Function for bootstrap - get sd of statistics of simulations - function

Question

I am trying to write a function for bootstrap (an assignment). The question is as follow:
Compute the bootstrap standard error for:
- mean() and
- median() and
- the top quartile and
- the standard deviation of the price (yes, I want the standard deviation of the standard deviation... If this confuses you, go through the mean example and replace the computation of the mean by the_thing_we_want and realize that the_thing_we_want can be the standard deviation)
- max()
One way to approach this is to define a new function for each. Another is to write a bootstrap_func function that takes an additional argument called fun, and then you call it bootstrap_func(B, v, median) to have the same effect as bootstrap_median. Implement this function bootstrap_func.
Example call to this function: bootstrap_func(1000, vienna_data$price, mean).
This is what I attempt to do:
hotels_price <- read.csv("data_repo/hotels-europe/clean/hotels-europe_price.csv")
hotels_features_vienna <- read.csv("data_repo/hotels-europe/clean/hotels-europe_features.csv") %>%
filter(city == "Vienna")
hotels_vienna <- left_join(hotels_price, hotels_features_vienna) %>%
filter(across(.cols = everything(), function(x){!is.na(x)}))
set.seed(7777)
B <- 100 # B is asked to be set to 100 - the number of simulations
v <- hotels_vienna$price
get_sim <- function(v) {
sample(v, replace = TRUE)
}
fun <- function(get_sim) {
mean <- function(get_sim) {mean(get_sim)}
median <- function(get_sim) {mean(get_sim)}
top_quartile <- function(get_sim) {quantile(get_sim, 0.75)}
sd <- function(get_sim) {sd(get_sim)}
max <- function(get_sim) {max(get_sim)}
}
sim_stats <- function(B) {
replicate(B, fun(get_sim()))
}
bootstrap_func <- function(B, v, fun) {
sd(sim_stats())
}
bootstrap_func(100, hotels_vienna$price, sd)
When I try to run the last line R throw an error "Error: C stack usage 15926432 is too close to the limit". I do not know how to fix this, and more importantly, if my code will get to the desired results. I appreciate any inputs. TIA.