cli
Tools for making beautiful & useful command line interfaces
The cli package provides tools for building command line interfaces in R using semantic elements like headers, lists, alerts, and paragraphs. It supports terminal styling through ANSI colors and font attributes, making console output more readable and visually organized.
The package integrates with the glue package for string interpolation, supports automatic pluralization of messages, and includes progress bars that work from both R and C code. It offers CSS-like theming for customizing the appearance of CLI elements and provides Unicode symbols with ASCII fallbacks for broader terminal compatibility. The package handles both high-level semantic formatting and lower-level primitives like rules, boxes, and trees.
Contributors#
Resources featuring cli#
What even is dbt? An Analytics engineer explains | Laurie Merrell & Michael Chow | Data Science Lab
The Data Science Lab is a live weekly call. Register at pos.it/dslab! Discord invites go out each week on lives calls. We’d love to have you!
The Lab is an open, messy space for learning and asking questions. Think of it like pair coding with a friend or two. Learn something new, and share what you know to help others grow.
On this call, Libby Heeren is joined by Jarvis Innovations Lead Analytics Engineer Laurie Merrell and Posit Principal Software Engineer Michael Chow as they walk us through a beginner dbt project and let us ask as many questions as we like (and we do, we ask all the questions, including, WHAT EVEN IS dbt??). This is a super friendly, MESSY, collaborative, and curious peek at dbt. It’s is a tool that’s often mysterious to data scientists and it’s a big enough framework that it can feel tough to get started with. Walking through the basics makes it way easier to get into!
Hosting crew from Posit: Libby Heeren, Isabella Velasquez
Laurie’s LinkedIn: https://www.linkedin.com/in/laurie-merrell/
Michael’s socials and urls: LinkedIn: https://www.linkedin.com/in/michael-a-chow/ Bluesky: https://bsky.app/profile/mchow.com GitHub: https://github.com/machow
Resources from the hosts and chat:
Michael Chow’s talk about dbt at the Coalesce Conference in 2022: https://www.youtube.com/watch?v=EYdb1x1cO9U Beginner dbt project Michael is using: https://github.com/dbt-labs/jaffle_shop_duckdb Laurie’s Coalesce talk with Ian and Jenna: https://www.youtube.com/watch?v=6aX7tAfMmIM Link to installation page for the DuckDB CLI: https://duckdb.org/install/?platform=macos&environment=cli “Why is dbt so important” shared by Jenna in the chat: https://highgrowthengineering.substack.com/p/why-is-dbt-so-important- dbtplyr: https://hub.getdbt.com/emilyriederer/dbtplyr/latest/ Parquet: https://parquet.apache.org/ From stored procedures to dbt: A modern migration playbook: https://www.getdbt.com/blog/stored-procedures-dbt-migration-playbook How to structure our dbt projects: https://docs.getdbt.com/best-practices/how-we-structure/1-guide-overview Jenna Jordan’s blog on dbt mesh: https://jennajordan.me/blog/data-mesh-dbt
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Thanks for learning with us!
Timestamps 00:00 Introduction 01:09 Guest introductions: Michael Chow and Laurie Merrell 04:15 Overview of today’s session 05:51 Setting up the GitHub Codespace 07:00 The data science workflow vs. organizational needs 10:06 Why dbt is hard to learn in the abstract 13:34 “Could we back up and explain what dbt is again?” 19:12 Running ‘dbt build’ 20:00 Inspecting the database with DuckDB CLI 26:21 “Does dbt have concurrency or dependency capabilities?” 27:37 Understanding the ‘ref’ macro 29:52 “Is dbt an orchestrator?” 31:14 “Starting a project from scratch with just SQL?” 32:04 “How is this better than writing Python scripts?” 35:46 “Is data source detection dynamic with dbt?” 38:36 Generating and serving dbt docs 46:51 “Is dbt an IDE like RStudio, but for SQL?” 52:32 Branching and development environments 53:57 “Where would you begin on a brand new project?” 56:38 “How would you validate dependencies and downstream impacts?” 57:48 Defining a view versus a table
Create a Quarto Document in Positron (Python Example)
Watch Charlotte Wickham’s Positron Quarto tutorial to see the full process of creating, rendering, and publishing your first Quarto document with ease.
Discover why Positron is the best environment for Quarto documents. We walk you through key features that streamline your work:
• Quarto CLI and the Quarto extension are pre-installed. You can start creating and rendering right out of the box! • Use handy buttons, commands (Quarto: New Document, Quarto: Preview), and shortcuts to complete common tasks quickly. • Get comprehensive support for code cells with code completion, linting, and integrated documentation for R and Python. • Benefit from suggestions and warnings as you configure document and code cell options in the header. • Easily access the full quarto command-line interface, including the powerful quarto publish command.
Read the blog post: https://posit.co/blog/create-a-quarto-document-in-positron/
Resources Mentioned:
• Quarto in the Positron Guide: https://positron.posit.co/quarto.html • Getting Started with Quarto in Positron (R/Python): https://quarto.org/docs/get-started/hello/positron.html • Positron in the Quarto Guide: https://quarto.org/docs/tools/positron/
#Quarto #Positron #DataScience #QuartoTutorial #PositronIDE #DataVisualization #Publishing #RStats #Python #CodingWorkflow
It’s all fun and games til your analysis code is finished (Alex Rossell Hayes) | posit::conf(2025)
It’s all fun and games til your analysis code is finished: the player package in R Speaker(s): Alex Rossell Hayes
Abstract: The player package is a set of games built entirely in R that you can play in the R console. This lighthearted, humor-filled talk will introduce the package and demo some of its games, including opportunities for audience participation. If selected for a full talk, this will also include a demonstration of how the package code comes together, including approachable introductions to concepts like object-oriented programming with R6 and message handling with cli. The talk will show how playing around with R can be one of the best ways to learn new techniques (some of which can even be carried over into more serious programming).
player repo: https://github.com/rossellhayes/player posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/
Birthing the pregnancy package (Ella Kaye, University of Warwick) | posit::conf(2025)
Birthing the pregnancy package
Speaker(s): Ella Kaye
Abstract: When I was pregnant, I wrote a personal, private package for date and medication calculations, hard-coded with my data. I thought it would be easy to adapt for general use, but no! I wanted the user experience to be excellent, but how to avoid them repeatedly entering the same due date and meds? How to print useful, nicely formatted, grammatically correct information to the console? How to test a package that relies on the current date? Using the pregnancy package as a case study, I’ll show how to take advantage of base R features such as global options and %||%, how the cli and rlang packages came to the rescue for messages and how testthat’s new mocking features saved the day (literally!) to create a package that’s a pleasure to use.
Slides: https://github.com/EllaKaye/pregnancy-lightning-talk posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/
Web applications with Shiny and React and AI (Winston Chang, Posit) | posit::conf(2025)
Web applications with Shiny and React (and AI)
Speaker(s): Winston Chang
If you’ve ever wanted to have complete control over the UI for a Shiny application, this talk might be for you. In this talk I’ll show how to integrate a back end written in Shiny (for R or Python) with a front end written in React.js. This lets you combine Shiny’s reactivity with the flexibility of the React web development ecosystem.
In the past, writing a front end in React was a large time investment, and would be reserved only for a serious project. However, with today’s agentic AI coding tools, it can make sense to create a React front end even for smaller-scale applications. But even with AI involved, you will still need to know some React or be willing to learn about it.
GitHub Repo - https://github.com/wch/shiny-react CLI tool - https://github.com/wch/create-shiny-react-app Anthropic Dashboard - https://github.com/wch/anthropic_dashboard posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/
Jeroen Janssens - Package Your Python Code as a CLI | PyData London 25
Learn how to transform your Python code into a command-line tool. Jeroen Janssens, author of Data Science at the Command Line, guides you through the process of turning your scripts into reusable, executable tools, integrating them into your data workflows and harnessing the power of the Unix command line.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
Quarto Crash Course | Create Professional Reports, Dashboards & Websites w/ Markdown & Python Code!
Welcome to this comprehensive Quarto crash course using Python! Whether you’re a complete beginner or an experienced user, this tutorial covers the topics you need to know about the Quarto publishing system.
We’ll explore:
- Basic setup and installation
- Creating HTML reports, PDFs, and interactive dashboards from your Python script or Jupyter notebook.
- Building presentations with Revealjs
- Customizing outputs with CSS and layouts (fenced divs, classes, and more)
- Working with parameters for dynamic reports
- Publishing to Posit Connect Cloud
- Creating complete websites
- Automated report generation
Perfect for data scientists, analysts, and developers looking to create beautiful, reproducible reports from their code. We’ll use Python throughout the tutorial with real-world examples using movie analytics data. Let’s dive in!
Video by @KeithGalli
Github repo: https://github.com/KeithGalli/quarto-crash-course
Deploy with Posit Connect Cloud! https://pos.it/keith_qc
#python #quarto #posit
— Resources Mentioned — Slideshow example: https://quarto.org/docs/presentations/revealjs/demo/#/title-slide Slideshow example (source code): https://github.com/quarto-dev/quarto-web/blob/main/docs/presentations/revealjs/demo/index.qmd Example HTML report: https://019302a7-e9e3-3454-3575-23148999a7f7.share.connect.posit.cloud/ Quarto Gallery: https://quarto.org/docs/gallery/ Bootstrap Icons: https://icons.getbootstrap.com/
Video timeline! 0:00 - About the Crash Course 0:50 - Quarto Overview 2:12 - Installation & Setup 6:22 - Markdown Basics 8:46 - Quarto Markdown Features 19:37 - Quarto Styling & Formatting (fenced divs, CSS classes, etc.) 34:53 - Parameters & CLI Options 40:46 - HTML & Publishing 49:46 - Static Docs (PDFs, Docx) 54:53 - Dashboards 1:06:50 - Slideshows (Revealjs) 1:16:11 - Websites 1:19:52 - Automated Report Generation (Parameterized Reports)
Creating tests for Shiny for Python apps | Karan Gathani | Posit
With the Shiny for Python v1.0 release, Shiny provides a simple way to create a test file for your Shiny app. The shiny add test command is a helpful CLI tool for Shiny app developers. It simplifies the process of creating test files for their applications.
When you run this command, it prompts you to input two pieces of information: the path to your Shiny app file and the desired location for the new test file.
Once you provide these details, the command automatically generates a test file at the specified location. This new file includes a pre-made test template, giving you a solid starting point for writing your app’s tests.
Reference documentation - https://shiny.posit.co/py/docs/unit-testing.html https://shiny.posit.co/py/docs/playwright-testing.html
How to build business reports with Quarto
How do you create the report look and feel that your leadership team expects?
Christophe Dervieux at Posit joined us on Wednesday, March 27th to share how to style Quarto docs and send scheduled email updates to required stakeholders.
Helpful resources: ️ Getting started with Quarto: https://quarto.org/docs/get-started ️ User guide: https://quarto.org/docs/guide ️ Github repo with this example: https://github.com/quarto-examples/quarto-business-report ️ Q&A Recording: https://youtube.com/live/bqk75igHo8M?feature=share ️ If you’re interested in learning more about Posit Connect, pos.it/chat-with-us
Timestamps: 02:00 - What is Quarto? 02:40 - How does Quarto work? (.md, .qmd or .ipynb as source files) 03:45 - How to get started with Quarto if you’re new to it? 04:51 - Using Quarto from within RStudio 05:00 - Using Quarto within VSCode with extension & Jupyter Lab extension 05:37 - Visual Editor for Quarto 07:22 - Customer Tracker Report in RStudio IDE (using source code: https://github.com/quarto-examples/quarto-business-report ) 10:39 - Making Quarto report downloadable as Excel doc (adding download button) 11:37 - Adding a table of contents to your Quarto report 12:23 - Spread Quarto graphics across page so that they go into margin 13:10 - Customizing theme in Quarto (Bootstrap 5) https://quarto.org/docs/output-formats/html-themes.html 14:45 - Increasing font size in Quarto report 17:10 - Customizing theme rules 21:16 - Publishing Quarto report to Posit Connect 22:35 - Scheduling Quarto report to automatically run 23:35 - Preview of default / non-customized email 23:58 - Customizing your Quarto email 26:52 - Customized email preview that Posit Connect can send 27:56 - Setting access controls for Quarto report on Connect and when you want emails to send
Resources shared in Q&A session: Community discussion for ongoing Quarto questions: https://forum.posit.co/tag/quarto Quarto document language: https://quarto.org/docs/authoring/language.html babelquarto (for multilingual project, book, or website): https://docs.ropensci.org/babelquarto/ Quarto Manuscripts: https://quarto.org/docs/manuscripts/ Managing Execution in Quarto: https://quarto.org/docs/projects/code-execution.html Quarto Extensions: https://quarto.org/docs/extensions/ Project Profiles in Quarto: https://quarto.org/docs/projects/profiles.html Custom branding deeper dive: https://www.youtube.com/watch?v=V82BBU9ldcM Quarto Parameters: https://quarto.org/docs/computations/parameters.html Lua Development: https://quarto.org/docs/extensions/lua.html Quarto CLI Discussions on Github: https://github.com/quarto-dev/quarto-cli/discussions Data Science Hangout every Thursday at 12 ET: https://posit.co/data-science-hangout/ Get connected with others at your org using Posit: pos.it/connect-us
There is no need to register; join us here on YouTube at the time above or you can add to your calendar using the link below:
pos.it/team-demo
We host these Workflow Demos on the last Wednesday of every month, so you can use the link above to add the recurring event as well. If you ever have ideas for topics or questions about them, you can comment below in YouTube!
Workflow Demo Live Q&A - March 27th
Q&A session from the March 27th Workflow Demo: Elevate your Quarto reports with styling and scheduled emails.
Demo recording: https://youtu.be/Hl9TvhlzfV4?feature=shared
Resources shared in Q&A session: Community discussion for ongoing Quarto questions: https://forum.posit.co/tag/quarto Quarto document language: https://quarto.org/docs/authoring/language.html babelquarto (for multilingual project, book, or website): https://docs.ropensci.org/babelquarto/ Quarto Manuscripts: https://quarto.org/docs/manuscripts/ Managing Execution in Quarto: https://quarto.org/docs/projects/code-execution.html Quarto Extensions: https://quarto.org/docs/extensions/ Project Profiles in Quarto: https://quarto.org/docs/projects/profiles.html Custom branding deeper dive: https://www.youtube.com/watch?v=V82BBU9ldcM Quarto Parameters: https://quarto.org/docs/computations/parameters.html Lua Development: https://quarto.org/docs/extensions/lua.html Quarto CLI Discussions on Github: https://github.com/quarto-dev/quarto-cli/discussions Data Science Hangout every Thursday at 12 ET: https://posit.co/data-science-hangout/
Demo: 11 am ET Q&A: ~11:30 am ET
![[84] Reproducible Publications with Python and Quarto (Thomas Mock)](/resources/videos/2023-07-11_84-reproducible-publications-with-python-and-quarto-thomas-mock/thumbnail_hu_9dfee706713141f4.webp)
![[84] Reproducible Publications with Python and Quarto (Thomas Mock)](/resources/videos/2023-07-11_84-reproducible-publications-with-python-and-quarto-thomas-mock/thumbnail_hu_1318342b0b0c9209.webp)
![[84] Reproducible Publications with Python and Quarto (Thomas Mock)](/resources/videos/2023-07-11_84-reproducible-publications-with-python-and-quarto-thomas-mock/thumbnail_hu_f56b6b1f48a2f23a.webp)
[84] Reproducible Publications with Python and Quarto (Thomas Mock)
Join our Meetup group: https://www.meetup.com/data-umbrella
Tom Mock: Reproducible Publications with Python and Quarto
Resources#
Full transcript#
https://blog.dataumbrella.org/quarto-blog
About the Event#
Quarto is an open-source scientific and technical publishing system that builds on standard markdown with features essential for scientific communication. The system has support for reproducible embedded computations, equations, citations, crossrefs, figure panels, callouts, advanced layouts, and more. In this talk we’ll explore the use of Quarto with Python, describing both integration with IPython/Jupyter and the Quarto VS Code extension. Users can author Jupyter notebooks or documents as plain text markdowns with code in Python, R, Julia or Observable. Quarto includes the ability to publish high-quality articles, reports, presentations, websites, blogs, and books in HTML, PDF, MS Word, ePub, Reveal.js and more.
Timestamps#
00:00 Data Umbrella introduction 03:41 Introduce the speaker, Thomas Mock 04:14 Thomas begins 05:14 RStudio is now Posit 05:55 What is Quarto? 07:13 Origins of Quarto 08:31 Goal: Computation Document 09:09 Goal: Scientific Markdown 10:03 Goal: Single Source Publishing 10:33 Simple example of what Quarto looks like (YAML, Markup, Markdown, code chunks) 12:29 Simple example: multi-format (output formats: html, pdf, docx, epub, pptx, revealjs) 13:16 List of what is possible with Quarto 14:02 So, what is Quarto: quarto is a language-agnostic command line interface (CLI) 15:27 Basic Quarto workflow 16:43 Difference between “render” and “preview” 17:16 IPython 18:43 Stored/frozen computation and reproducibility 20:36 A *.qmd is a plain text file 21:28 Quarto doesn’t have to be plain text 22:12 Rendering pipeline 22:57 What to do with my existing .ipynb? 24:23 Comfort of your own workspace: JupyterLab, Visual Studio Code, 25:00 Auto-completion in RStudio + VSCode 26:01 Quarto Extensions and Visual / Live Editor 27:19 Quarto, unified document layout 29:54 Quarto, unified syntax across Markdown and code 31:11 Built-in vs Custom 33:01 Extending Quarto with Extensions 33:51 Interactivity, Jupyter Widgets (with plots, matplotlib, etc) 34:15 Interactivity, Observable 35:01 Interactivity, on the fly Observable “widgets” 36:24 Parameters - one source, many outputs 37:36 Rendering with parameters 38:27 Quarto Publish 38:57 Quarto, crafted with love and care (the team) 39:30 Quarto Resources (installation) 39:44 Quarto resources: video tutorials 40:13 Q: Can Quarto documents be shared like Overleaf docs and can users import article templates for specific journals into Quarto? 41:39 new! Manuscript option to bundle an entire project together (bundle can be shipped to a journal) 42:48 Q: Is Quarto git friendly? 43:28 Q: Has Quarto already been used in published scientific work? 44:14 publishing books with Quarto 44:22 Q: Any general suggestions for outputting to docx (Word)? 45:20 Q: Any tips on how Quarto can help conda users? 46:14 Q: Can you use GitHub Actions with Quarto? 47:18 Q: Can you have individual environments for each blog post? 49:50 Download CLI (command line interface) for Quarto 51:10 Example Gallery 51:44 nbdev project 53:14 Quarto blog, Shinylive extension 55:12 Q: How can I use Quarto to write scientific papers?
About the Speaker: Tom Mock#
- Twitter: https://twitter.com/thomas_mock
- GitHub: https://github.com/jthomasmock
#python #quarto #rstats
Quarto with the Quarto Team | An Open-Source Chat
Join Al Manning, Carlos SchIidegger, & Charles Teague, members of the Quarto Team, as they take our questions.
Quarto is an open-source tool for scientific and technical publishing. Create dynamic content with Python, R, Julia, and Observable. Author documents as plain text markdown or Jupyter notebooks. Publish high-quality articles, reports, presentations, websites, blogs, and books in HTML, PDF, MS Word, ePub, and more. Author with scientific markdown, including equations, citations, crossrefs, figure panels, callouts, advanced layout, and more.
Key Resources: ⬡ Learn more and get started with Quarto at quarto.org
Contact ⬡ Bug reports and feature requests - https://github.com/quarto-dev/quarto-cli/issues ⬡ Need help? Github discussions - https://github.com/quarto-dev/quarto-cli/discussions
Introduction Videos for Quarto ⬡ Mine and Julia talk, https://www.youtube.com/watch?v=p7Hxu4coDl8 ⬡ Quarto Series, 1️⃣ Welcome to Quarto Workshop led by Tom Mock: https://www.youtube.com/watch?v=yvi5uXQMvu4 2️⃣ Building a Blog with Quarto led by Isabella Velásquez: https://www.youtube.com/watch?v=CVcvXfRyfE0&feature=youtu.be 3️⃣ Beautiful reports and presentations with Quarto led by Tom Mock: https://www.youtube.com/watch?v=hbf7Ai3jnxY&feature=youtu.be
Timestamps
00:00:00 Introductions
2:55 Why open source?
6:20 Can we expect to see Quarto available to R-users via CRAN any time soon?
9:10 Quarto and Google Docs?
9:49 Lua filters/shortcodes. Advice for a good development environment for prototyping and debugging?
14:59 Is there a single documentation page for ALL the quarto-specific YAML options? https://quarto.org/docs/reference
16:15 Navigating Quarto’s documentation.
18:00 Is there something like Observable SQL cells on the roadmap?
20:10 Is there something closer to {bookdown} for Quarto? What is the best way to retain data and environment objects in a quarto book? Is there any path to enabling this? See Includes, https://quarto.org/docs/authoring/includes.html
24:20 Flexdashboard? Coming soon.
26:30 A big challenge in the adoption is that Quarto is competing with ipython notebooks for mindspace, what does the Quarto team think about that? Quarto and Jupyter Notebooks will hopefully be thought of as complementary to one another, with Quarto helping a lot with narrative, layout, and appearance for publication and sharing.
30:10 Where should I go to contact you about an issue? What if the issue isn’t just Quarto, say, Quarto + Jupyter?
31:50: What is the Quarto team hoping to see the community produce? Feedback, reporting in github issues. Quarto Extensions.
34:05 Custom styling, configuring grid options. Any tips or anything in the roadmap that will help users finetune the look and feel of their output?
38:40 Terminology question; what do we call a published Quarto doc? (or webpage, blog, etc.?)
40:00 How do I stay up to date with Quarto? Getting the latest release and learning about what is new?
See what’s up on quarto.org. Look under get-started and under downloads for pre-releases
RStudio Pro Product Lightning Series Meetup ⚡️
Recording from our October 11th meetup: a lightning series with our RStudio Product Managers to hear what’s new, ask questions, and provide feedback.
Lightning talks: 3:16 - Sharing Internal Packages with RStudio Package Manager 18:07 - Running RStudio workloads in the Cloud with Amazon SageMaker 40:02 - Content execution in Kubernetes with RStudio Connect
Resources and links shared during the meetup: A Package Manager demo tutorial on GitHub: https://github.com/rstudio/package-manager-demo Remote API Quickstart: https://docs.rstudio.com/rspm/admin/getting-started/configuration/#quickstart-remote-cli Differences between RStudio Workbench and RStudio Workbench on SageMaker: https://docs.aws.amazon.com/sagemaker/latest/dg/rstudio.html#rstudio-differences RStudio Workbench release notes: https://www.rstudio.com/products/rstudio/release-notes/ Remote Content Execution with RStudio Connect and Kubernetes Conference talk: https://www.rstudio.com/conference/2022/talks/remote-content-execution-rstudio-connect/
Product Links: Package Manager, control and distribute packages throughout your organization: https://www.rstudio.com/products/package-manager/ Workbench, premiere development environment for data science professionals: https://www.rstudio.com/products/workbench/ Connect, easily share your insights: https://www.rstudio.com/products/connect/
Timestamps: 22:43 - Demo of RStudio Workbench on Amazon SageMaker
Sharing Internal Packages with RStudio Package Manager | Presented by Joe Roberts
Many know that RSPM can be used to mirror public packages from CRAN or PyPI, but it can also be used to share your private, internally developed packages. We’ll explore the latest features to make internal packages easier to deploy within your organization.
Running RStudio workloads in the Cloud with Amazon SageMaker | Presented by James Blair
RStudio Workbench on SageMaker enables users to “right-size” their environment for any given analysis. We’ll showcase how this flexibility enables users to effectively meet the workload demands of various analyses.
Content execution in Kubernetes with RStudio Connect | Presented by Kelly O’Briant
New and interesting ways to configure RStudio Connect: A quick introduction to off-host content execution in Kubernetes
We’re looking forward to learning from you and hearing your feedback as well!
Meetup recordings are always shared here: https://www.youtube.com/playlist?list=PL9HYL-VRX0oRKK9ByULWulAOO5jN70eXv
Create & Publish a Quarto Blog on Quarto Pub in 100 Seconds | Quarto Pub
Thomas Mock, Quarto Product Manager, walks you through how to build a simple blog with Quarto and share it with the world on quarto.pub, all in less than two minutes.
Quarto is the multi-language publishing system. It also allows you to publish executable code blocks to include R, Python, Julia, or Observable JS output in your blog posts (and many other formats).
Quarto websites and blogs are particularly excellent ways to develop your technical skills and share your learnings with the world.
Resources, ⬡ Creating a Quarto Blog, https://quarto.org/docs/websites/website-blog.html ⬡ Publishing to Quarto Pub, https://quarto.org/docs/publishing/quarto-pub.html ⬡ Customize your Quarto blog or Website. This example creates and deploys a simple Quarto blog template, but there are ways to customize and style your content. Isabella Velásquez walks through this in detail at the Sept 2022 meetup, https://youtu.be/CVcvXfRyfE0 ⬡ Learn more about Quarto at quarto.org.
Requirements,
- To publish from the RStudio IDE, you’ll need to be working on a recent version of RStudio, v2022.07.1 or later.
- You may also work from Jupyter Labs, VS Code, or a notebook integrated with the Quarto CLI
Welcome to Quarto Workshop! | Led by Tom Mock, RStudio
Welcome to Quarto 2-hour Workshop | Led by Tom Mock, RStudio
Content website: https://jthomasmock.github.io/quarto-2hr-webinar/ FULL Workshop Materials (this was from a 2-day workshop): rstd.io/get-started-quarto Other upcoming live events: rstd.io/community-events
Double-check: Are you on the latest version of RStudio i.e. v2022.07.1 or later?
Packages used: tidyverse, gt, gtExtras, reactable, ggiraph, here, quarto, rmarkdown, gtsummary, palmerpenguins, fs, skimr
️ Pre-built RStudio Cloud with workshop materials already installed: https://rstudio.cloud/content/4332583
For follow-up questions, please use: community.rstudio.com/tag/quarto
Timestamps: 7:16 - What is Quarto? 8:28 - How does R Markdown work? 9:40: Quarto, more than just knitr 13:56 - Quarto can support htmlwidgets in R and Jupyter widgets for Python/Julia 14:18 - Native support for Observable Javascript 19:28 - Quarto in your own workspace (Jupyter Lab, VSCode, RStudio) 20:26 - RStudio Visual Editor mode 23:30 - VS Code YAML 26:02 - Quarto for collaboration 26:55 - How do you publish Quarto? (Quarto Pub, GitHub Pages, RStudio Connect, Netlify) 28:44 - What about Data Science at Work? 29:59 - Formats baked into Quarto (basic formats, beamer, ppt, html slides, advanced layout, cross references, websites, blogs, books, interactivity) 32:13 - What to do with my existing .Rmd or .ipynb? 33:16 - Why Quarto, instead of R Markdown? 40:50 - Text Formatting 41:30 - Headings 41:51 - Code (also merging R and Python in one document) 43:29 - What about the CLI? 44:55 - Navigating in the terminal 57:56 - PART 2: Authoring Quarto 1:00:22 - Output options 1:04:46 - Quarto workflow 1:12:06 - Quarto YAML intelligence 1:13:20 - Divs and Spans 1:22:13 - Figure layout 1:34:40 - Code chunk options 1:41:00 - Quarto and R Markdown (converting R Markdown to Quarto)
This 2-hour virtual session is designed for those who have no or little prior experience with R Markdown and who want to learn Quarto.
Want to get started with Quarto?
- Install RStudio v2022.07.1 from https://www.rstudio.com/products/rstudio/download/#download - this will come with a working version of Quarto!
- Webinar materials/slides: https://jthomasmock.github.io/quarto-2hr-webinar/
- Workshop materials on RStudio Cloud: https://rstudio.cloud/content/4332583
What is Quarto?
Quarto is the next generation of R Markdown for publishing, including dynamic and static documents and multi-lingual programming language support. With Quarto you can create documents, books, presentations, blogs or other online resources.
Should I take this?
As with all the community meetups, everyone is welcome. This will be especially interesting to you if you have experience programming in R and want to learn how to take advantage of Quarto for literate data science programming in academia, science, and industry.
This workshop will be appropriate for attendees who answer yes to these questions:
Have you programmed in R and want to better encapsulate your code, documentation, and outputs in a cohesive “data product”? Do you want to learn about the next generation of R Markdown for data science? Do you want to have a better interactive experience when writing technical or scientific documents with literate programming?
For more info on Quarto: quarto.org
