rspatialdata
r-lib/producethis: What the Package Does (One Line, Title Case)
Note the use of the /exec folder for different deployable workflows
Documenting functions
The basics of roxygen2 tags and how to use them for documenting functions.
Examples
@examples provides executable R code showing how to use the function in practice. This is a very important part of the documentation because many people look at the examples before reading anything. Example code must work without errors as it is run automatically as part of R CMD check.
For the purpose of illustration, it’s often useful to include code that causes an error. You can do this by wrapping the code in try() or using \dontrun{} to exclude from the executed example code.
For finer control, you can use @examplesIf:
#' @examplesIf interactive()
#' browseURL("https://roxygen2.r-lib.org")
Instead of including examples directly in the documentation, you can put them in separate files and use @example path/relative/to/package/root to insert them into the documentation.
All functions must have examples for initial CRAN submission.
UNCHARTED DATA: Interactive Tooltip Tables
How to include tables in your {ggiraph} tooltips.
Welcome and Getting Started – Next Generation Shiny Apps with {bslib}
Welcome to the workshop and hello, bslib!
Opinionated Backend and Reusability Focused Considerations for Shiny
Purposefully simple helper functions, tools, and a framework for creating reusable applications fit for production in clinical systems.
tidyverse/dtplyr: Data table backend for dplyr
Data table backend for dplyr. Contribute to tidyverse/dtplyr development by creating an account on GitHub.
Building a team of internal R packages | Emily Riederer
On the jobs-to-be-done and design principles for internal tools
Explore Your Data Interactively • ExPanDaR
Provides a shiny-based front end (the 'ExPanD' app) and a set of functions for exploratory data analysis. Run as a web-based app, 'ExPanD' enables users to assess the robustness of empirical evidence without providing them access to the underlying data. You can export a notebook containing the analysis of 'ExPanD' and/or use the functions of the package to support your exploratory data analysis workflow. Refer to the vignettes of the package for more information on how to use 'ExPanD' and/or the functions of this package.
jsugarelli/shinyfilter
Contribute to jsugarelli/shinyfilter development by creating an account on GitHub.
ropenscilabs/allcontributors: all-contributions as an R package
all-contributions as an R package. Contribute to ropenscilabs/allcontributors development by creating an account on GitHub.
CRAN - Package shinydlplot
Add a download button to a 'shiny' plot or 'plotly' that appears when the plot is hovered. A tooltip, styled to resemble 'plotly' buttons, is displayed on hover of the download button. The download button can be used to allow users to download the dataset used for a plot.
renkun-ken/rlist: A Toolbox for Non-Tabular Data Manipulation
A Toolbox for Non-Tabular Data Manipulation. Contribute to renkun-ken/rlist development by creating an account on GitHub.
HenrikBengtsson/doFuture: R package: doFuture - A Universal Foreach Parallel Adaptor using the Future API of the 'future' Package
:rocket: R package: doFuture - A Universal Foreach Parallel Adaptor using the Future API of the 'future' Package - HenrikBengtsson/doFuture
HenrikBengtsson/parallelly: R package: parallelly - Enhancing the 'parallel' Package
R package: parallelly - Enhancing the 'parallel' Package - HenrikBengtsson/parallelly
HenrikBengtsson/future: R package: future: Unified Parallel and Distributed Processing in R for Everyone
:rocket: R package: future: Unified Parallel and Distributed Processing in R for Everyone - HenrikBengtsson/future
yonicd/d3Tree: htmlwidget that binds d3js collapsible trees to R and Shiny to make an interactive search tool
htmlwidget that binds d3js collapsible trees to R and Shiny to make an interactive search tool - yonicd/d3Tree
Rdatatable/data.table: R's data.table package extends data.frame:
R's data.table package extends data.frame:. Contribute to Rdatatable/data.table development by creating an account on GitHub.
dbosak01/libr: An R package to create data libraries and data dictionaries.
An R package to create data libraries and data dictionaries. - dbosak01/libr
Install and Run Programs, Outside of R, Inside of R • rOpenSci: outsider
Install and run external command-line programs in R through use of Docker and online repositories.
njtierney/brolgar: BRowse Over Longitudinal Data Graphically and Analytically in R
BRowse Over Longitudinal Data Graphically and Analytically in R - njtierney/brolgar
jaytimm/quicknews: Some R-based tools for navigating the online news landscape
Some R-based tools for navigating the online news landscape - jaytimm/quicknews
rstudio/shinytest: Automated testing for shiny apps
Automated testing for shiny apps. Contribute to rstudio/shinytest development by creating an account on GitHub.
R Scripts in the Google Cloud via Cloud Run, Cloud Build and Cloud Scheduler • googleCloudRunner
Tools to easily enable R scripts in the Google Cloud Platform. Utilise cloud services such as Cloud Run for R over HTTP, Cloud Build for Continuous Delivery and Integration services and Cloud Scheduler for scheduled scripts.
r-dbi/DBI: A database interface (DBI) definition for communication between R and RDBMSs
A database interface (DBI) definition for communication between R and RDBMSs - r-dbi/DBI
dreamRs/shinyWidgets: shinyWidgets : Extend widgets available in shiny
cboettig/knitcitations: Generate citations for knitr markdown and html files
:package: Generate citations for knitr markdown and html files - cboettig/knitcitations
etiennebacher/prompter: Add Tooltips in 'Shiny' Apps With 'Hint.css'
Add Tooltips in 'Shiny' Apps With 'Hint.css'. Contribute to etiennebacher/prompter development by creating an account on GitHub.
You're Already Ready: Zen and the Art of R Package Development | Malcolm Barrett
R packages make it easier to write robust, reproducible code, and modern tools in R development like usethis make it easy to work with packages. When you write R packages, you also unlock a whole ecosystem of tools that will make it easier to test, document, and share your code. Despite these benefits, many believe package development is too advanced for them or that they have nothing to offer. A fundamental belief in Zen is that you are already complete, that you already have everything you need. I’ll talk about why your project is already an R package, why you’re already an R package deve...
{attachment} v0.2.0 : find dependencies in your scripts and fill package DESCRIPTION - Rtask
We continue to improve {attachment} functionalities to help you deal with dependencies in R, in particular during package development.