利用SQL處理CVS文件：CSVQuery

CSVQuery是一個用于處理CVS文件的便利 SQL Runner。你可以使用SQL來解析和過濾CSV行。

import scalikejdbc._
import csvquery._
implicit val session = autoCSVSession

// ---
// simple queries

val csv = CSV("./sample.csv", Seq("name", "age"))

val count: Long = withCSV(csv) { table =>
  sql"select count(*) from $table".map(_.long(1)).single.apply().get
}

val records: Seq[Map[String, Any]] = withCSV(csv) { table =>
  sql"select * from $table".toMap.list.apply()
}

// ---
// join queries

case class Account(name: String, companyName: String, company: Option[Company])
case class Company(name: String, url: String)

val (accountsCsv, companiesCsv) = (
  CSV("src/test/resources/accounts.csv", Seq("name", "company_name")),
  CSV("src/test/resources/companies.csv", Seq("name", "url"))
)
val accounts: Seq[Account] = withCSV(accountsCsv, companiesCsv) { (a, c) =>
  sql"select a.name, a.company_name, c.url from $a a left join $c c on a.company_name = c.name".map { rs =>
    new Account(
      name = rs.get("name"),
      companyName = rs.get("company_name"),
      company = rs.stringOpt("url").map(url => Company(rs.get("company_name"), url))
    )
  }.list.apply()
}

// ---
// SkinnyCSVMapper examples
// also required: "org.skinny-framework" %% "skinny-orm"
// NOTICE: Compilation of DAO definitio on the REPL fails, use initialCommands instead.

case class User(name: String, age: Int)
object UserDAO extends SkinnyCSVMapper[User] {
  def csv = CSV("./sample.csv", Seq("name", "age"))
  override def extract(rs: WrappedResultSet, rn: ResultName[User]) = autoConstruct(rs, rn)
}
val users = UserDAO.findAll()
val alice = UserDAO.where('name -> "Alice").apply().headOption

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