Scrape K5EM's skimmer and plot the number of spots in each band so I can see which bands are open near me

gistfile1.txt

# Load necessary libraries
library(selenider)
library(dplyr)
library(ggplot2)
library(purrr)
library(tidyr)

# --- 1. Setup the Selenider Session ---
# The timeout here is important: find_elements() will wait up to 20 seconds.
selenider_session <- selenider_session(
  "chromote",
  timeout = 20,
  options = chromote_options(headless = FALSE)
)

# --- 2. Define HF Bands in kHz ---
hf_bands <- tibble(
  band = factor(
    c("160m", "80m", "60m", "40m", "30m", "20m", "17m", "15m", "12m", "10m"),
    levels = c("160m", "80m", "60m", "40m", "30m", "20m", "17m", "15m", "12m", "10m")
  ),
  low = c(1800, 3500, 5330, 7000, 10100, 14000, 18068, 21000, 24890, 28000),
  high = c(2000, 4000, 5406, 7300, 10150, 14350, 18168, 21450, 24990, 29700)
)

# --- 3. Define the Target URL ---
url <- "https://www.reversebeacon.net/main.php?zoom=47.76,-117.73,5.90&rows=100&spotters=1&max_age=10,minutes&spotter_call=k5em&hide=distance_km"

# --- 4. Define Functions ---

#' Scrape Frequencies from RBN
get_frequencies <- function() {
  open_url(url)
  
  # This is the correct, idiomatic way to find elements in selenider.
  # It will implicitly wait for the elements to appear.
  elements <- selenider_session %>%
    find_elements(".freq_show_hide.qrg")
  
  if (length(elements) == 0) {
    return(numeric(0))
  }
  
  freqs <- elements %>%
    map_chr(elem_text) %>%
    as.numeric()
  
  return(freqs[!is.na(freqs)])
}

#' Bin Frequencies into HF Bands
bin_to_bands <- function(freqs) {
  if (length(freqs) == 0) {
    return(hf_bands %>% select(band) %>% mutate(n = 0))
  }
  
  tibble(freq = freqs) %>%
    left_join(hf_bands, by = join_by(between(freq, low, high))) %>%
    count(band) %>%
    right_join(hf_bands %>% select(band), by = "band") %>%
    replace_na(list(n = 0)) %>%
    arrange(band)
}

# --- 5. Live Update Loop ---
repeat {
  tryCatch({
    cat("Scraping for new spots...\n")
    freqs <- get_frequencies()
    counts <- bin_to_bands(freqs)
    
    p <- ggplot(counts, aes(x = band, y = n, fill = band)) +
      geom_col() +
      coord_cartesian(ylim = c(0, max(5, max(counts$n, na.rm = TRUE) + 1))) +
      labs(
        title = paste("Live RBN Spots for K5EM (Last 10 Mins)"),
        subtitle = paste("Last Updated:", Sys.time()),
        x = "HF Band",
        y = "Number of Spots"
      ) +
      theme_minimal(base_size = 14) +
      theme(legend.position = "none")
    
    print(p)
    
    cat("Update complete. Waiting 30 seconds...\n")
  }, error = function(e) {
    cat("An error occurred:", e$message, "\n")
    cat("Retrying in 30 seconds...\n")
  })
  
  Sys.sleep(30)
}