With this question I'm only interested in obtaining some clarity on a best approach to using packages while working with a Shiny app. Despite the fact that, contrary to good practice on asking R-related questions, the question does not contain code or reproducible example, I hope that it touches on practical and relevant matters.

Problem

I'm working on a modular Shiny app that has the following structure:

• server.R - contains some key functions and first few initial graphics
• ui.R - provides basic user interface framework
• data - folder with some data files that are not sourced dynamically
  • list.csv - sample file with data
  • ... - other data files
• functionsAndModules - folder with *.R files pertaining to functions and modules
  • functionCleanGeo.R - simple function cleaning some data frames of format: cleanDataFrame <- function(data) { ... return(cleanDta) }
  • moduleTimeSeries.R - module providing time series analysis doing the following things:
    • generating user interface
    • sourcing data
    • generating charts
  • ...R - other modules and functions saved as *.R files.

Libraries

What I would like to know is how to approach loading packages that would be most optimal for the app structure outlined above. In particular, I would like to know:

1. When it's sufficient to load libraries only in global.R and when (if at all) it may be required to load libraries across module files and/or server.R / ui.r?

   1.2. For example when using shinyTree package I load it in server.R and ui.R as, it is my understanding that this flows from examples. Modules and functions use dplyr / tidyr combination, would it be sufficient to load those packages in global.R?

2. My preferred method for loading packages looks like that: Vectorize(require)(package = c("ggvis", "SPARQL", "jsonlite", "dplyr", "tidyr", "magrittr"), character.only = TRUE), will it work fine with the architecture described above?