Dynamically create and evaluate function in R - r

Question

I am trying to dynamically create and evaluate a function from a string input and am hung up, again, on meta-programming/evaluation (https://adv-r.hadley.nz/metaprogramming.html). I have a feeling this is answered on SO, but I searched and wasn't able to figure out the solution looking through other posts; however, if there is an existing answer, please let me know and flag as duplicate. Thank you so much for your time and help! Below is a reprex of the issue.
library(dplyr)
library(purrr)
library(rlang)
library(palmerpenguins)
# Create data to join with penguins
penguin_colors <-
tibble(
species = c("Adelie", "Chinstrap", "Gentoo"),
color = c("orange", "purple", "green")
)
# Create function to do specified join and print join type
foo <- function(JOINTYPE) {
# DOESN'T RUN
# JOINTYPE_join(penguins, penguin_colors, by = "species")
# call2(sym(paste0(JOINTYPE, "_join")), x = penguins, y = penguin_colors, by = "species")
print(JOINTYPE)
}
# Desired behavior of foo when JOINTYPE == "inner"
inner_join(penguins, penguin_colors, by = "species")
#> # A tibble: 344 x 9
#> species island bill_length_mm bill_depth_mm flipper_length_… body_mass_g
#> <chr> <fct> <dbl> <dbl> <int> <int>
#> 1 Adelie Torge… 39.1 18.7 181 3750
#> 2 Adelie Torge… 39.5 17.4 186 3800
#> 3 Adelie Torge… 40.3 18 195 3250
#> 4 Adelie Torge… NA NA NA NA
#> 5 Adelie Torge… 36.7 19.3 193 3450
#> 6 Adelie Torge… 39.3 20.6 190 3650
#> 7 Adelie Torge… 38.9 17.8 181 3625
#> 8 Adelie Torge… 39.2 19.6 195 4675
#> 9 Adelie Torge… 34.1 18.1 193 3475
#> 10 Adelie Torge… 42 20.2 190 4250
#> # … with 334 more rows, and 3 more variables: sex <fct>, year <int>,
#> # color <chr>
print("inner")
#> [1] "inner"
# Use function in for loop
for (JOINTYPE in c("inner", "left", "right")) {
foo(JOINTYPE)
}
#> [1] "inner"
#> [1] "left"
#> [1] "right"
# Use function in vectorised fashion
walk(c("inner", "left", "right"), foo)
#> [1] "inner"
#> [1] "left"
#> [1] "right"
Created on 2020-10-27 by the reprex package (v0.3.0)

Answer 1

One option is to use get() to retrieve the appropriate function:
join <- function(JOINTYPE) {
get( paste0(JOINTYPE, "_join") )
}
join("inner")(penguins, penguin_colors, by="species")
If using rlang, the more appropriate function here is rlang::exec:
join2 <- function(JOINTYPE, ...) {
rlang::exec( paste0(JOINTYPE, "_join"), ... )
}
join2("inner", penguins, penguin_colors, by="species")