About
CSV parser library for Scala. Easiest way to convert CSV string representation into a case class.
Usage
import zamblauskas.csv.parser._
case class Person(name: String, age: Int, city: Option[String])
val csv = """
|name,age,height,city
|Emily,33,169,London
|Thomas,25,,
""".stripMargin
val result = Parser.parse[Person](csv)
result shouldBe Right(List(Person("Emily",33,Some("London")), Person("Thomas",25,None)))ColumnReads[T]
Example above used a macro generated ColumnReads[Person].
You can define one manually if the generated one does not fit your use case
(e.g. column names differ from case class parameter names).
This is identical to what the macro generates for a Person case class:
import zamblauskas.csv.parser._
import zamblauskas.functional._
case class Person(name: String, age: Int, city: Option[String])
implicit val personReads: ColumnReads[Person] = (
column("name").as[String] and
column("age").as[Int] and
column("city").asOpt[String]
)(Person)
val csv = """
|name,age,height,city
|Emily,33,169,London
|Thomas,25,,
""".stripMargin
val result = Parser.parse[Person](csv)
result shouldBe Right(List(Person("Emily",33,Some("London")), Person("Thomas",25,None)))Alternative column names
If columns have two or more alternative names (e.g. in different languages),
you can use an or combinator.
import zamblauskas.csv.parser._
import zamblauskas.functional._
import Parser.parse
case class Person(age: Int, city: String)
implicit val personReads: ColumnReads[Person] = (
(column("age").as[Int] or column("alter").as[Int]) and
(column("city").as[String] or column("stadt").as[String])
)(Person)
val englishCsv =
"""
|age,city
|33,London
""".stripMargin
val germanCsv =
"""
|alter,stadt
|33,London
""".stripMargin
parse[Person](englishCsv) shouldBe parse[Person](germanCsv)Alternative reads
Example above can be rewritten to use alternative ColumnReads instead of alternative column names.
import zamblauskas.csv.parser._
import zamblauskas.functional._
import Parser.parse
case class Person(age: Int, city: String)
val englishPersonReads: ColumnReads[Person] = (
column("age").as[Int] and
column("city").as[String]
)(Person)
val germanPersonReads: ColumnReads[Person] = (
column("alter").as[Int] and
column("stadt").as[String]
)(Person)
implicit val personReads = englishPersonReads or germanPersonReads
val englishCsv =
"""
|age,city
|33,London
""".stripMargin
val germanCsv =
"""
|alter,stadt
|33,London
""".stripMargin
parse[Person](englishCsv) shouldBe parse[Person](germanCsv)SBT dependency
Package is available on Maven Central.
Check the link for the latest version and add to your build.sbt:
libraryDependencies += "io.github.zamblauskas" %% "scala-csv-parser" % "<latest_version>"