1.2.0

Added plotmap function.

Author: ip2location

DESCRIPTION

@@ -1,16 +1,15 @@
 Package: ip2proxy
 Type: Package
 Title: Lookup for IP Address Proxy Information
-Version: 1.0.0
+Version: 1.2.0
 Author: IP2Location
 Maintainer: IP2Location <[email protected]>
 Description: A R package to find the IP addresses which are used as VPN anonymizer, open proxies, web proxies and Tor exits.
     The package lookup the proxy IP address from IP2Proxy BIN Data file. You may visit <https://lite.ip2location.com> for free database download. 
 License: MIT + file LICENSE
 Encoding: UTF-8
 Depends: R (>= 3.2.3)
-Imports: reticulate (>= 1.13), stringr (>= 1.4.0), jsonlite (>= 1.6)
-LazyData: true
+Imports: reticulate (>= 1.13), jsonlite (>= 1.6), ggplot2 (>= 3.4), maps (>= 3.4.1), scales (>= 1.2.1)
 SystemRequirements: IP2Proxy Python library
         <https://www.ip2location.com/development-libraries/ip2proxy/python>
-RoxygenNote: 7.1.1
+RoxygenNote: 7.2.3

NAMESPACE

@@ -2,6 +2,12 @@
 
 export(get_all)
 export(is_proxy)
+export(lookup_web_service)
 export(open)
+export(plot_map)
+import(ggplot2)
 import(jsonlite)
+import(maps)
 import(reticulate)
+import(scales)
+import(utils)

R/IP2Proxy.r

@@ -5,7 +5,7 @@
 #' @return NULL
 #' @import reticulate
 #' @export
-#' @examples \donttest{
+#' @examples \dontrun{
 #' open("~/IP-COUNTRY.BIN")
 #' }
 #'
@@ -19,14 +19,14 @@ open <- function(bin_location){
 
 #' @title Lookup for IP address proxy information
 #'
-#' @description Find the country, region, city, ISP, domain name, usage types, asn, as name, last seen and threat type. The return values will be depending on the BIN data loaded.
+#' @description Find the country, region, city, ISP, domain name, usage types, asn, as name, last seen, threat type and provider. The return values will be depending on the BIN data loaded.
 #' @param ip IPv4 or IPv6 address
 #' @return Return all the proxy information about the IP address
 #' @import reticulate
 #' @import jsonlite
 #' @export
-#' @examples \donttest{
-#' get_all("8.8.8.8")
+#' @examples \dontrun{
+#' get_all("1.0.241.135")
 #' }
 #'
 
@@ -45,8 +45,8 @@ get_all <- function(ip){
 #' @import reticulate
 #' @import jsonlite
 #' @export
-#' @examples \donttest{
-#' is_proxy("8.8.8.8")
+#' @examples \dontrun{
+#' is_proxy("1.0.241.135")
 #' }
 #'
 
@@ -59,3 +59,29 @@ is_proxy <- function(ip){
   result = fromJSON(py$j1)
   return(result['is_proxy'])
 }
+
+#' @title Lookup for IP address proxy information using IP2Proxy web service.
+#' @param api_key IP2Proxy web service API key
+#' @param ip IPv4 or IPv6 address
+#' @param package Package to use for IP2Proxy web service.
+#' @description Find the country, region, city, ISP, domain name, usage types, asn, as name, last seen, threat type and provider. The return values will be depending on the IP2Proxy web service package used.
+#' @return Return all the proxy information about the IP address
+#' @import reticulate
+#' @import jsonlite
+#' @export
+#' @examples \dontrun{
+#' lookup_web_service("1.0.241.135","PX1")
+#' }
+#'
+
+lookup_web_service <- function(api_key, ip, package = 'PX1'){
+  py_run_string("import IP2Proxy")
+  py_run_string("import json")
+  ws_initialize = paste("ws = IP2Proxy.IP2ProxyWebService('", api_key, "','", package, "',True)", sep = "")
+  py_run_string(ws_initialize)
+  API_result = paste("rec = ws.lookup('", ip, "')", sep = "")
+  py_run_string(API_result)
+  py_run_string("j = json.dumps(rec)")
+  result = fromJSON(py$j)
+  return(result)
+}

R/IP2Proxy_plotmap.R

@@ -0,0 +1,76 @@
+if(getRversion() >= "2.15.1")  utils::globalVariables(c("long", "lat", "group", "prop"))
+
+#' @title Plot map using IP2Location data.
+#'
+#' @description Plot the country on the map based on IP addresses and its IP2Location country data.
+#' @param ips A vector of IP addresses to be plot on
+#' @return NULL
+#' @import maps
+#' @import ggplot2
+#' @import scales
+#' @import utils
+#' @export
+#' @examples \dontrun{
+#' plot_map(c("1.0.241.135", "1.2.3.4"))
+#' }
+#'
+
+plot_map <- function(ips){
+  countries = c()
+  mapData = map_data("world")
+  for ( i in ips ) {
+    result = ip2proxy::get_all(i)
+    countries = append(countries, toString(result["country_long"]))
+  }
+
+  country_table    <- table(countries)
+  ipData  <- data.frame(country_table)
+
+  variable1 = deparse(substitute(countries))
+  variable1 = strsplit(variable1, "\\$")[[1]][2]
+
+  if(ncol(ipData) == 2) {
+    names(ipData) <- c(variable1, "n")
+  } else if(ncol(ipData) > 2){
+    names(ipData)[length(ipData)] <- "n"
+  }
+
+  prop <- as.vector(country_table)/sum(country_table)
+  ipData  <- data.frame(ipData, prop)
+
+  table.prop <- as.vector(country_table)/sum(country_table)
+  table.perc <- format(round(table.prop*100, 1), nsmall = 1)
+  table.perc <- gsub("$", "%", table.perc)
+  ipData <- data.frame(ipData, table.perc)
+
+  names(ipData)[1] = "group"
+
+  path = find.package("ip2proxy")
+
+  #data <- read.csv("inst\\countrynames_mapping.txt", header=TRUE)
+  data <- read.csv(paste(path, '/countrynames_mapping.txt', sep = ""), header=TRUE)
+
+  data$matched_country_name[data$matched_country_name == ''] <- NA
+
+  for(i in 1:nrow(data)){
+    if(!is.na(data[i, "matched_country_name"])){
+      old.name <- paste(data[i, "country_name"])
+      new.name <- paste(data[i, "matched_country_name"])
+      ipData[, "group"] <- gsub(old.name, new.name, ipData[, "group"])
+    }
+  }
+
+  worldMapIPs <- merge(mapData, ipData, by.x = "region", by.y = "group", all.x = TRUE)
+  worldMapIPs <- worldMapIPs[order(worldMapIPs[, "order"]), ]
+  worldMapIPs[is.na(worldMapIPs)] <- 0
+  world <- map_data("world")
+  p <- ggplot() +
+    geom_polygon(data=world, aes(x=long, y=lat, group = group),
+                 colour = "#595959", fill = "white") + theme(panel.background = element_rect(fill = "#b2cce5"), plot.background = element_rect(fill = "#b2cce5"))
+
+  mapcolors = c("black", "#d6d6d6", "white")
+  mapvalues = c(1, .025, 0)
+
+
+  p + geom_polygon(data=worldMapIPs, aes(x=long, y=lat, group = group, fill = prop)) + geom_path(data=worldMapIPs, aes(x=long, y=lat, group=group), color="#595959", size=0.05) + scale_fill_gradientn(colours= mapcolors, values= mapvalues, labels = percent_format(), limits = c(0,1)) + theme(plot.title = element_text(size = 20, colour = "black", family = "sans", margin = unit(c(0, 0, 5, 0), "mm"))) + scale_y_continuous(name=NULL, breaks=NULL, expand = c(0,0)) + scale_x_continuous(name=NULL, breaks=NULL, expand = c(0,0)) + theme(legend.justification = c(0, 0), legend.position = c(0, 0.32), legend.background = element_blank(), legend.title = element_blank(), legend.text = element_text(size = rel(1.1), colour = "black", family = "sans")) + guides(fill = guide_colorbar(barwidth = rel(0.5), barheight = rel(5.0), ticks = F))
+}