Anorm has been pulled out of the core of Play into a separately managed project that can have its own lifecycle. To add a dependency on it, use:

libraryDependencies += "" %% "anorm" % "2.4.0"

The release 2.4.0 of Anorm requires Java 8. The last version compatible with a JDK 1.6 or 1.7 is Anorm 2.3.9.


The new Anorm version includes various fixes and improvements.

Following BatchSQL #3016, SqlQuery case class is refactored as a trait with companion object.
Consequently, BatchSql is now created by passing a raw statement which is validated internally.

import anorm.BatchSql

// Before
BatchSql(SqlQuery("SQL")) // No longer accepted (won't compile)

// Now
// Simpler and safer, as SqlQuery is created&validated internally


It’s now possible to get values from Row using the column index.

val res: (String, String) = SQL("SELECT * FROM Test").map(row =>
 row[String](1) -> row[String](2) // string columns #1 and #2

Column resolution per label is now unified, whatever the label is name or alias.

val res: (String, Int) = SQL"SELECT text, count AS i".map(row =>
  row[String]("text") -> row[Int]("i")

New fold and foldWhile functions to work with result stream.

val countryCount: Either[List[Throwable], Long] =
  SQL"Select count(*) as c from Country".fold(0l) { (c, _) => c + 1 }

val books: Either[List[Throwable], List[String]] =
 SQL("Select name from Books").foldWhile(List[String]()) { (list, row) =>
  foldWhile(List[String]()) { (list, row) =>
    if (list.size == 100) (list -> false) // stop with `list`
    else (list := row[String]("name")) -> true // continue with one more name

New withResult function to provide custom stream parser.

import anorm.{ Cursor, Row }
def go(c: Option[Cursor], l: List[String]): List[String] = c match {
  case Some(cursor) => {
    if (l.size == 100) l // custom limit, partial processing
    else {
      val row =
      go(it, l :+ row[String]("name"))
  case _ => l

val books: Either[List[Throwable], List[String]] =
  SQL("Select name from Books").withResult(go(_, List.empty[String]))

§Type mappings

More parameter and column conversions are available.


A column can be multi-value if its type is JDBC array (java.sql.Array). Now Anorm can map it to either array or list (Array[T] or List[T]), provided type of element (T) is also supported in column mapping.

import anorm.SQL
import anorm.SqlParser.{ scalar, * }

// array and element parser
import anorm.Column.{ columnToArray, stringToArray }

val res: List[Array[String]] =
  SQL("SELECT str_arr FROM tbl").as(scalar[Array[String]].*)

New convenient parsing functions are also provided for arrays with SqlParser.array[T](...) and SqlParser.list[T](...)

In case JDBC statement is expecting an array parameter (java.sql.Array), its value can be passed as Array[T], as long as element type T is a supported one.

val arr = Array("fr", "en", "ja")
SQL"UPDATE Test SET langs = $arr".execute()

Multi-value parameter

New conversions are available to pass List[T], Set[T], SortedSet[T], Stream[T] and Vector[T] as multi-value parameter.

SQL("SELECT * FROM Test WHERE cat IN ({categories})")
 .on('categories -> List(1, 3, 4))

SQL("SELECT * FROM Test WHERE cat IN ({categories})")
 .on('categories -> Set(1, 3, 4))

SQL("SELECT * FROM Test WHERE cat IN ({categories})")
 .on('categories -> SortedSet("a", "b", "c"))

SQL("SELECT * FROM Test WHERE cat IN ({categories})")
 .on('categories -> Stream(1, 3, 4))

SQL("SELECT * FROM Test WHERE cat IN ({categories})")
 .on('categories -> Vector("a", "b", "c"))

Numeric and boolean types

Column conversions for basic types like numeric and boolean ones have been improvided.

Some invalid conversions are removed:

Column (JDBC type) (as) JVM/Scala type
Double Boolean
Int Boolean

There are new conversions extending column support.

Column (JDBC type) (as) JVM/Scala type
BigDecimal BigInteger
BigDecimal Int
BigDecimal Long
BigInteger BigDecimal
BigInteger Int
BigInteger Long
Boolean Int
Boolean Long
Boolean Short
Byte BigDecimal
Float BigDecimal
Int BigDecimal
Long Int
Short BigDecimal

Binary and large data

New column conversions are provided for binary columns (bytes, stream, blob), to be parsed as Array[Byte] or InputStream.

↓JDBC / JVM➞ Array[Byte] InputStream1
Array[Byte] Yes Yes
Blob2 Yes Yes
Clob3 No No
InputStream4 Yes Yes
Reader5 No No

Binary and large data can also be used as parameters:

Array[Byte] Long varbinary
Blob1 Blob
InputStream2 Long varbinary
Reader3 Long varchar


Next: Migrating Plugin to Module

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