Exploring program flow with magrittr

1st method

library(data.table)

orig_subset<-function(workingdata){
  workingdata[["inputs"]][Species!='virginica']
}

orig_mult<-function(workingdata){
  workingdata[["subset"]][,.SD*1.1,by=Species]
}

originalflow<-function(input){
  workingdata<-list()
  workingdata[["inputs"]]<-data.table(input)
  workingdata[["subset"]]<-orig_subset(workingdata)
  workingdata[["multiply"]]<-orig_mult(workingdata)
  return(workingdata)
}

# Either get everything for debug
oldresult<-originalflow(iris)

# or just get relevant bit
oldresult<-originalflow(iris)[["multiply"]]

A skeleton flow

library(magrittr)
library(data.table)

get_subset<- . %>% data.table
multiply_values<- . %>% data.table

skeletonflow<-function(input){
  input %>% 
    data.table %>%
    get_subset  %>%
    multiply_values
}

skeletonresult<-skeletonflow(iris)

magrittr branching example

## You need to use a named input if you want to do conditions based on function values
library(magrittr)
library(data.table)

mytestfunction<-function(x,y = TRUE) {
  x %>% 
    data.table %>%
{ 
  if(y) {
    .[1:50]
  } else {
    .[1:75]
  } 
} %>%
  nrow
}

mytestfunction(iris,0)

New method

library(magrittr)
library(data.table)

get_subset<- . %>% .[Species!='virginica']
multiply_values<- . %>% .[,.SD*1.1,by=Species]

newflow<-function(input){
  input %>% 
    data.table %>%
    get_subset  %>%
    multiply_values
}

newresult<-newflow(iris)