Python for KDP Authors: Automate Manuscript Checks, EPUBs, Print PDFs, Covers, Keyword Lists, Metadata, Sales Reports, and Royalty Tracking

Stop renaming files at midnight.

If you self-publish across KDP, Apple Books, and Etsy, you already know that most of your time goes to formatting files, regenerating covers, comparing keyword lists, and reconciling sales reports. Python for KDP Authors hands you a complete, working Python toolkit you can run from your own laptop — no consultants, no subscriptions, no scraping.

Across twenty hands-on chapters, you'll build:

• Manuscript validators that catch double spaces, smart-quote inconsistencies, missing chapters, and word-count drift before they reach a paying reader.
• An EPUB pipeline that converts your Markdown or .docx manuscript into a clean, KDP- and Apple-Books-compliant ebook with a real table of contents.
• A ReportLab print PDF pipeline with a two-pass table of contents, recto-verso running heads, and an exact-page-count gutter calculator.
• Parametric cover templates with bleed, spine, and trim math computed from page count and paper thickness.
• Metadata, category, and keyword exporters that produce KDP, Apple Books, and Etsy listings from one canonical source file.
• Sales and royalty reports built on top of pandas, with per-title, per-store, and per-pen-name breakdowns.
• A SQLite catalog that tracks every book, format, store listing, and pen name in your operation.
• A personal command-line tool — kdp-tools — that wires the whole pipeline together with one command.

Who this book is for

This book is written for self-published authors who already have a working catalog and want to spend more of their week writing instead of reformatting. You should be comfortable with a text editor and the basics of moving files around. You do not need a computer science background. The book starts with plain Python and walks you through every script you'll need, end to end.

What you'll need

• A laptop (Mac, Windows, or Linux).
• Python 3.11 or newer.
• A text editor — VS Code is recommended.
• A folder of manuscripts you actually care about backing up first.