Fix build-deploy errors on push to main

.github/workflows/quarto-publish.yml

@@ -12,6 +12,8 @@ permissions:
 jobs:
   build-deploy:
     runs-on: ubuntu-latest
+    env:
+      R_LIBS_USER: ${{ github.workspace }}/R/library
     steps:
       - name: Check out repository
         uses: actions/checkout@v4
@@ -30,9 +32,12 @@ jobs:
           restore-keys: |
             ${{ runner.os }}-R-
 
+      - name: Install system dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y libcurl4-openssl-dev libuv1-dev
+
       - name: Install R Packages
-        env:
-          R_LIBS_USER: ${{ github.workspace }}/R/library
         run: |
           mkdir -p $R_LIBS_USER
           Rscript -e 'install.packages(c("knitr", "rmarkdown", "ggplot", "palmerpenguins", "plotly"), repos = "https://cloud.r-project.org/", lib = Sys.getenv("R_LIBS_USER"))'

tutorials/info_schema_tutorial.qmd

@@ -25,7 +25,7 @@ The Quarto document begins with a header that includes essential metadata (title
 
 Next, the following R code chunk loads the necessary libraries and suppresses the output for a clean setup:
 
-```{r, warning=FALSE, message=FALSE}
+```r
 library(bigrquery)
 library(dplyr)
 library(DBI)
@@ -40,7 +40,7 @@ bigrquery::bq_auth()
 
 Here, we specify the dataset and project, authenticate with BigQuery, and open a connection. Finally, we list the tables in the dataset to confirm that the connection is working:
 
-```{r}
+```r
 # Specify dataset and project details
 dataset <- "FlatConnect"
 project <- "nih-nci-dceg-connect-dev"
@@ -59,7 +59,7 @@ DBI::dbListTables(con)
 
 The next code block runs a SQL query on the `INFORMATION_SCHEMA.COLUMNS` to locate columns that contain specific Concept IDs. This query filters columns based on a pattern present in their names:
 
-```{sql, connection=con}
+```sql
 SELECT 
   table_catalog, 
   table_schema, 
@@ -74,7 +74,7 @@ WHERE column_name
 
 To make the querying process more flexible, we define an R function named `get_schema_info`. This function accepts a vector of Concept IDs and a tier (development, staging, or production), constructs the appropriate SQL query dynamically, and returns the result:
 
-```{r}
+```r
 get_schema_info <- function(con, cids, tier, dataset = 'FlatConnect') {
 
   # Determine the project based on the tier