Below is the scenario of 2 case classes that I have -
case class Pack(name: String, age: Int, dob: String)
object Pack{
def getPack(name:String, age: Int, dob:String): Pack = {
Pack(name,age,dob)
}
}
case class NewPack(name: String, pack: (List[Pack]))
object NewPack{
def getNewPackList(data: List[Pack]): List[NewPack] = {
val newData = for(x <- data )yield(x.name,List(x))
val newPackData = for(x <- newData)yield(NewPack(x._1,x._2))
newPackData
}
}
val someData = List(Pack.getPack("x",12,"day1"), Pack.getPack("y",23,"day2"),Pack.getPack("x",34,"day3") )
val somePackData = NewPack.getNewPackList(someData)
the values of someData and somePackData is like this -
someData: List[Pack] = List(Pack(x,12,day1), Pack(y,23,day2), Pack(x,34,day3))
somePackData: List[NewPack] = List(NewPack(x,List(Pack(x,12,day1))), NewPack(y,List(Pack(y,23,day2))), NewPack(x,List(Pack(x,34,day3))))
Now I want to get the final data in the below mentioned format. Could anyone suggest me the better way of doing that.
finalData: List[NewPack] = List(NewPack(x,List(Pack(x,12,day1),Pack(x,34,day3)),NewPack(y,List(Pack(y,23,day2))))
Here is small simplification.
case class Pack(name: String, age: Int, dob: String)
case class NewPack(name: String, pack: List[Pack])
object NewPack{
def getNewPackList(data: List[Pack]): List[NewPack] =
data.map{case pack#Pack(name, _, _) => NewPack(name, List(pack))}
}
Note that in general you don't need additional factory method for case class. If you would like to present something tricky later, you can always define custom apply in your companion object.
Additionally if you were intending to group packs by name you can easily define something like
def newPacksGrouped(data: List[Pack]): List[NewPack] =
data.groupBy(_.name).map{case (name, packs) => NewPack(name, packs)}.toList
Related
im getting in my api some case class that looks like this:
case class UserUpdate(
name: Option[String],
age: Option[String],
city: Option[String])
from this case class I need to build update json for mongo that looks like:
{"basicInfo.name": "new nameeee","age.vatId": "23"}
since all the fields are optional, I need to go over the fields and build it by the ones that are defined.
so I did something like this:
val updateAsMap = Json.toJson(userUpdateObj).as[JsObject]
.fields.map(fieldTpl => fieldTpl.copy(_1 = s"basicInfo.${fieldTpl._1}")).toMap
val userUpdateJson = Json.toJson(updateAsMap)
val query = json("userId" -> userId)
val update = json("$set" -> userUpdateJson)
is there a better suggestion, something that will look more elegant?
One option could be to convert UserUpdate to an intermediary case class, say MongoModel, and then convert MongoModel to JSON. For example,
import play.api.libs.json._
case class MongoModel(
`basicInfo.name`: Option[String] = None,
`age.vatId`: Option[String] = None
)
object MongoModel {
implicit val codec = Json.format[MongoModel]
}
case class UserUpdate(
name: Option[String] = None,
age: Option[String] = None,
city: Option[String] = None
) {
def toMongoModel =
MongoModel(
`basicInfo.name` = name,
`age.vatId` = age
)
}
val userUpdate = UserUpdate(name = Some("new nameeee"), age = Some("23"))
Json.toJson(userUpdate.toMongoModel) // {"basicInfo.name": "new nameeee", "age.vatId": "23"}: JsValue
Note the usage of backticks in MongoModel.
My use case has case classes something like
case class Address(name:String,pincode:String){
override def toString =name +"=" +pincode
}
case class Department(name:String){
override def toString =name
}
case class emp(address:Address,department:Department)
I want to create a DSL like below.Can anyone share the links about how to create a DSL and any suggestions to achieve the below.
emp.withAddress("abc","12222").withDepartment("HR")
Update:
Actual use case class may have more fields close to 20. I want to avoid redudancy of code
I created a DSL using reflection so that we don't need to add every field to it.
Disclamer: This DSL is extremely weakly typed and I did it just for fun. I don't really think this is a good approach in Scala.
scala> create an Employee where "homeAddress" is Address("a", "b") and "department" is Department("c") and that_s it
res0: Employee = Employee(a=b,null,c)
scala> create an Employee where "workAddress" is Address("w", "x") and "homeAddress" is Address("y", "z") and that_s it
res1: Employee = Employee(y=z,w=x,null)
scala> create a Customer where "address" is Address("a", "b") and "age" is 900 and that_s it
res0: Customer = Customer(a=b,900)
The last example is the equivalent of writing:
create.a(Customer).where("address").is(Address("a", "b")).and("age").is(900).and(that_s).it
A way of writing DSLs in Scala and avoid parentheses and the dot is by following this pattern:
object.method(parameter).method(parameter)...
Here is the source:
// DSL
object create {
def an(t: Employee.type) = new ModelDSL(Employee(null, null, null))
def a(t: Customer.type) = new ModelDSL(Customer(null, 0))
}
object that_s
class ModelDSL[T](model: T) {
def where(field: String): ValueDSL[ModelDSL2[T], Any] = new ValueDSL(value => {
val f = model.getClass.getDeclaredField(field)
f.setAccessible(true)
f.set(model, value)
new ModelDSL2[T](model)
})
def and(t: that_s.type) = new { def it = model }
}
class ModelDSL2[T](model: T) {
def and(field: String) = new ModelDSL(model).where(field)
def and(t: that_s.type) = new { def it = model }
}
class ValueDSL[T, V](callback: V => T) {
def is(value: V): T = callback(value)
}
// Models
case class Employee(homeAddress: Address, workAddress: Address, department: Department)
case class Customer(address: Address, age: Int)
case class Address(name: String, pincode: String) {
override def toString = name + "=" + pincode
}
case class Department(name: String) {
override def toString = name
}
I really don't think you need the builder pattern in Scala. Just give your case class reasonable defaults and use the copy method.
i.e.:
employee.copy(address = Address("abc","12222"),
department = Department("HR"))
You could also use an immutable builder:
case class EmployeeBuilder(address:Address = Address("", ""),department:Department = Department("")) {
def build = emp(address, department)
def withAddress(address: Address) = copy(address = address)
def withDepartment(department: Department) = copy(department = department)
}
object EmployeeBuilder {
def withAddress(address: Address) = EmployeeBuilder().copy(address = address)
def withDepartment(department: Department) = EmployeeBuilder().copy(department = department)
}
You could do
object emp {
def builder = new Builder(None, None)
case class Builder(address: Option[Address], department: Option[Department]) {
def withDepartment(name:String) = {
val dept = Department(name)
this.copy(department = Some(dept))
}
def withAddress(name:String, pincode:String) = {
val addr = Address(name, pincode)
this.copy(address = Some(addr))
}
def build = (address, department) match {
case (Some(a), Some(d)) => new emp(a, d)
case (None, _) => throw new IllegalStateException("Address not provided")
case _ => throw new IllegalStateException("Department not provided")
}
}
}
and use it as emp.builder.withAddress("abc","12222").withDepartment("HR").build().
You don't need optional fields, copy, or the builder pattern (exactly), if you are willing to have the build always take the arguments in a particular order:
case class emp(address:Address,department:Department, id: Long)
object emp {
def withAddress(name: String, pincode: String): WithDepartment =
new WithDepartment(Address(name, pincode))
final class WithDepartment(private val address: Address)
extends AnyVal {
def withDepartment(name: String): WithId =
new WithId(address, Department(name))
}
final class WithId(address: Address, department: Department) {
def withId(id: Long): emp = emp(address, department, id)
}
}
emp.withAddress("abc","12222").withDepartment("HR").withId(1)
The idea here is that each emp parameter gets its own class which provides a method to get you to the next class, until the final one gives you an emp object. It's like currying but at the type level. As you can see I've added an extra parameter just as an example of how to extend the pattern past the first two parameters.
The nice thing about this approach is that, even if you're part-way through the build, the type you have so far will guide you to the next step. So if you have a WithDepartment so far, you know that the next argument you need to supply is a department name.
If you want to avoid modifying the origin classes you can use implicit class, e.g.
implicit class EmpExtensions(emp: emp) {
def withAddress(name: String, pincode: String) {
//code omitted
}
// code omitted
}
then import EmpExtensions wherever you need these methods
Is it possible to add functionality before calling constructor in extra constructor in scala ?
Lets say, I have class User, and want to get one string - and to split it into attributes - to send them to the constructor:
class User(val name: String, val age: Int){
def this(line: String) = {
val attrs = line.split(",") //This line is leading an error - what can I do instead
this(attrs(0), attrs(1).toInt)
}
}
So I know I'm not able to add a line before sending to this, because all constructors need to call another constructor as the first statement of the constructor.
Then what can I do instead?
Edit:
I have a long list of attributes, so I don't want to repeat line.split(",")
I think this is a place where companion object and apply() method come nicely into play:
object User {
def apply(line: String): User = {
val attrs = line.split(",")
new User(attrs(0), attrs(1).toInt)
}
}
class User(val name: String, val age: Int)
Then you just create your object the following way:
val u1 = User("Zorro,33")
Also since you're exposing name and age anyway, you might consider using case class instead of standard class and have consistent way of constructing User objects (without new keyword):
object User {
def apply(line: String): User = {
val attrs = line.split(",")
new User(attrs(0), attrs(1).toInt)
}
}
case class User(name: String, age: Int)
val u1 = User("Zorro,33")
val u2 = User("Zorro", "33")
Ugly, but working solution#1:
class User(val name: String, val age: Int){
def this(line: String) = {
this(line.split(",")(0), line.split(",")(1).toInt)
}
}
Ugly, but working solution#2:
class User(val name: String, val age: Int)
object User {
def fromString(line: String) = {
val attrs = line.split(",")
new User(attrs(0), attrs(1).toInt)
}
}
Which can be used as:
val johny = User.fromString("johny,35")
You could use apply in place of fromString, but this will lead to a confusion (in one case you have to use new, in the other you have to drop it) so I prefer to use different name
Another ugly solution:
class User(line: String) {
def this(name: String, age: Int) = this(s"$name,$age")
val (name, age) = {
val Array(nameStr,ageStr) = line.split(",")
(nameStr,ageStr.toInt)
}
}
But using a method of the companion object is probably better.
I'm trying to improve a CSV parsing routine and feel that extractors could be useful here but can't figure them out. Suppose there's a file with user ids and emails:
1,alice#alice.com
2,bob#bob.com
3,carol#carol.com
If the User class is defined as case class User(id: Int, email: String) everything is pretty easy with something like
lines map { line =>
line split "," match {
case Array(id, email) => User(id.toInt, email)
}
}
What I don't understand is how to deal with the case where User class can have complex properties e.g
case class Email(username: String, host: string)
case class User(id: Int, email: Email)
You probably want to use a regular expression to extract the contents of the email address. Maybe something like this:
val lines = Vector(
"1,alice#alice.com",
"2,bob#bob.com",
"3,carol#carol.com")
case class Email(username: String, host: String)
case class User(id: Int, email: Email)
val EmailRe = """(.*)#(.*\.com)""".r // substitute a real email address regex here
lines.map { line =>
line.split(",") match {
case Array(id, EmailRe(uname, host)) => User(id.toInt, Email(uname, host))
}
}
Here you go, an example using a custom Extractor.
// 1,Alice,21212,Baltimore,MD" -> User(1, Alice, Address(21212, Baltimore, MD))
Define a custom Extractor that creates the objects out of given String:
object UserExtractor {
def unapply(s: String) : Option[User] = try {
Some( User(s) )
}
catch {
// bettor handling of bad cases
case e: Throwable => None
}
}
Case classes to hold the data with a custom apply on Comapnion object on User:
case class Address(code: String, cit: String, county: String)
case class User(id: Int, name: String, address: Address)
object User {
def apply(s: String) : User = s.split(",") match {
case Array(id, name, code, city, county) => User(id.toInt, name, Address(code, city, county) )
}
}
Unapplying on a valid string (in the example valid means the correct number of fields).
"1,Alice,21212,Baltimore,MD" match { case UserExtractor(u) => u }
res0: User = User(1,Alice,Address(21212,Baltimore,MD))
More tests could be added with more custom apply methods.
I'd use a single RegexExtractor :
val lines = List(
"1,alice#alice.com",
"2,bob#bob.com",
"3,carol#carol.com"
)
case class Email(username: String, host: String)
case class User(id: Int, email: Email)
val idAndEMail = """^([^,]+),([^#]+)#(.+)$""".r
and define a function that transforms a line to the an User :
def lineToUserWithMail(line: String) : Option[User] =
idAndEMail.findFirstMatchIn(line) map {
case userWithEmail(id,user,host) => User(id.toInt, Email(user,host) )
}
Applying the function to all lines
lines flatMap lineToUserWithMail
//res29: List[User] = List(User(1,Email(alice,alice.com)), User(2,Email(bob,bob.com)), User(3,Email(carol,carol.com)))
Alternatively you could implement custom Extractors on the case classe by adding an unnapply Method. But for that case it wouldn't be worth the pain.
Here is an example for unapply
class Email(user:String, host:String)
object Email {
def unapply(s: String) : Option[(String,String)] = s.split("#") match {
case Array(user, host) => Some( (user,host) )
case _ => None
}
}
"bob#bob.com" match {
case Email(u,h) => println( s"$u , $h" )
}
// prints bob , bob.com
A word of warning on using Regex to parse CSV-data. It's not as easy as you might think, i would recommend to use a CSV-Reader as http://supercsv.sourceforge.net/ which handles some nasty edge cases out of the box.
in order to implement a ReSTfull APIs stack, I need to convert data extracted from a DB to JSON format. I think that the best way is to extract data from the DB and then convert the row set to JSON using Json.toJson() passing as argument a case class after having defined a implicit serializer (writes).
Here's my case class and companion object:
package deals.db.interf.slick2
import scala.slick.driver.MySQLDriver.simple._
import play.api.libs.json.Json
case class PartnerInfo(
id: Int,
name: String,
site: String,
largeLogo: String,
smallLogo: String,
publicationSite: String
)
object PartnerInfo {
def toCaseClass( ?? ) = { // what type are the arguments to be passed?
PartnerInfo( fx(??) ) // how to transform the input types (slick) to Scala types?
}
// Notice I'm using slick 2.0.0 RC1
class PartnerInfoTable(tag: Tag) extends Table[(Int, String, String, String, String, String)](tag, "PARTNER"){
def id = column[Int]("id")
def name = column[String]("name")
def site = column[String]("site")
def largeLogo = column[String]("large_logo")
def smallLogo = column[String]("small_logo")
def publicationSite = column[String]("publication_site")
def * = (id, name, site, largeLogo, smallLogo, publicationSite)
}
val partnerInfos = TableQuery[PartnerInfoTable]
def qPartnerInfosForPuglisher(publicationSite: String) = {
for (
pi <- partnerInfos if ( pi.publicationSite == publicationSite )
) yield toCaseClass( _ ) // Pass all the table columns to toCaseClass()
}
implicit val partnerInfoWrites = Json.writes[PartnerInfo]
}
What I cannot get is how to implement the toCaseClass() method in order to transform the column types from Slick 2 to Scala types - notice the function fx() in the body of toCaseClass() is only meant to give emphasis to that.
I'm wondering if is it possible to get the Scala type from Slick column type because it is clearly passed in the table definition, but I cannot find how to get it.
Any idea?
I believe the simplest method here would be to map PartnerInfo in the table schema:
class PartnerInfoTable(tag: Tag) extends Table[PartnerInfo](tag, "PARTNER"){
def id = column[Int]("id")
def name = column[String]("name")
def site = column[String]("site")
def largeLogo = column[String]("large_logo")
def smallLogo = column[String]("small_logo")
def publicationSite = column[String]("publication_site")
def * = (id, name, site, largeLogo, smallLogo, publicationSite) <> (PartnerInfo.tupled, PartnerInfo.unapply)
}
val partnerInfos = TableQuery[PartnerInfoTable]
def qPartnerInfosForPuglisher(publicationSite: String) = {
for (
pi <- partnerInfos if ( pi.publicationSite == publicationSite )
) yield pi
}
Otherwise PartnerInfo.tupled should do the trick:
def toCaseClass(pi:(Int, String, String, String, String, String)) = PartnerInfo.tupled(pi)