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The Triplicate: A Data-Driven Large-Format Newspaper Layout Engine

Authors: Daniel Ari Friedman;

The Triplicate: A Data-Driven Large-Format Newspaper Layout Engine

Abstract

Abstract We present template_newspaper, a pure-Python engine that renders a complete twelve-page, large-format newspaper to a print-ready PDF from structured YAML content. The exemplar edition is The Triplicate, a homage to the historic newspaper of Crescent City, California (founded 1879). The engine demonstrates designed multi-column page layout — nameplate and ears, spanning headlines, flowing column frames with an optional rail, drop caps, pull quotes, ruled modular boxes, data tables, halftone "engraving" figures and running folios — while keeping a strict separation between content (data) and engine (code): a new title is a data edit, never a code change. The layout strategy is a hybrid in which fixed furniture is drawn directly on the canvas to establish where the column grid begins, after which body copy flows through ReportLab frames that split paragraphs across columns automatically. The project obeys the research-template monorepo contract and is discovered and executed by the same orchestration pipeline as its code- and prose-focused siblings. --- Associated artifacts GitHub release: v1.0.0 (https://github.com/docxology/template_newspaper/releases/tag/v1.0.0) PDF SHA-256: 5c991b5c4c7bb59fd7d7253d7293ec3c3ba2f6262a9e3ba8f1fc224b1c276f03

Keywords

document engineering, typography, reportlab, newspaper layout, reproducible publishing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average