quarto-dev/quarto-cli

Open-source scientific and technical publishing system built on Pandoc.

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Summary Information

Updated 57 minutes ago
Added to GitGenius on September 11th, 2026
Created on September 25th, 2020
Open Issues & Pull Requests: 1,880 (+0)
GitHub issues: Enabled
Number of forks: 455
Total Stargazers: 5,994 (+0)
Total Subscribers: 29 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 0.5 hours
Mean response time: 12.3 days
90th percentile: 2.6 days
Tracked items: 2,322

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 58% of open issues come from outside the core team, a mix of external reports and the maintainers' own roadmap. 43% of tracked open issues have had no activity in three months. Only 3% of issues opened in the past year have been closed. Three people close 74% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 1,285
New in 7 days: 8
Closed in 7 days: 4
Avg open age: 729 days
Stale 30+ days: 1,215
Stale 90+ days: 828

Recent activity

Opened in 7 days: 8
Closed in 7 days: 4
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (1,198)
  • enhancement (634)
  • support (255)
  • documentation (202)
  • themes (134)
  • latex (128)
  • crossref (121)
  • html (119)

Detailed Description

Quarto is an open-source scientific and technical publishing system built on Pandoc that transforms Markdown documents into multiple output formats.

Quarto solves the problem of integrating executable code with technical documentation by embedding code and output from Python, R, Julia, and JavaScript through Jupyter, Knitr, and Observable. It extends Pandoc's Markdown with features designed for technical writing—cross-references, sub-figures, layout panels, callouts, and interactive citations—and provides a project system for rendering multiple documents together with shared configuration, enabling the creation of websites and books from collections of source files.

The tool suits researchers, data scientists, and technical writers who want to combine narrative prose with live code execution and produce polished output across formats. It integrates with popular editors and notebooks including JupyterLab, RStudio, and VS Code, and includes a visual Markdown editor for long-form document composition. Developers can author in their preferred environment rather than being locked into a single tool.

The project maintains active continuous integration with parallel smoke tests and automated installer builds. Development follows a structured release process with both stable and prerelease versions tracked through GitHub releases. The codebase is written primarily in JavaScript and accepts contributions through standard pull request workflows, with a test suite that developers can run locally to validate changes before submission.