# Counts of license actions by date
# Use this file to scrape a series of dates from AE7Q

# Set start and end date
date_vec <- seq(as.Date("2004-11-29"), as.Date("2024-07-22"), by="days")
# Randomize dates we are querying
date_vec <- sample(date_vec)

dvbackup <- date_vec
date_vec <- date_vec[1687:7176]

ae7q_list <- list()
for(i in 1:length(date_vec)){
    ae7q_new_url <- paste0("https://www.ae7q.com/query/list/ProcessDate.php?DATE=", date_vec[i])
    print(ae7q_new_url)
    
    # Read the page
    ae7q_new_raw <- read_html(ae7q_new_url)
    
    # Make sure the new license table exists first
    if(!grepl("No license grants found issued on",  ae7q_new_raw %>% html_text())){
        # Get tables and clean up
        ae7q_new_tables <- ae7q_new_raw %>% 
            html_elements(xpath = "//table") %>% 
            html_table()
        
        # Find the right table by the column names
        right_table_id <- grep(paste(c("Callsign",
                                       "Region/ State",
                                       "Entity Name",
                                       "Applicant Type",
                                       "Licensee Class",
                                       "License Status",
                                       "Action Type"), collapse = " "),
                               lapply(ae7q_new_tables, function(x) paste(names(x), collapse = " ")))
        
        ae7q_table_new <- ae7q_new_tables[[right_table_id]]
        
        ae7q_list[[i]] <- ae7q_table_new %>% 
            #mutate(across(everything(), ~na_if(., "\""))) %>% 
            mutate(across(everything(), 
                          ~ case_when(. == "\"" ~ NA, 
                                      TRUE ~ .))) %>% 
            fill(everything()) %>% 
            group_by(`Action Type`) %>% 
            summarize(count = n(), .groups = "keep") %>% 
            mutate(date = date_vec[i],
                   source = "AE7Q", source_detail = ae7q_new_url) %>% 
            relocate(date)
    } else {
        ae7q_list[[i]]<- data.frame("date" = date_vec[i],
                                    "Action Type" = NA,
                                    "count" = NA,
                                    "source" = "AE7Q",
                                    "source_detail" = ae7q_new_url)
    }
    # Wait for random time up to 10 seconds
    Sys.sleep(sample(1:5, 1))
}

# Combine all the data and sort by date
a <- bind_rows(ae7q_list) %>% 
    arrange(date) %>% 
    filter(!is.na(date))

write.csv(a, "out/ae7q-actions-scraped03.csv", row.names = F)