利用SQL处理CVS文件：CSVQuery
jopen
10年前
CSVQuery是一个用于处理CVS文件的便利 SQL Runner。你可以使用SQL来解析和过滤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