val pattern = "([0-9]+) ([A-Za-z]+)".r
val pattern(count, fruit) = "100 Bananas"scala> val pattern = "([0-9]+) ([A-Za-z]+)".r
pattern: scala.util.matching.Regex = ([0-9]+) ([A-Za-z]+)
scala> val pattern(count, fruit) = "100 Bananas" count: String = 100
fruit: String = Bananas这种语法看上去让人感觉有一点奇怪，好像定义了pattern两次，但实际上这种语法在实际情况下更加直观，代码读起来也比较容易理解。
例如，假设我们需要写一段代码，来识别用户对电影的各种不同搜索方式的检索，比如如以下用户输入字符串：
"movies near 80301"
"movies 80301"
"80301 movies"
"movie: 80301"
"movies: 80301"
"movies near boulder, co"
"movies near boulder, colorado"为了识别这些搜索条件，我们可以写一些pattern来分别识别不同的输入，比如：
// match "movies 80301"
val MoviesZipRE = "movies (\\d{5})".r // match "movies near boulder, co"
val MoviesNearCityStateRE = "movies near ([a-z]+), ([a-z]{2})".r当定义了这些pattern以后，我们可以使用scala的match语句来分别进行匹配，并将匹配后提取的子字符串进行相应的函数调用，如下：
textUserTyped match {
case MoviesZipRE(zip) => getSearchResults(zip)
case MoviesNearCityStateRE(city, state) => getSearchResults(city, state)
case _ => println("did not match a regex")
}可以从以上语法中看出，代码非常的简洁直观。