---
title: "LaTeX Journal Template Converter for Easy Formatting"
url: https://stacklist.com/card/779a0bbe-ab76-44bc-a002-babb8c15eee1
source_url: "https://github.com/sachugowda/Latex_Journal_to_Journal_Template_Converter"
stack: https://stacklist.com/stack/6fc7d3f0-6685-4e31-8ceb-c4229649fa41
summary: "LaTeX Journal Template Converter is a Python tool that automatically converts academic papers from one journal's LaTeX template to another, handling multi-file projects, figures, and bibliographies while generating a review checklist for manual verification. It extracts content into an intermediate format and re-emits it using the target journal's structure, though users must still verify submission requirements against journal guidelines."
tags: "latex, journal-template, conversion-tool, document-processing, overleaf, automation, bibliography"
key_entities: "LaTeX (technology), Python (technology), Overleaf (technology), IEEE (organization), Springer (organization), Springer Nature (organization), document-class-conversion (concept), template-agnostic-format (concept)"
classification: "tutorial"
content_hash: "sha256:45f23f92b31cc2791fc6f61952bf310d2f86c3e76ee09d78eba0174ac9d0ca98"
acp_version: "0.2"
token_counts_approximate: 1724
visibility: public
agent_accessible: true
status: "final"
---

# LaTeX Journal Template Converter for Easy Formatting

LaTeX Journal Template Converter Converts a LaTeX paper written for one journal's template into another — for reuse after a rejection, or when re-targeting a paper to a different venue. Works with whole Overleaf projects (multi-file, figures, .bib ) and any target journal, not a fixed list — it reads the target's own template to figure out how to structure the output. What this does: extracts your paper's content (title, authors, abstract, sections, figures, tables, bibliography) into a template-agnostic intermediate format, then re-emits it using the target template's structure and commands, adding placeholders for any journal-required sections your source didn't have (e.g. "Data Availability", "Competing Interests"). What this does NOT do: guarantee a submission-ready file. LaTeX journal classes have too many idiosyncrasies (custom macros, exact word/reference limits, house style rules that change over time) for any script to promise 100% automated conversion. Every run produces a REVIEW_CHECKLIST.md alongside the output — treat that as required reading, not boilerplate. Requirements Python 3.8+. No external dependencies (standard library only). Usage Point --input at your source project and --output-template at an empty/unmodified template project for the target journal — Overleaf: open the target journal's official template (gallery or the journal's own submission-guidelines page), download as zip before writing anything into it , so it still has its own sample title/author/abstract content. python3 convert_project.py --input my_source_project.zip \ --output-template empty_journal_template.zip \ --output my_paper_converted.zip The tool reads that sample content to work out how the target journal expects things structured — documentclass, author-block style (IEEE's \IEEEauthorblockN/A , LNCS/Springer's \inst{N} indexing, Springer Nature's \fnm{}/\sur{}/\orgdiv{} convention, or a generic \author{}/\address{} fallback), whether the abstract is a \begin{abstract} environment or a plain \abstract{} command (matters — some classes only define one of the two), keyword syntax, declaration sections it requires (detected from real section headings in the sample, not a fixed list), and bibliography style. It also copies the target's own .cls / .sty / .bst files into the output zip, so the result is self-contained. Handles: Multi-file source projects ( \input{} / \include{} 'd section files, a separate macros.tex , etc.) — everything gets merged before conversion. Custom \newcommand / \newenvironment macros — detected and carried over into the new preamble automatically. Figures and .bib files — copied into the output zip at the same relative paths your \includegraphics / \bibliography commands expect. Auto-detects the main .tex file in both the source and target template projects. Override with --main-tex (source) / --output-template-main-tex (target) if it picks the wrong one. Output zip contains: main.tex (converted), all referenced figures/bib files, the target's .cls / .sty / .bst files, REVIEW_CHECKLIST.md , CONVERSION_NOTES.txt , and the intermediate JSON ( _parsed_content.ir.json ) for transparency if something looks off. Known limits of the auto-detection: it can only detect what's actually demonstrated in the template's sample content — if the sample doesn't show a structured abstract or doesn't list every declaration section the journal actually requires, those won't be detected. Always cross-check against the journal's current submission guidelines before submitting; this tool saves the mechanical rebuilding work, it doesn't replace reading the guidelines. Known limitations (be aware of these) Author/affiliation parsing is heuristic. It handles plain \author{A \and B} , IEEE's \IEEEauthorblockN/A , IEEE's \thanks{} -based per-group affiliation style (plain-English "A, B, and C are with..." name lists, including braced multi-email shorthand like \{a, b, c\}@domain and authors with two institutions via "...and also with..."), LNCS/Springer's \inst{N} - indexed style (including multiple numbers per author, e.g. \inst{1,2} ), and Springer Nature's \fnm{}/\sur{}/\orgdiv{} convention on BOTH the source and target sides (separate numbered \author*[N]{} / \affil[N]{} commands, multi-affiliation authors, per-author \email{} ; first/last name split is a best-effort split on the last space — check compound surnames manually). Unusual macro-heavy author blocks may still need manual cleanup. The parser recognizes both common syntax variants for abstract ( \begin{abstract} environment or a plain \abstract{} command) and keywords ( \keywords{} command, IEEE's \begin{IEEEkeywords} environment, or Elsevier's \begin{keyword} environment) on the SOURCE side, and strips whichever one is actually used out of the body before conversion — so a source written in one journal's syntax doesn't leak that class-specific syntax untouched into a target that doesn't define it. When an author's affiliation genuinely can't be detected from the source, the tool emits a short [Affiliation not detected] bracket placeholder in the actual field (safe to compile, clearly visible to edit) plus a % comment with the full explanation — never a long TODO sentence inside a rendered command argument, since that can visibly break the compiled output's front matter. Auto-detection only knows what the target template's sample content actually demonstrates — a declaration section, structured-abstract format, or author style the sample doesn't show won't be detected. It scans both the preamble and body for author/keyword/abstract commands (some classes put these before \begin{document} , others after), but a genuinely unusual template layout can still be missed. Figures/tables are carried over as raw LaTeX blocks (paths, captions, labels preserved) rather than re-validated against the new template's column layout — dense multi-panel figures sized for a single-column source may need figure* / table* (double-column-spanning) in a two-column target to stay legible; check after converting. This tool does not know current journal-specific word/reference/page limits — those change over time and must be checked on the journal's site. Files convert_project.py - entry point: whole project .zip -> ready-to-upload .zip latex_parser.py - source .tex -> intermediate representation (also usable standalone) template_profile.py - analyzes an empty target template zip -> structure profile render_template.py - intermediate representation + profile -> target .tex + checklist samples/ - example multi-file IEEE project, for testing latex_parser.py can also be run standalone for debugging ( python3 latex_parser.py mypaper.tex -o mypaper.ir.json — dumps the parsed intermediate representation without converting anything). render_template.py and template_profile.py are library modules only, imported by convert_project.py .