更新：问题解决了

Question

我正在尝试使用Scala解析器组合器编写CSV解析器。语法基于RFC4180。我想出了以下代码。它几乎可以工作，但我不能让它正确地分隔不同的记录。我错过了什么？

object CSV extends RegexParsers {
  def COMMA   = ","
  def DQUOTE  = "\""
  def DQUOTE2 = "\"\"" ^^ { case _ => "\"" }
  def CR      = "\r"
  def LF      = "\n"
  def CRLF    = "\r\n"
  def TXT     = "[^\",\r\n]".r

  def file: Parser[List[List[String]]] = ((record~((CRLF~>record)*))<~(CRLF?)) ^^ { 
    case r~rs => r::rs
  }
  def record: Parser[List[String]] = (field~((COMMA~>field)*)) ^^ {
    case f~fs => f::fs
  }
  def field: Parser[String] = escaped|nonescaped
  def escaped: Parser[String] = (DQUOTE~>((TXT|COMMA|CR|LF|DQUOTE2)*)<~DQUOTE) ^^ { case ls => ls.mkString("")}
  def nonescaped: Parser[String] = (TXT*) ^^ { case ls => ls.mkString("") }

  def parse(s: String) = parseAll(file, s) match {
    case Success(res, _) => res
    case _ => List[List[String]]()
  }
}


println(CSV.parse(""" "foo", "bar", 123""" + "\r\n" + 
  "hello, world, 456" + "\r\n" +
  """ spam, 789, egg"""))

// Output: List(List(foo, bar, 123hello, world, 456spam, 789, egg)) 
// Expected: List(List(foo, bar, 123), List(hello, world, 456), List(spam, 789, egg))

更新：问题解决了

默认的RegexParsers使用正则表达式[\s]+忽略空格，包括空格，制表符，回车符和换行符。上面的解析器无法分离记录的问题是由于这个原因。我们需要禁用skipWhitespace模式。将whiteSpace定义替换为[ \t]}并不能解决问题，因为它会忽略字段中的所有空格（因此CSV中的“foo bar”变为“foobar”），这是不希望的。因此，解析器的更新源是

import scala.util.parsing.combinator._

// A CSV parser based on RFC4180
// http://tools.ietf.org/html/rfc4180

object CSV extends RegexParsers {
  override val skipWhitespace = false   // meaningful spaces in CSV

  def COMMA   = ","
  def DQUOTE  = "\""
  def DQUOTE2 = "\"\"" ^^ { case _ => "\"" }  // combine 2 dquotes into 1
  def CRLF    = "\r\n" | "\n"
  def TXT     = "[^\",\r\n]".r
  def SPACES  = "[ \t]+".r

  def file: Parser[List[List[String]]] = repsep(record, CRLF) <~ (CRLF?)

  def record: Parser[List[String]] = repsep(field, COMMA)

  def field: Parser[String] = escaped|nonescaped


  def escaped: Parser[String] = {
    ((SPACES?)~>DQUOTE~>((TXT|COMMA|CRLF|DQUOTE2)*)<~DQUOTE<~(SPACES?)) ^^ { 
      case ls => ls.mkString("")
    }
  }

  def nonescaped: Parser[String] = (TXT*) ^^ { case ls => ls.mkString("") }



  def parse(s: String) = parseAll(file, s) match {
    case Success(res, _) => res
    case e => throw new Exception(e.toString)
  }
}

Answer 1

你错过的是空白。我投入了一些奖励改进。

import scala.util.parsing.combinator._

object CSV extends RegexParsers {
  override protected val whiteSpace = """[ \t]""".r

  def COMMA   = ","
  def DQUOTE  = "\""
  def DQUOTE2 = "\"\"" ^^ { case _ => "\"" }
  def CR      = "\r"
  def LF      = "\n"
  def CRLF    = "\r\n"
  def TXT     = "[^\",\r\n]".r

  def file: Parser[List[List[String]]] = repsep(record, CRLF) <~ opt(CRLF)
  def record: Parser[List[String]] = rep1sep(field, COMMA)
  def field: Parser[String] = (escaped|nonescaped)
  def escaped: Parser[String] = (DQUOTE~>((TXT|COMMA|CR|LF|DQUOTE2)*)<~DQUOTE) ^^ { case ls => ls.mkString("")}
  def nonescaped: Parser[String] = (TXT*) ^^ { case ls => ls.mkString("") }

  def parse(s: String) = parseAll(file, s) match {
    case Success(res, _) => res
    case _ => List[List[String]]()
  }
}

Answer 2

从2.11开始，Scala标准库中的Scala Parser Combinators库没有充分的理由不使用性能更高的Parboiled2库。以下是Parboiled2的DSL中的CSV解析器的一个版本：

/*  based on comments in https://github.com/sirthias/parboiled2/issues/61 */
import org.parboiled2._
case class Parboiled2CsvParser(input: ParserInput, delimeter: String) extends Parser {
  def DQUOTE = '"'
  def DELIMITER_TOKEN = rule(capture(delimeter))
  def DQUOTE2 = rule("\"\"" ~ push("\""))
  def CRLF = rule(capture("\r\n" | "\n"))
  def NON_CAPTURING_CRLF = rule("\r\n" | "\n")

  val delims = s"$delimeter\r\n" + DQUOTE
  def TXT = rule(capture(!anyOf(delims) ~ ANY))
  val WHITESPACE = CharPredicate(" \t")
  def SPACES: Rule0 = rule(oneOrMore(WHITESPACE))

  def escaped = rule(optional(SPACES) ~
    DQUOTE ~ (zeroOrMore(DELIMITER_TOKEN | TXT | CRLF | DQUOTE2) ~ DQUOTE ~
    optional(SPACES)) ~> (_.mkString("")))
  def nonEscaped = rule(zeroOrMore(TXT | capture(DQUOTE)) ~> (_.mkString("")))

  def field = rule(escaped | nonEscaped)
  def row: Rule1[Seq[String]] = rule(oneOrMore(field).separatedBy(delimeter))
  def file = rule(zeroOrMore(row).separatedBy(NON_CAPTURING_CRLF))

  def parsed() : Try[Seq[Seq[String]]] = file.run()
}

Answer 3

RegexParsers解析器的默认空格为\s+，其中包含新行。因此，CR，LF和CRLF永远不会有机会被处理，因为解析器会自动跳过它。

使用Scala解析器组合器来解析CSV文件

更新：问题解决了

3 个答案: