r data.table functional programming / metaprogramming / computing on the language

Question

I am exploring different ways to wrap an aggregation function (but really it could be any type of function) using data.table (one dplyr example is also provided) and was wonderi

Answer 1

I don't recommend eval(parse()). You can achieve the same as in approach three without it:

fn_dt_agg4 <- 
  function(dt, metric, metric_name, dimension, dimension_name, agg_type) {

    e <- function(x) getFunction(agg_type)(x, na.rm = T)

    temp <- dt[, setNames(lapply(.SD, e), 
                          metric_name), 
               keyby = dimension, .SDcols = metric]
    temp[]
  }

This also avoids some security risks.

PS: You can check what data.table is doing regarding optimizations by setting options("datatable.verbose" = TRUE).