// A Web-Scraper that extracts the daily Shanghai polution
// data from the web-page
//
//   http://www.envir.gov.cn/eng/airep/index.asp
//
//
// Important! They stopped providing this data in November
// 2012, but kept the historical data since 2001. So dates
// must be in that range.

import java.io.OutputStreamWriter
import java.net.URL
import scala.io.Source.fromInputStream

val url = new URL("http://www.envir.gov.cn/eng/airep/index.asp")

//connecting to url
val conn = url.openConnection
conn.setRequestProperty("User-Agent", "")
conn.setDoOutput(true)
conn.connect

//sending data
val wr = new OutputStreamWriter(conn.getOutputStream())

//possible date ranges
wr.write("Fdate=2012-8-24&Tdate=2012-09-25")
//wr.write("Fdate=2001-9-18&Tdate=2012-09-24")
wr.flush
wr.close

//receiving data
val page = fromInputStream(conn.getInputStream).getLines.mkString("\n")

//data encoded as an HTML-string, which you can see with
//println(page)

// regular expression: excludes newlines, 
// therefore we have to use [\S\s]
val regex1 = """<tr align=\"center\">[\S\s]*?</tr>""".r
val rows = regex1.findAllIn(page).toList

//print(rows)

val regex2 = """<td align=\"center\">([\S\s]*?)</td>""".r

def aux(s: String) : Array[String] = {
  for (m <- regex2.findAllIn(s).toArray) yield m match {
    case regex2(value) => value.trim
  }
}

//data completely extracted
val data = rows.map { aux }

//for comparing elements from an array
def compare(i: Int)(e: Array[String], f: Array[String]) = e(i).toInt < f(i).toInt

println("The day with highest particle pollution (PM_10)")
println(data.sortWith(compare(1)).last.mkString(","))

println("The day with highest sulfur dioxide (SO_2)")
println(data.sortWith(compare(2)).last.mkString(","))

println("The day with highest nitro dioxide (NO_2)")
println(data.sortWith(compare(3)).last.mkString(","))

println("The day(s) with highest PM_10")
val groups1 = data.groupBy(_(1).toInt)
val max_key1 = groups1.keySet.max
println(groups1(max_key1).map(_.mkString(",")).mkString("\n"))

println("The day(s) with highest SO_2")
val groups2 = data.groupBy(_(2).toInt)
val max_key2 = groups2.keySet.max
println(groups2(max_key2).map(_.mkString(",")).mkString("\n"))

println("The day(s) with highest NO_2")
val groups3 = data.groupBy(_(3).toInt)
val max_key3 = groups3.keySet.max
println(groups3(max_key3).map(_.mkString(",")).mkString("\n"))