quarto.org

Quarto is an open-source scientific and technical publishing system for turning source text and code into finished documents. You write in Jupyter notebooks or plain-text Markdown in your preferred editor, and Quarto renders the result as articles, presentations, dashboards, websites, blogs, or books in HTML, PDF, MS Word, ePub, and other formats. It is a good fit if you already work in Python, R, Julia, or JavaScript/Observable and want reproducible output from the same file that contains your analysis.

What Quarto actually does

Quarto sits between your writing and your final output. The input is a Markdown or notebook file that mixes prose with executable code blocks. Quarto runs the code, captures the results (tables, plots, numbers), and produces a formatted document where the text and results stay in sync.

The site describes it as a multi-language, next-generation version of R Markdown from Posit. Like R Markdown, Quarto uses knitr to execute R code, so most existing .Rmd files render without modification.

Supported languages

You can author in a traditional notebook UI or in a plain-text Markdown representation of a notebook — the choice does not change the output pipeline.

What you can produce

Quarto targets a wide range of publication types from the same authoring approach:

• Articles and reports — reproducible, production-quality documents
• Presentations — slide decks
• Dashboards — data displays
• Websites and blogs — multi-page sites
• Books — long-form publications

Output formats include HTML, PDF, MS Word, ePub, and more. For organizational sharing, Quarto can publish to Posit Connect, Confluence, or other publishing systems.

Authoring features

Quarto uses Pandoc Markdown, which covers the things technical writers usually need:

• Equations
• Citations
• Cross-references
• Figure panels
• Callouts
• Advanced layout

A minimal document shows the pattern — YAML front matter for metadata and format options, then prose and code:

---
title: "ggplot2 demo"
author: "Norah Jones"
date: "5/22/2021"
format:
  html:
    fig-width: 8
    fig-height: 4
    code-fold: true
---

## Air Quality

@fig-airquality further explores the impact of temperature on ozone level.

```{r}
#| label: fig-airquality
#| fig-cap: "Temperature and ozone level."
#| warning: false
library(ggplot2)

ggplot(airquality, aes(Temp, Ozone)) +
  geom_point() +
  geom_smooth(method = "loess")

The `#|` lines are cell options: they label the figure so it can be cross-referenced, attach a caption, and suppress warnings. The same structure works for Julia, with an `engine: julia` setting in the front matter and `{julia}` code blocks.

## Who it is for

Quarto suits people who need documents where the analysis and the write-up live in one reproducible file:

- **Data scientists and analysts** who want reports that regenerate when data or code changes
- **Researchers** who need citations, equations, and cross-references alongside computation
- **Technical writers and educators** producing books, course sites, or blogs with embedded code
- **Teams** that need to publish consistent output to a shared platform

If your work is purely prose with no code, a standard Markdown editor or static site generator may be simpler. Quarto's value comes from executing code and keeping results reproducible.

## How to get started

The site's own path is: Overview → Get Started → Guide, with Extensions, Reference, Gallery, Blog, and Help as supporting sections. There is also a FAQ and a place to report bugs or ask questions. Start with the Get Started page for your language, render the sample document, then move to the Guide for the format you need.

An open-source UI element library is a collection of individual, ready-made interface pieces—buttons, cards, inputs, toggles, loaders—that you copy into your own project and adapt. A UI framework, by contrast, is a structured system of components, conventions, and often a theming layer that governs how your whole interface is built. The practical difference: an element library gives you a snippet; a framework gives you a way of working. If you need a polished button in ten minutes, reach for the element library. If you're building a 40-screen product with a team, you probably want the framework.

What "open-source UI element library" actually means

The term gets used loosely, so it helps to separate the parts:

• Open-source: the code is publicly available, and the license tells you what you may do with it—copy, modify, redistribute, or use commercially.
• UI element: a single, self-contained piece of interface, usually small enough to read in one sitting. A button with hover states, a pricing card, a search field.
• Library: a browsable, searchable collection of those elements, typically contributed by many different people.

On a site like Uiverse, elements are shared by a community and written in plain CSS or Tailwind. You find one you like, copy the markup and styles, paste them into your project, and adjust colors, spacing, and text to fit. There's no package to install and no build step required—which is exactly the appeal, and also the source of most of the confusion.

Element library vs. UI framework: the core differences

The table isn't a verdict. It's a map of trade-offs. Element libraries win on speed and freedom; frameworks win on consistency and maintenance.

Licensing and attribution: what to check before you paste

This is where people get into trouble, and it's worth slowing down for.

1. Find the license. Every element or collection should state one. Common open-source licenses include MIT, Apache-2.0, and BSD. Some projects use copyleft licenses like GPL, which can impose obligations if you redistribute your code.
2. Understand what the license permits. MIT and Apache-2.0 are permissive: you can typically use the code in commercial and closed-source projects. Copyleft licenses may require you to release derivative source under the same terms.
3. Check attribution requirements. Permissive licenses usually require you to keep the copyright notice and license text somewhere in your project. That's a real obligation, not a formality.
4. Look for per-element terms. On community sites, the site's overall terms and the individual contributor's stated wishes may differ. If a contributor asks for credit, honor it.
5. When in doubt, ask or avoid. If a snippet has no license at all, you don't have clear permission to reuse it. Treat "no license" as "not open source," even if the code is publicly visible.

This article is general information, not legal advice. For commercial products with real exposure, have someone qualified review the licenses you're relying on.

How to use a community element in your project: a practical workflow

Here's a repeatable process that avoids most of the usual mess.

1. Start from a real need, not a browsing session

Decide what you need first—"a compact primary button with a loading state"—then search. Browsing aimlessly produces a pile of pretty snippets that don't fit together.

2. Copy the smallest version that works

Take the markup and the styles. Strip anything you don't need: demo wrappers, extra animations, decorative layers. Less code means fewer surprises.

3. Convert it to your conventions

If your project uses design tokens or CSS variables, replace hard-coded values:

/* Before: hard-coded */
.button { background: #4f46e5; border-radius: 8px; }

/* After: token-based */
.button { background: var(--color-primary); border-radius: var(--radius-md); }

This one step is what keeps a copied element from looking like a foreign object in your UI.

4. Check accessibility before you ship

Community elements vary widely here. Verify at minimum:

• Keyboard focus is visible and the element is reachable by Tab.
• Color contrast meets WCAG AA (4.5:1 for normal text).
• Interactive elements use semantic HTML (<button>, not a clickable <div>).
• Form inputs have associated labels.
• Motion respects prefers-reduced-motion.

5. Test in context

Paste it into a real page with real content. Long labels, small screens, and dark mode break more copied elements than anything else.

6. Note where it came from

Keep a short comment or an internal credits file: source, license, date. Future you—and your legal reviewer—will be grateful.

Where element libraries genuinely shine

• Prototypes and demos: you need something clickable today, not a design system.
• Landing pages and marketing sites: a handful of distinctive elements, each custom.
• Filling gaps: your framework lacks one specific component, and you don't want to build it from scratch.
• Learning: reading well-made CSS is one of the fastest ways to improve.
• Small projects: a personal site doesn't need a theming architecture.

Where they fall short

• Consistency at scale: ten elements from ten contributors rarely look like one product.
• Maintenance: you own every copy. When your design changes, you edit each one.
• Accessibility debt: you inherit whatever the contributor did or didn't do.
• No upstream fixes: a bug fixed in the original won't reach your copy.
• Integration friction: different naming conventions, different units, different assumptions about resets.

When to choose which

Choose an element library when the scope is small, the timeline is short, or you need a few distinctive pieces rather than a whole system.

Choose a framework or design system when multiple people build multiple screens over months, when consistency is a product requirement, or when accessibility and theming need to be guaranteed rather than checked.

A hybrid works well for many teams: adopt a framework for the structural components—forms, navigation, layout—and borrow individual elements for the places where you want personality. Just route every borrowed element through the same token and accessibility checks, so it lands as part of your system rather than beside it.

The short version: open-source UI element libraries are a fast, flexible way to get good-looking interface pieces into a project. They are not a substitute for a design system, and the license and accessibility details are the part worth reading carefully.

Quarto is an open-source scientific and technical publishing system for creating articles, websites, blogs, books, and slides. To get started, you author documents in Jupyter notebooks or plain-text Markdown in your preferred editor, then render them into formats like HTML, PDF, MS Word, and ePub. The official Get Started and Guide pages are the intended entry points, and the Hello, Quarto examples walk through Python, R, Julia, and Observable.

What Quarto Is and What You Need

Quarto is described as a multi-language, next-generation version of R Markdown from Posit. It executes code from Python, R, Julia, and Observable, and produces reproducible, production-quality output.

Before you begin, decide two things:

• Your authoring environment — a Jupyter notebook UI, or plain-text Markdown in any editor you already use.
• Your language and output format — for example Python with HTML output, or R with PDF.

You do not need to pick a single language for everything; Quarto supports all four across the same authoring workflow.

Step 1: Read the Official Entry Points

Start with the two documentation sections the site highlights:

1. Get Started — installation and a first document.
2. Guide — the full authoring and publishing reference.

These are the canonical starting points rather than third-party tutorials, so version-specific behavior matches what you are running.

Step 2: Choose How You Author

Quarto supports two authoring styles, and you can move between them:

The site notes that you can author using traditional notebook UIs or with a plain-text Markdown representation of notebooks — so the same project can be handled either way.

Step 3: Work Through "Hello, Quarto"

The Hello, Quarto examples cover Python, R, Julia, and Observable. Working through at least one gives you a complete, renderable document.

A representative R example from the site shows the structure:

---
title: "ggplot2 demo"
author: "Norah Jones"
date: "5/22/2021"
format:
  html:
    fig-width: 8
    fig-height: 4
    code-fold: true
---

## Air Quality

@fig-airquality further explores the impact of temperature on ozone level.

```{r}
#| label: fig-airquality
#| fig-cap: "Temperature and ozone level."
#| warning: false
library(ggplot2)
ggplot(airquality, aes(Temp, Ozone)) +
  geom_point() +
  geom_smooth(method = "loess")

Note the three parts: a YAML header for metadata and format options, prose with a cross-reference (`@fig-airquality`), and a code block with `#|` options controlling the figure label, caption, and warnings.

A Julia example follows the same pattern, adding an engine declaration:

```markdown
---
title: "Plots Demo"
format:
  html:
    code-fold: true
engine: julia
---

## Parametric Plots

Plot function pair (x(u), y(u)). See @fig-parametric for an example.

```{julia}
#| label: fig-parametric
#| fig-cap: "Parametric Plots"
using Plots
plot(sin, x->sin(2x), 0, 2π, leg=false, fill=(0, :lavender))

**Expected result:** rendering produces an HTML document with the figure, its caption, and a working cross-reference. If a figure or reference does not appear, check that the `#| label:` value matches the `@` reference exactly.

## Step 4: Learn the Markdown Features You Will Actually Use

Quarto uses Pandoc Markdown. The site lists these capabilities as part of the core authoring model:

- Equations
- Citations
- Cross-references
- Figure panels
- Callouts
- Advanced layout

You do not need all of these on day one. Add them as your documents require them, using the Guide as reference.

## Step 5: Publish

Quarto can publish to Posit Connect, Confluence, or other publishing systems, which the site frames as a way to share knowledge organization-wide. Output formats include HTML, PDF, MS Word, and ePub.

If you are publishing internally, confirm which system your organization uses before building a workflow around one target.

## If You Are Coming From R Markdown

Quarto uses knitr to execute R code and can render most existing `.Rmd` files without modification, according to the site. That means an existing R Markdown project is a reasonable first test case: render it under Quarto and see what needs adjusting.

## Where to Get Help

The site points to several support channels:

- **FAQ** — common questions
- **Ask a Question** — community help
- **Report a Bug** — issue reporting
- **Extensions** and **Gallery** — examples and add-ons to learn from

## Common Starting Points to Watch

- **Engine mismatch:** if you declare `engine: julia` but the code is R, rendering fails. Match the engine to the code block language.
- **Cross-reference typos:** a label of `fig-airquality` must be referenced as `@fig-airquality`.
- **Format options placement:** figure sizing and code folding belong under the `format:` key in the YAML header, nested under the target format (for example `html:`).

The fastest path is: read **Get Started**, render one **Hello, Quarto** example in your language, then consult the **Guide** as you add features.

Quarto is a next-generation version of R Markdown from Posit. It keeps the core R Markdown workflow — write markdown, embed code, render to a document — but broadens it into a multi-language publishing system. According to Quarto's own documentation, it "uses knitr to execute R code, and is therefore able to render most existing Rmd files without modification." So if you already have R Markdown documents, you can often point Quarto at them and get output without rewriting anything.

What stays the same

• Authoring model. You write Pandoc markdown with embedded code chunks, then render to a final format. The YAML header still controls title, author, date, and output format.
• R execution path. Quarto runs R code through knitr, the same engine R Markdown uses. Existing R chunks and most R-specific behavior carry over.
• Output formats. Both target HTML, PDF, Word, and more, so the publishing destinations you already use remain available.

What changes

Language scope

R Markdown is centered on R. Quarto is explicitly multi-language: the documentation describes dynamic content with Python, R, Julia, and Observable, and notes it supports Python, R, Julia, and JavaScript. The same document structure works across engines, so a team using both R and Python doesn't need two separate toolchains.

Engine options

For R, Quarto uses knitr as described above. For Julia, the documentation says Quarto executes code either via the julia engine using QuartoNotebookRunner.jl or via the jupyter engine using the IJulia Jupyter kernel. That engine choice is a Quarto concept — you can author in plain text or render existing Jupyter notebooks.

Authoring surface

You can author using Jupyter notebooks or plain text markdown in your editor. R Markdown is primarily a plain-text markdown workflow, so notebook-based authoring is a wider option in Quarto.

Markdown features

Quarto's Pandoc markdown includes equations, citations, crossrefs, figure panels, callouts, and advanced layout. Some of these (crossrefs, callouts, panels) are Quarto additions rather than things you'd get from a stock R Markdown setup.

Should you migrate?

How to check compatibility on a real document

1. Take one existing .Rmd file.
2. Render it with Quarto instead of rmarkdown::render().
3. Compare the output against your current version — check figures, tables, cross-references, and the YAML header behavior.
4. If it renders as expected, you can migrate incrementally; if not, keep that file on R Markdown while you move the rest.

The expected result is that a typical R-only Rmd renders without edits. The common sticking point is anything tied to R Markdown-only options or packages, which is why testing one representative file beats migrating everything at once.

Bottom line

Quarto is not a replacement you must adopt immediately — it's a superset built on the same R execution path. If your work is R-only and stable, staying on R Markdown is fine. If you want multi-language support, notebook authoring, or the newer markdown features, Quarto is the forward path, and your existing Rmd files are the starting point rather than a rewrite.

Quarto's authoring layer is Pandoc markdown plus a set of extensions aimed at scientific and technical documents. If you need equations, citations, cross-references, figure panels, callouts, or advanced page layout in a reproducible document, you can write all of it in plain text and render to HTML, PDF, MS Word, ePub, and more. The features below apply when you author in markdown (or in a Jupyter notebook, which Quarto can also render).

The base: Pandoc markdown

Quarto documents are written in Pandoc markdown, so standard markdown syntax works, and the Pandoc extensions for scholarly writing are available. This is the foundation the rest of the authoring features build on.

Scientific writing features

The Quarto overview lists these markdown capabilities explicitly:

• Equations — mathematical notation in your source text.
• Citations — reference management integrated into the markdown.
• Cross-references — link to figures, tables, sections, and other labeled elements.
• Figure panels — compose multi-part figures.
• Callouts — highlighted notes, warnings, and tips.
• Advanced layout — control how content is arranged on the page.

A cross-reference in practice looks like @fig-airquality in the body text, paired with a label on the code chunk that produces the figure. Quarto resolves the label to the correct number and link at render time.

Dynamic content inside markdown

Markdown is not static here. You can embed executable code from Python, R, Julia, and Observable, and the output — plots, tables, computed values — is inserted into the rendered document. The overview describes this as creating "dynamic content" and publishing "reproducible, production quality" output.

A minimal R example from the site shows the pattern:

---
title: "ggplot2 demo"
author: "Norah Jones"
date: "5/22/2021"
format:
  html:
    fig-width: 8
    fig-height: 4
    code-fold: true
---

## Air Quality

@fig-airquality further explores the impact of temperature on ozone level.

```{r}
#| label: fig-airquality
#| fig-cap: "Temperature and ozone level."
#| warning: false
library(ggplot2)
ggplot(airquality, aes(Temp, Ozone)) +
  geom_point() +
  geom_smooth(method = "loess")

The chunk options (`label`, `fig-cap`, `warning`) are written as comments inside the code block, which is how you attach behavior to a chunk without leaving markdown.

## Authoring tools and formats

You can write in a Jupyter notebook UI or in plain text markdown in your editor of choice. The same source can render to HTML, PDF, MS Word, ePub, and other formats, and can be published to systems such as Posit Connect or Confluence.

## How this relates to R Markdown

Quarto is described as a multi-language, next-generation version of R Markdown from Posit. It uses knitr to execute R code, so most existing `.Rmd` files render without modification. If you already have R Markdown documents with equations, citations, and cross-references, that investment carries over.

## What to check before committing

- **Format needs**: confirm your target output (HTML, PDF, Word, ePub) is among the supported formats for your workflow.
- **Language**: Python, R, Julia, and Observable are supported; pick the engine that matches your code.
- **Existing documents**: if you have R Markdown files, they are likely to render as-is, which lowers migration cost.
- **Publishing target**: if you need to publish to Posit Connect, Confluence, or another system, verify that path fits your organization.

For the exact syntax of each feature, the Quarto Guide and Reference sections are the authoritative sources; the overview page establishes what is available, not the full grammar.