Align comparison grain
Aggregate many receipts before comparing them with one invoice.
Python and data workflows · EDITION 1.0.0
Build an inspectable SQLite reconciliation that aggregates receipts at invoice grain and separates mismatches, unpaid invoices and orphan receipts.
By Sanjaay Gowda T S · For analysts who can read basic sql and need to compare two business extracts.
Runtime and hardware details
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Basic SELECT and GROUP BY; Python dictionaries and lists; Understanding primary keys.
Full setup and scope ↓$2.99USD · one-time purchase
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review remains pending. Automated checks and agent review are not certification.
PDF + EPUB + companion project. Any applicable tax is shown at checkout. Single-reader ebook terms; companion code is MIT licensed.

TRY THE FREE SAMPLE
Read 6 sample pages to explore the introduction, first chapter and teaching approach before you choose the complete edition.
WHAT YOU WILL LEARN
Aggregate many receipts before comparing them with one invoice.
Distinguish underpayment, overpayment, unpaid invoices and orphan receipts.
Prove conservation and preserve identifiers behind every summary.
INSIDE THE BOOK
Python 3.10 or later and a terminal. The supplied project runs locally and uses the Python standard library.
No model, API key, cloud account or network calls are used by the companion.
Learning prerequisites: Basic SELECT and GROUP BY; Python dictionaries and lists; Understanding primary keys.
Prepared with AI assistance. Independent human technical, editorial and assistive-technology reader review is pending.
The included examples are synthetic teaching material. Model access, software subscriptions, hosting, ongoing updates and consulting are not included.
CLEAR EXPECTATIONS
Build an inspectable SQLite reconciliation that aggregates receipts at invoice grain and separates mismatches, unpaid invoices and orphan receipts. The local companion uses fictional teaching fixtures. Project limits: One teaching currency, no refunds or fees; One invoice reference per receipt; Small fixed in-memory extracts, no durable approval record.
The 14 companion tests passed on the packaged project. The supplied fictional fixture produced its recorded expected JSON output. EPUBCheck reported no errors or warnings; DAISY Ace and PDF/UA automated checks passed. These local teaching checks are not production accuracy claims or certification. Independent human technical, editorial and assistive-technology reader review remains pending.
Complete the secure Lemon Squeezy checkout to access the PDF, EPUB and companion ZIP. Keep your receipt and download access private. This is a one-time purchase of edition 1.0.0; ongoing updates and consulting are not included.
The full ebook is licensed to one reader. The labelled free sample may be shared unchanged. The companion project is MIT licensed and may be adapted or shared with its licence notice. See the exact ebook terms.
One book. A complete learning project. Evidence you can inspect.
AI-assisted · Independent human review pending