Publishers and editors
Catalog checks
Favorable to scraping
Compare author names, subtitles, ISBNs, publisher text, and publication dates across a curated list of Google Books pages before updating internal catalog records.
Search Engine$50Free
Google Books Scraper for CSV Export
This Google Books scraper turns known Google Books book pages into a structured CSV for catalog cleanup, market research, publishing audits, and reading-list enrichment. Import the template into the UScraper local desktop app, add or replace the book URLs in the Navigate block, and export titles, subtitles, ISBNs, authors, page counts, publishers, languages, subjects, descriptions, original publication dates, and buy links without writing a crawler.
Output
CSV
Columns
18
Input
URL loop
Waits
Built in
Template
Free
At a glance
Export Google Books metadata to CSV
Google Books is useful for discovery, but copying book pages into a spreadsheet by hand is slow and inconsistent. This template gives operations teams a no-code Google Books extractor: set the browser size, navigate through a list of book detail URLs, wait for the page and metadata areas, run a helper script, and append a structured row to CSV.
Book records in fixed columns
Export metadata that a catalog, CRM, or research spreadsheet can actually use: ISBN, author, publisher, language, subjects, description, and buy-link fields.
Repeatable URL batches
The Navigate block accepts multiple Google Books URLs, so you can collect records from a curated list instead of rebuilding the workflow for every title.
API enrichment with DOM fallback
The helper reads the book ID, checks the public Google Books Volume API, and uses page content as backup for fields such as title, author, format, and subjects.
Local desktop app custody
The browser run and CSV export happen on your machine. Nothing in the stock template sends your output to UScraper servers.
Who this is for
Teams that need book metadata outside the browser
Researchers and librarians
Bibliography prep
Favorable to scraping
Download Google Books metadata for a topic list, then clean the CSV in Excel or Sheets before citation review, subject tagging, or collection planning.
Data operations teams
Workflow prototyping
Favorable to scraping
Test a local extraction flow before deciding whether the official API, a paid SERP API, or a larger metadata pipeline is worth the setup and recurring cost.
How to use
Scrape Google Books pages in five steps
1
Download and import
Download the hosted JSON template from this page, import it into UScraper, and open the block graph.
2
Replace the sample URLs
Edit the Navigate block and add the Google Books book or about URLs you want to process. Keep the first run small so you can validate output.
3
Review the export path
Structured Export writes google-books-scraper.csv with headers and append mode enabled. Change the folder if your team stores research files elsewhere.
4
Run the workflow
UScraper opens each URL, waits for page load and book metadata, runs the enrichment helper, exports the configured columns, and continues the URL loop.
5
Open the CSV
Spot-check titles, ISBNs, author names, subjects, and buy links before moving the file into Excel, Sheets, Airtable, or a catalog database.
Automation path inside the template
- 1
Navigate
Open each configured Google Books URL from the multi-URL Navigate block.
- 2
Wait and enrich
Wait for the book page, then run JavaScript that reads the volume ID, checks API metadata, and collects DOM fallbacks.
- 3
Export
Append one CSV row from the Structured Export block using JavaScript-backed columns.
- 4
Loop
Continue to the next URL until the input list is complete.
Output preview
What the Google Books CSV includes
The export is built for review and enrichment, not blind authority. Some Google Books pages expose sparse metadata, so empty cells should be treated as fields to verify, not proof that the data does not exist.
| keyword | book_title | isbn | author | publisher | subject |
|---|---|---|---|---|---|
| Web scraping | Web Scraping with Python | 9781491985571 | Ryan Mitchell | O'Reilly Media | Computers / Web |
| Psychology | Thinking, Fast and Slow | 9780374533557 | Daniel Kahneman | Farrar, Straus and Giroux | Psychology |
| Education | The Smartest Kids in the World | 9781451654431 | Amanda Ripley | Simon and Schuster | Education |
google-books-scraper.csvColumn
keyword
Keyword from the URL query, category, or subject fallback.
Column
book_url
The Google Books page processed for this row.
Column
book_title
Primary book title from API or page heading.
Column
book_subtitle
Subtitle when Google Books exposes one.
Column
isbn
One or more industry identifiers.
Column
author
Author list from the volume record or page metadata.
Column
page_count
Detected number of pages.
Column
published
Publication date, normalized where possible.
Column
format
Paperback, hardcover, ebook, or similar format cue.
Column
publisher
Publisher name from API or page metadata.
Column
language
Language code expanded when possible.
Column
description
Book description or synopsis.
Column
originally_published
Original publication date when visible.
Column
genre
Primary genre or category.
Column
subject
Full subject/category path when available.
Column
buy_link_1
First detected retailer or library buy link.
Column
buy_link_2
Second detected buy link.
Column
buy_link_3
Third detected buy link.
Sample rows
1 of many
| keyword | book_url | book_title | book_subtitle | isbn | author | page_count | published | format | publisher | language | description | originally_published | genre | subject | buy_link_1 | buy_link_2 | buy_link_3 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Web scraping | Web Scraping with Python | Collecting More Data from the Modern Web | 9781491985571 | Ryan Mitchell | 306 | April 17, 2018 | ebook | O'Reilly Media | English | A practical guide to collecting data from websites. | Computers | Computers / Web |
Headers included - one row per Google Books URL
Related workflows
Build a broader research workflow
Start with the Google Search Scraper or Google SERP Scraper when you need to discover candidate book pages first. Use the Google Scholar Scraper for academic follow-up, browse the full UScraper template library, or install the local desktop app from uscraper.io/download.
Frequently asked questions
Google Books shows public book pages and also documents an official Books API, but automated collection can still be limited by Google terms, copyright, robots guidance, and local law. Use modest batches, avoid bypassing access controls, and get legal review before republishing, reselling, or training models on exported metadata.
Before you run
Practical limits to plan around
Run small URL batches first and avoid parallel runs. Some Google Books pages may load slowly, lack a complete volume record, or respond differently by region.
Get Started
Download and use this template instantly
$50Free
What's Included
- Template JSON file ready to import
- Pre-configured scraping nodes
- Works with UScraper desktop app
Open-source templates
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