vitalsource2pdf

Ultra-high quality PDFs from VitalSource.

This is an automated, all-in-one scraper to convert VitalSource textbooks into PDFs. Features include:

• Automated download of pages.
• Automated OCR.
• Correct page numbers (including Roman numerals at the beginning). There might be some issues with wierd page numbers at the end of the book.
• Table of contents creation.
• No funny stuff. No wierd endpoints are used and no hacky scraping is preformed.
• Almost completly transparent. All actions are ones that a normal user would do.

The goal of this project is for this to "just work." There are many other VitalSource scrapers out there that are wierd, poorly designed, or are broken. I designed my scraper to be as simple while producing the highest-quality PDF possible.

Install

sudo apt install ocrmypdf jbig2dec
pip install -r requirements.txt

Make sure you have Chrome installed. If you have both Chrome and Chrominium you can use --chrome-exe to specify the path to google-chrome.

The Webdriver binary will be automatically downloaded.

Use

./vitalsource2pdf.py --isbn [your book's ISBN number]

A browser window will pop up so you can log into VitalSource. Press the ENTER key when you are ready.

You can use --output to control where the files are created. By default it creates a folder named VitalSource.

If your network is slow, use --delay to allow more time for the files to download.

Make sure to leave the window maximized as the content scaling will mess with the scraper.

What This Scraper Doesn't Do

Guide you through step-by-step. You are expected to have the required technical knowledge and understand what is happening behind the scenes in order to troubleshoot any issues.

You will also have to double check the output PDF to make sure everything is as it should be.

How it Works

This scraper uses Selenium to load the ebook viewer webpage. It then navigates through the book page by page and records network requests. After each page it will analyze the requests and find one matching the format of the page image. It then saves that request to a .jpg.

Once all images are downloaded, a PDF is created.

Then pytesseract is used to add text to the page images.

Finally, the table of contents is scraped and added to the PDF.