
author	Public author credit (지은이), as Aladin shows it.
publisher	Publisher name when shown, else null (best-effort — see limitations).
price_krw	New-book selling price in KRW (Aladin's discounted 판매가).
used_price_krw	Lowest used price only if the bestseller card shows one inline — in practice almost always null (see limitations).
category	The bestseller list scraped (e.g. 종합, 경제경영).
url	Product page URL.
image_url	Cover image URL.
scraped_at	ISO-8601 timestamp (KST, UTC+9).

The critical fields — rank, title, author, and price_krw — populated on 40/40 records in the live test, along with publisher, url, image_url, and category. used_price_krw is best-effort and was null on all 40 (Aladin doesn't expose a used price on the bestseller card — see Known limitations).

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Use cases

• Used-book arbitrage & resale — Aladin is Korea's biggest used-book market, so its bestseller list is a live demand signal for the titles most worth sourcing second-hand. Track which books top the charts, then price and flip them.
• Publishing & translation-rights scouting — since Han Kang won the 2024 Nobel Prize in Literature (Korea's first), foreign publishers and agents are actively hunting Korean titles. A live bestseller feed by category is a fast way to spot what's selling and shortlist rights candidates.
• Bestseller & trend tracking — schedule daily/weekly snapshots to chart how ranks move over time, by category, and benchmark Aladin against other Korean bookstores.
• AI agents & datasets — feed structured Korean book data (rank, author, publisher, price, cover) into recommendation models, dashboards, or LLM agents.

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❓ FAQ

Is it legal to scrape this data? This actor collects only public, non-personal bestseller data — the same rankings any visitor sees on aladin.co.kr without logging in. Author names are the public book credits, not personal contact data. You are responsible for how you use the data; see the legality note below.

What does it cost in practice? $2.00 per 1,000 results (launch pricing) + a few cents of platform usage. Example: a 100-result daily pull costs about $0.20/day. Apify's free $5 monthly credit covers ~2,500 results (5 ÷ 2 × 1,000).

Do I need an Aladin API key? No. Aladin offers an official OpenAPI (TTB) that needs a registered key, but this actor deliberately uses only the public web pages, so it works with zero configuration.

Do I need to configure proxies? No — the default settings work out of the box. Aladin serves its bestseller pages without a bot wall, so the actor runs fine on a direct connection. For very heavy pulls you can optionally enable Apify Proxy — see the proxy note below.

How fresh is the data? Every run scrapes the live Aladin bestseller list at run time. Schedule the actor for recurring snapshots (e.g. daily rank tracking).

What is NOT included? Per-book used prices (they live on the individual product page, which this actor doesn't crawl — see limitations), reviews, and stock counts. publisher is best-effort. Titles, authors, and categories come as Korean strings.

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🤖 Use with AI agents (MCP)

Call this Actor as a tool from Claude or any MCP-compatible AI agent — no glue code. Point your MCP client at Apify's server, scoped to this Actor:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=kdatafactory/aladin-scraper",
      "headers": { "Authorization": "Bearer <YOUR_APIFY_TOKEN>" }
    }
  }
}

Your agent can then pull Korean bestseller book data on demand — no scraping code in your app. Grab a free token from Apify → Integrations.

🇰🇷 More Korean data actors

This actor is part of a suite of Korean-platform scrapers by the same maintainer:

• yes24-bestseller-scraper — bestseller rankings from Yes24, another of Korea's big-3 bookstores. Run it alongside this actor to compare bestseller lists across stores.
• ridibooks-scraper — e-book bestsellers and rankings from RIDIBOOKS, Korea's leading e-book platform.
• Browse all: apify.com/kdatafactory

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Rate limiting & legality

• The actor collects only public, non-authenticated data. It never logs in and never touches private endpoints.
• No personal data is collected — author names are public book credits, nothing more.
• Requests are rate-limited: one page at a time with a ≥ 500 ms delay between requests, to stay gentle on Aladin's servers.
• You are responsible for using the data in line with Aladin's terms of service and applicable law.

Known limitations (honesty note)

• used_price_krw is best-effort and almost always null. Aladin's bestseller cards do not show a used price inline — the used-copy price lives on each book's own product page. This actor deliberately does not crawl per-book pages just to fetch it (that would be slow and heavy), so this field is populated only in the rare case a card exposes a used price directly. It was null on 40/40 records in the live test. If you need per-book used prices, that would be a separate, heavier crawl.
• publisher is best-effort. It populated on 40/40 books in the live test, but Aladin's markup can vary, so it may be null for some listings. rank, title, author, and price_krw are the guaranteed-populated core fields.
• price_krw is the new-book selling price (Aladin's discounted 판매가), not the list price (정가) or any used price.
• Titles, authors, publishers, and categories are Korean strings — this actor does not translate them.
• Only the bestseller mode is supported today (overall + category bestseller lists). Search and per-book detail are out of scope.

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If this actor saves you time, a rating on the Store page helps a solo maintainer a lot. Found an issue? Open it in the Issues tab — I respond fast.