ci: install package

Author: ColinFay

content/post/2020-05-10_shinipsum-cran-realease/index.Rmarkdown

@@ -22,14 +22,16 @@ projects: []
 ---
 
 ```{r include=FALSE}
-install.packages("shinipsum")
+if (!requireNamespace("shinipsum")){
+  install.packages("shinipsum", repos = "https://cran.rstudio.com")
+}
 ```
 
 
 I'm very happy to announce that `{shinipsum}` is now on CRAN!
 
-`{shinipsum}` is a package that can help you build `{shiny}` prototypes faster by providing a series of functions that can generate random elements to populate your UI. 
-If you are familiar with "lorem ipsum", the fake text generator that is used in software design as a placeholder for text, the idea is the same: generating placeholders for Shiny outputs. 
+`{shinipsum}` is a package that can help you build `{shiny}` prototypes faster by providing a series of functions that can generate random elements to populate your UI.
+If you are familiar with "lorem ipsum", the fake text generator that is used in software design as a placeholder for text, the idea is the same: generating placeholders for Shiny outputs.
 
 `{shinipsum}` can be installed from CRAN with:
 
@@ -43,7 +45,7 @@ You can install this package from GitHub with:
 remotes::install_github("Thinkr-open/shinipsum")
 ```
 
-In this package, a series of functions that generates random placeholders. 
+In this package, a series of functions that generates random placeholders.
 For example, `random_ggplot()` generates random `{ggplot2}` elements:
 
 ```{r}
@@ -53,17 +55,17 @@ library(ggplot2)
 
 
 ```{r}
-random_ggplot() + 
-  labs(title = "Random plot") 
+random_ggplot() +
+  labs(title = "Random plot")
 ```
 
 ```{r}
-random_ggplot() + 
-  labs(title = "Random plot") 
+random_ggplot() +
+  labs(title = "Random plot")
 ```
 
 Of course, the idea is to combine this with a Shiny interface, for example `random_ggplot()` will be used with a `renderPlot()` and `plotOutput()`.
-And as we want to prototype but still be close to what your final application will look like, these functions take arguments that can shape the output: for example, `random_ggplot()` has a `type` parameter that can help you select a specific geom. 
+And as we want to prototype but still be close to what your final application will look like, these functions take arguments that can shape the output: for example, `random_ggplot()` has a `type` parameter that can help you select a specific geom.
 
 ```{r eval = FALSE}
 library(shiny)
@@ -93,9 +95,9 @@ shinyApp(ui, server)
 ```
 
 
-Other `{shinipsum}` functions include: 
+Other `{shinipsum}` functions include:
 
-+ tables: 
++ tables:
 
 ```{r 10-prototyping-9 }
 random_table(nrow = 3, ncol = 10)
@@ -109,7 +111,7 @@ random_print(type = "model")
 
 ... and text, image, ggplotly, dygraph, and DT.
 
-Learn more about `{shinipsum}`: 
+Learn more about `{shinipsum}`:
 
 + [`{shinipsum}` website](https://thinkr-open.github.io/shinipsum/)
 + [Chapter 10 Building an “ipsum-app” - Engineering Production-Grade Shiny Apps](https://engineering-shiny.org/stepprotopype.html)