There are two main use-cases for regular expressions:
- predicates (does a string match a given pattern?)
- data extraction (grab whatever matches a given pattern)
Kantan.regex is solely concerned with the second use case, and is meant to make data extraction from strings as painless as possible - you still have to write regular expressions, so still a bit painful, but at least the rest is automated away and checked by the compiler.
Documentation and tutorials are available on the companion site, but for those looking for a few quick examples:
import kantan.regex._
import kantan.regex.implicits._
import kantan.regex.generic._
// Returns an iterator on all parts of str that look like a positive integer
"abc 123 def".evalRegex[Int](rx"\d+")
// Returns an iterator on all parts of str that look like an (x, y) point. Points
// are represented as a Tuple2[Int, Int]
"(1, 2) and then (3, 4)".evalRegex[(Int, Int)](rx"\((\d+), (\d+)\)")
// Declares a new Point case class, lets shapeless work out how to decode for it.
case class Point(x: Int, y: Int)
// Returns an iterator on all parts of str that look like an (x, y) point. Points
// are represented as Point.
"(1, 2) and then (3, 4)".evalRegex[Point](rx"\((\d+), (\d+)\)")
// A somewhat contrived example where the z-coordinate of a point is optional:
"(1, 2) and then (3, 4, 5)".evalRegex[(Int, Int, Option[Int])](rx"\((\d+), (\d+)(?:, (\d+))?\)")kantan.regex is distributed under the Apache 2.0 License.