Example code for using a dataframe to access USEPA WATERS API. Shows two iteration examples: purrr and for loop.

iterate_waters.R

library(purrr)
library(jsonlite)
library(dplyr)
library(usethis)

# The Data.gov API requires a key and has a 1000 request/hour limit
# Get Key from https://api.data.gov/signup/
# Save key in r environ
usethis::edit_r_environ()
# Add DATAGOV_KEY=YOURKEYGOESHERE to the file.  Save and restart R
dg_key <- Sys.getenv("DATAGOV_KEY")


# Example dataframe with coords as x, y columns
xdf <- data.frame(id = c("A","B"), x = c(-87.941093, -87.93053627014162), y = c(42.544354, 42.529982254508425), numeric_id = 1:2)

# Function that accepts a one row data frame, builds WATERS API URL, gets result
# and returns COMID.  It assumes 4 columns named id, x, y, and numeric_id.                  
my_fun <- function(df, key){
  #API limits to 1000 requests/hour
  Sys.sleep(4)
  base_url <- "https://api.epa.gov/waters/v1/pointindexing?pGeometry=SRID%3D4269%3BPOINT%28"
  end_url <- "%29&pPointIndexingMethod=RAINDROP&pOutputPathFlag=TRUE&pReturnFlowlineGeomFlag=TRUE&f=json&api_key="
  url <- paste0(base_url, df$x, "%20", df$y, end_url, key)
  response <- jsonlite::read_json(url, flatten = TRUE)
  # Simple way to see progress, better solutions but this is easy
  cat("\r", paste(df$numeric_id))
  flush.console()
  response$output$ary_flowlines[[1]][[4]]
  }

# purrr solution
comids_purrr <- purrr::map2_chr(split(xdf, xdf$id), dg_key, my_fun)
xdf_purrr <- mutate(xdf, comids = comids_purrr)

# for loop solution
# preallocate object/memory
comids_loop <- vector("character", nrow(xdf))
for(i in seq_along(comids_loop)){
  comids_loop[i] <- my_fun(xdf[i,], key = dg_key)
}
xdf_loop <- mutate(xdf, comids = comids_loop)