Invoice and Quotation Engine for Pehesara Engineers

Product or service	Qty	Rate	Amount
Aluminium sliding window, 1800 × 1200 mm, fitted	6	38,500	231,000.00
10 mm tempered glass partition	240 sq ft	1,150	276,000.00
Aluminium door frame with fittings	2	64,000	128,000.00
Installation and site labour	1	85,000	85,000.00

Product or service

Qty

Rate

Amount

Aluminium sliding window, 1800 × 1200 mm, fitted

38,500

231,000.00

10 mm tempered glass partition

240 sq ft

1,150

276,000.00

Aluminium door frame with fittings

64,000

128,000.00

Installation and site labour

85,000

85,000.00

Read it as

Problem: A family aluminium and glass firm was writing its invoices and quotations in Word, including the documents for Hayleys PLC's Farmers Building refurbishment.
Constraint: Documents going to a listed company must match the letterhead exactly and get every figure right, and they are often needed from a phone on site.
Decision: A small web app. Fill in the job on a phone, tap Generate, and download a PDF that matches the letterhead, with the signature and terms included.
Outcome: In daily use for the firm's invoices and quotations, including the Farmers Building documents. Old PDFs can be opened again and edited, so nothing is retyped.

The problem

Pehesara Engineers is a family aluminium and glass fixing firm. Its invoices and quotations were Word documents, edited by hand for every job, including the documents for Hayleys PLC’s Farmers Building refurbishment. When the client is a listed company, a mistyped figure or a misaligned letterhead is not a small thing.

The constraint

Faithful, not inspired by. The PDF had to be indistinguishable from the company letterhead: the black-to-red bars, the layout, the signature and the terms and conditions.
Exact figures. Line items, discount, tax, total, an advance payment request and the balance, formatted the same way every time.
From a phone. Quotations are often needed on site, by someone who is not going to open a laptop.

The decision

A Streamlit form, a ReportLab renderer, and a lot of care in between.

Typography by metrics. The Word documents used Calibri. Carlito is its open, metric-compatible twin, so it is embedded in the PDF and every line breaks exactly where Word broke it.
Totals computed once. Subtotal, discount, tax, total, advance and balance are calculated in one place and formatted by one function, so the page can never disagree with itself.
The PDF remembers. After the document is drawn, the form data is appended to the file behind a %PEHESARA-DOC-V1: comment line. PDF readers ignore it and the app reads it back. Upload last month’s quotation and it becomes an editable form again, with no database and nothing extra to host.

The outcome

Most of the engineering story is about the host. Streamlit Community Cloud started pulling newer pandas and pyarrow builds that crashed the items table with a segmentation fault, and it could choose a Python version for which the pinned packages had no prebuilt wheels, so the build itself failed. The fix was to pin what the app actually imports (Streamlit 1.50 and ReportLab 4.2.5), pin the runtime to Python 3.12, and document the one deployment setting that matters for whoever deploys next.

Then a mobile pass, because the people using it are on phones. The engine is in daily use for the firm’s invoices and quotations.