Organize and Curate Your Content Within 'Posit Connect'.

connectwidgets

Curate your content on Posit Connect

connectwidgets is an R package that can be used to query a Posit Connect server for a subset of your existing content items, then organize them within htmlwidget components in an R Markdown document or Shiny application.

Use connectwidgets to create a content hub or knowledge repository, a customized summary page for a particular group of stakeholders, or a presentation layer for any group of related content.

Installation

You can install connectwidgets from CRAN using:

install.packages("connectwidgets")

Alternatively, you can install the development version from GitHub:

# install.packages("remotes")
remotes::install_github("rstudio/connectwidgets")

Example

Use the template:

rmarkdown::draft("example-page.Rmd", template = "connectwidgets", package = "connectwidgets")

You can also copy and knit the following example, or read on for more details:

---
title: an example page
output: html_document
---

```{r setup, include=FALSE}
library(connectwidgets)
library(dplyr)

knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE)

client <- connect(
  # server  = Sys.getenv("CONNECT_SERVER"),
  # api_key = Sys.getenv("CONNECT_API_KEY")
  )

all_content <- client %>%
  content()

sample_content <- all_content %>%
  arrange(desc(updated_time)) %>%
  slice_head(n = 50)
```

![](https://source.unsplash.com/1920x1080/?forest "A random forest.")

## Components

### card

```{r card}
sample_content %>%
  slice(1) %>%
  rsc_card()
```

### grid

```{r grid}
sample_content %>%
  rsc_grid()
```

### table

```{r table}
sample_content %>%
  rsc_table()
```

### search & filter

```{r search-and-filter}
rsc_cols(rsc_search(all_content), rsc_filter(all_content), widths = c(2, 2))
rsc_table(all_content)
```

Setup

The client object:

• Validates your API key with the Posit Connect server
• Ensures you are running a recent enough version of Connect

Use an .Renviron file to set the CONNECT_SERVER and CONNECT_API_KEY environment variables. If you’re not familiar with setting environment variables, check out the R Startup chapter of What They Forgot to Teach You About R. Posit Connect will automatically apply values for these at document run time, so there is no need to include them in your code:

library(connectwidgets)
library(dplyr, warn.conflicts = FALSE)

knitr::opts_chunk$set(echo = FALSE, message = FALSE, warning = FALSE)

client <- connect(
  # server  = Sys.getenv("CONNECT_SERVER"),
  # api_key = Sys.getenv("CONNECT_API_KEY")
  )

all_content <- client %>%
  content()

glimpse(all_content)
#> Rows: 12
#> Columns: 15
#> $ id               <int> 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1
#> $ guid             <chr> "0b7e0b47-a8c7-4492-87ea-7082eb942839", "d0664722-a93…
#> $ name             <chr> "puser3-acl-static-plot-with-title-and-description", …
#> $ title            <chr> "Static Plot (Title and Description)", "Static Plot (…
#> $ description      <chr> "This static plot was deployed with a title and a des…
#> $ app_mode         <chr> "static", "static", "static", "static", "static", "st…
#> $ content_category <chr> "plot", "plot", "plot", "plot", "plot", "plot", "plot…
#> $ url              <chr> "http://localhost:3939/content/0b7e0b47-a8c7-4492-87e…
#> $ owner_guid       <chr> "504a8529-9a89-4062-8758-a419a490a9a3", "4dfa986f-3e4…
#> $ owner_username   <chr> "puser3", "puser2", "puser1", "puser3", "puser2", "pu…
#> $ owner_first_name <chr> "", "", "", "", "", "", "", "", "", "", "", ""
#> $ owner_last_name  <chr> "", "", "", "", "", "", "", "", "", "", "", ""
#> $ created_time     <dttm> 2023-01-10 22:37:59, 2023-01-10 22:37:59, 2023-01-10 …
#> $ updated_time     <dttm> 2023-01-10 22:37:59, 2023-01-10 22:37:59, 2023-01-10 …
#> $ tags             <list> <NULL>, <NULL>, <NULL>, <NULL>, <NULL>, <NULL>, <NULL…

sample_content <- all_content %>%
  arrange(desc(updated_time)) %>%
  slice_head(n = 100)

content()

content() returns a data frame with the following columns:

• id - Auto-incrementing identifier for each content item (legacy)
• guid - Unique identifier for each content item (preferred)
• app_mode - The type of the content item (examples: shiny, rmd-static, static, python-dash, etc.)
• content_category - For static app modes, the specific category of content (examples: site, plot, pin, etc.)
• name - The name of the content item as set at initial publishing
• title - The user-provided title of the content item
• description - The user-provided description of the content item
• url - The URL to the content item
• owner_guid - Unique identifier of the owner of the content item
• owner_username - Username of the owner of the content item
• owner_first_name - First name of the owner of the content item
• owner_last_name - Last name of the owner of the content item
• tags - A data frame of the tags associated with the content item, with the following columns: id, name, parent_id, created_time, updated_time.
• created_time - The timestamp at which the content item was created
• updated_time - The timestamp at which the content item was last updated

The data frame contains one row for each item visible to the requesting user. For users in an “administrator” role, that will be all content items.

Filtering Content

We provide helper functions to filter by both owners and tags.

• by_tags() - Filters the data frame to only include content that has been tagged with the specified tag name(s). You can pass a single tag name or a vector of tag names. by_tag is provided as an alias for readability when using a single tag.

• by_owners() - Filters the data frame to only include content with the specified owner(s) by username. You can pass a single username or a vector of usernames. by_owner is provided as an alias for readability when using a single username.

all_content %>% 
  by_tag("Audit Reports")
#> # A tibble: 0 × 15
#> # … with 15 variables: id <int>, guid <chr>, name <chr>, title <chr>,
#> #   description <chr>, app_mode <chr>, content_category <chr>, url <chr>,
#> #   owner_guid <chr>, owner_username <chr>, owner_first_name <chr>,
#> #   owner_last_name <chr>, created_time <dttm>, updated_time <dttm>,
#> #   tags <list>

Since all_content is a tibble(), you can also manipulate it with dplyr:

all_content %>% 
  filter(updated_time >= "2021-01-01") %>% 
  arrange(created_time)
#> # A tibble: 12 × 15
#>       id guid  name  title descr…¹ app_m…² conte…³ url   owner…⁴ owner…⁵ owner…⁶
#>    <int> <chr> <chr> <chr> <chr>   <chr>   <chr>   <chr> <chr>   <chr>   <chr>  
#>  1     6 18b2… puse… Stat… ""      static  plot    http… 504a85… puser3  ""     
#>  2     5 2460… puse… Stat… ""      static  plot    http… 4dfa98… puser2  ""     
#>  3     4 3de7… puse… Stat… ""      static  plot    http… f6fd68… puser1  ""     
#>  4     3 7299… puse… <NA>  ""      static  plot    http… 504a85… puser3  ""     
#>  5     2 edab… puse… <NA>  ""      static  plot    http… 4dfa98… puser2  ""     
#>  6     1 7ccf… puse… <NA>  ""      static  plot    http… f6fd68… puser1  ""     
#>  7    12 0b7e… puse… Stat… "This … static  plot    http… 504a85… puser3  ""     
#>  8    11 d066… puse… Stat… "This … static  plot    http… 4dfa98… puser2  ""     
#>  9    10 c335… puse… Stat… "This … static  plot    http… f6fd68… puser1  ""     
#> 10     9 66f2… puse… <NA>  "This … static  plot    http… 504a85… puser3  ""     
#> 11     8 e7dd… puse… <NA>  "This … static  plot    http… 4dfa98… puser2  ""     
#> 12     7 5d4e… puse… <NA>  "This … static  plot    http… f6fd68… puser1  ""     
#> # … with 4 more variables: owner_last_name <chr>, created_time <dttm>,
#> #   updated_time <dttm>, tags <list>, and abbreviated variable names
#> #   ¹​description, ²​app_mode, ³​content_category, ⁴​owner_guid, ⁵​owner_username,
#> #   ⁶​owner_first_name

Components

Once your content data are filtered, connectwidgets provides components for displaying information about them. The title, description, and preview image can be set from the Posit Connect dashboard. For content deployed to Connect where no image has been supplied, a default image will be used.

Note: In many cases, you will only see default images until your content is deployed.

card

Use a card to highlight an individual piece of content:

grid

Display multiple content items via a grid:

table

Provide a more detailed view with a table:

search & filter

The search and filter components help viewers find the content they are most interested in. You must pass the same content data frame to rsc_search(), rsc_filter(), and rsc_table() or rsc_grid() in order for filter and search to work. You can also create your own crosstalk::SharedData() object to pass to the components if you want more control over searching and filtering. Read more at vignette("using-crosstalk").

Theming

connectwidgets components support styling in rmarkdown::html_document via the bslib package. You can supply a Bootswatch theme in the yaml header, e.g.:

---
output:
  html_document:
    theme:
      bootswatch: minty
---

or pass a custom theme consistent with your organization’s style:

---
output:
  html_document:
    theme:
      bg: "#FFF"
      fg: "#22333B" 
      primary: "#4F772D"
      dark: "#252525"
      light: "#DCE6D3"
      base_font: "Lato, sans-serif"
      heading_font: "Lato, sans-serif"
      border-color: "#E9F5DB"
      gray-100: "#F7FCF0"
---

Once you’re happy with the look of your page, Publish it to Posit Connect. Read more at vignette("publishing").

A more customized example:

Putting it all together, the example API portal page below:

• uses CSS to create a full-width image with inset text
• uses a Bootswatch theme
• overrides the description text for a couple of cards

If no APIs are deployed on your Posit Connect server, try filtering for static documents or Shiny apps instead.

---
output:
  html_document:
    theme:
      bootswatch: lumen
---

```{css, echo=FALSE}
.main-container {
    width: 100%;
    max-width: unset;
}

.main {
    max-width: 940px;
    margin-left: auto;
    margin-right: auto;
}

/* https://codepen.io/eversionsystems/pen/YOmqdj */
.jumbotron {
  color: white;
  background-image: url("https://source.unsplash.com/d30sszrW7Vw/1920x1080");
  background-position: center;
  background-repeat: no-repeat;
  background-size: cover;
  height: 50vh;
}
```

```{r, include=FALSE}
library(connectwidgets)
library(dplyr)
library(htmltools)

knitr::opts_chunk$set(
  comment = "",
  echo = FALSE, warning = FALSE, message = FALSE
)

rsc_content <-
  connect() %>%
  content()

apis <- rsc_content %>%
  filter(app_mode %in% c("api", "python-api"))
```

```{r}
div(
  class = "jumbotron jumbotron-fluid",
  div(
    class = "container",
    h1("Connect API Portal", class = "display-4"),
    p("Model APIs maintained by the data science team")
  )
)
```

```{r}
div(
  class = "main",
  h3("Featured APIs", class = "text-center"),
  {
    model_copy <- c(
      "Our most important model: Distillery retro taiyaki fashion axe.
      Art party cray intelligentsia flexitarian.",
      "Our second most important model: Pug af twee portland pitchfork brunch
      kogi gochujang organic migas shaman four dollar toast 90's slow-carb."
      )

    apis %>%
      slice_head(n = 2) %>%
      mutate(
      description = model_copy
      ) %>%
      rsc_card()
  },
  h3("All APIs", class = "text-center"),
  p("that thing George Box said one time. You know what thing."),
  {
    tagList(
      rsc_cols(rsc_search(apis), rsc_filter(apis)),
      rsc_grid(apis)
    )
  }
)
```