NYT Best Sellers List Scraper

Extract ranked book data from the New York Times Best Sellers lists — no API key required. Covers all ~20 weekly list categories with support for the full historical archive (2008–present via dated URLs).

What it does

The NYT Best Sellers lists are updated weekly across categories including Hardcover Fiction, Paperback Nonfiction, Young Adult, Children's, Combined Print & E-Book, and more. This actor reads the free public HTML pages (which embed the complete structured book record) and extracts per-book data including rank movement, sales metadata, and retailer buy links.

The official NYT Books API requires a developer key and enforces strict rate quotas — this actor reads the public HTML pages instead, which return full data with no authentication.

Output fields

Field	Description
list_name	Human-readable list name (e.g. "Hardcover Fiction")
list_slug	URL slug (e.g. "hardcover-fiction")
bestsellers_date	Publication date of this ranking (YYYY-MM-DD)
published_date	Full ISO timestamp of publication
rank	Current rank on the list (1 = #1 bestseller)
rank_last_week	Rank the previous week (0 = new entry)
weeks_on_list	Number of weeks on this list
title	Book title
author	Author credit (e.g. "by Jane Smith")
publisher	Publisher name
description	Short description or plot summary
isbn13	Primary ISBN-13 identifier
book_image_url	URL to the book cover image
amazon_url	Amazon buy link
buy_links	All retailer buy links (pipe-separated: "Seller|url Seller2|url2")

Input

Parameter	Type	Default	Description
maxItems	integer	—	Maximum book records to return. 0 = no limit
listSlugs	array	[]	Filter to specific list slugs. Empty = all lists
currentOnly	boolean	true	When true, only scrape the most recent published week

List slugs reference

Common list slugs you can use with listSlugs:

• hardcover-fiction
• hardcover-nonfiction
• paperback-nonfiction
• trade-fiction-paperback
• combined-print-and-e-book-fiction
• combined-print-and-e-book-nonfiction
• young-adult-hardcover
• childrens-middle-grade-hardcover
• picture-books
• series-books
• advice-how-to-and-miscellaneous

Example runs

Current week — Hardcover Fiction top 5

{
  "maxItems": 5,
  "listSlugs": ["hardcover-fiction"],
  "currentOnly": true
}

All current week lists

{
  "maxItems": 200,
  "currentOnly": true
}

Historical archive — all weeks for one list

{
  "listSlugs": ["hardcover-fiction"],
  "currentOnly": false
}

Sample output record

{
  "list_name": "Hardcover Fiction",
  "list_slug": "hardcover-fiction",
  "bestsellers_date": "2026-05-17",
  "published_date": "2026-05-17T04:00:00.000Z",
  "rank": 1,
  "rank_last_week": 1,
  "weeks_on_list": 4,
  "title": "YESTERYEAR",
  "author": "by Caro Claire Burke",
  "publisher": "Knopf",
  "description": "Natalie Heller Mills, a privileged tradwife social media influencer, wakes up to find she is living in the comparatively difficult reality of 1855.",
  "isbn13": "9780593804216",
  "book_image_url": "https://static01.nyt.com/bestsellers/images/9780593804216.jpg",
  "amazon_url": "https://www.amazon.com/dp/059380421X?tag=thenewyorktim-20",
  "buy_links": "Amazon|https://www.amazon.com/dp/059380421X?tag=thenewyorktim-20  Apple Books|https://goto.applebooks.apple/9780593804216?at=10lIEQ  Barnes and Noble|...  Bookshop.org|..."
}

Use cases

• Publishing analytics — Track rank movement, weeks on list, and new entries across categories
• Author/PR research — Monitor a title's performance over time using historical data
• Bookstore merchandising — Pull current bestseller data to inform inventory and display decisions
• Reading recommendation engines — Seed with current bestsellers by category
• Competitive analysis — Compare publisher performance across categories and time periods

Schedule recommendations

The NYT Best Sellers lists publish weekly (Saturday/Sunday). Set a schedule to run every Sunday with currentOnly: true to capture each new list as it publishes.

Notes

• Each list page contains 10-15 titles; a full scrape of all current-week lists returns approximately 150-200 records
• Historical data is available from approximately 2008 onwards via dated URLs
• The actor reads public HTML pages — no NYT developer account or API key required
• Buy links include Amazon, Apple Books, Barnes & Noble, Books-A-Million, and Bookshop.org