# library(glue)
# library(purrr)
# library(rlang)

pad_transformer <- function(code, envir) {
  if (grepl("[*]$", code)) {
    code <- stringr::str_replace(code, "[*]$", "")
    res <- glue::evaluate(code, envir)
    stringr::str_pad(res, 3, "left", "0")
  } else {
    glue::evaluate(code, envir)
  }
}

acs_vars <- function(..., .envir = parent.frame()) {
  glue::glue(..., .envir = .envir, .transformer = pad_transformer)
}

acs_sum <- function(..., na.rm = TRUE, .envir = parent.frame()) {
  list(...) %>%
    purrr::map(acs_vars) %>%
    purrr::flatten_chr() %>%
    purrr::map(~rlang::eval_tidy(rlang::sym(.x), env = .envir)) %>%
    as.data.frame() %>%
    rowSums(na.rm = na.rm)
}


library(dplyr)

df <- tibble(
  endyear = 2009:2011,
  b01001_e001 = c(1, 2, 3),
  b01001_e003 = c(NA, 1, NA),
  b01001_e002 = c(NA, 1, NA))

df %>%
  mutate(
    foo = acs_sum("b01001_e{1:3*}"),
    bar = acs_sum("b01001_e001", "b01001_e002", "b01001_e003"),
    baz = acs_sum("b01001_e{1:2*}", "b01001_e003")
  )

#> # A tibble: 3 x 7
#>   endyear b01001_e001 b01001_e003 b01001_e002   foo   bar   baz
#>     <int>       <dbl>       <dbl>       <dbl> <dbl> <dbl> <dbl>
#> 1    2009           1          NA          NA     1     1     1
#> 2    2010           2           1           1     4     4     4
#> 3    2011           3          NA          NA     3     3     3

df %>%
  mutate(
    foo = case_when(
      endyear == 2009L ~ acs_sum("b01001_e{1:3*}"),
      endyear == 2010L ~ acs_sum("b01001_e001", "b01001_e002", "b01001_e003"),
      endyear == 2011L ~ acs_sum("b01001_e{1:2*}", "b01001_e003")
    )
  )

#> # A tibble: 3 x 5
#>   endyear b01001_e001 b01001_e003 b01001_e002   foo
#>     <int>       <dbl>       <dbl>       <dbl> <dbl>
#> 1    2009           1          NA          NA     1
#> 2    2010           2           1           1     4
#> 3    2011           3          NA          NA     3