I have a custom column in my Slick as follow:
class PgACL(tag: Tag) extends Table[ACL](tag, Some(schemaName), "ACL") {
def id = column[UUID]("ID", O.PrimaryKey)
def resourceSpec = column[ResourceSpec]("RESOURCE_SPEC")
def * = (id, resourceSpec) <>(ACL.tupled, ACL.unapply)
}
and the custom class:
case class ResourceSpec (val resourceType: String, val resourceId: String)
And I map them like this:
implicit val ResourceSpecMapper = MappedColumnType.base[ResourceSpec, String](
resourceSpec => resourceSpec.resourceSpecStr,
str => ResourceSpec.fromString(str)
)
I am trying to have a query which filter based on a property of the custom column, but I don't know how I can access to it. For example I want to have:
TableQuery[PgACL].filter(x => x.resourceSpec.resourceType === "XYZ")
But x.resourceSpec returns Rep[ResourceSpec] and I don't know how to get its "resourceType" property.
Any help?
Related
I'm writing a CRUD app using Slick, and I want my update queries to only update a specific set of columns and I use .map().update() for that.
I have a function that returns a tuple of fields that can be updated in my table definition (def writableFields). And I have a funciton that returns a tuple of values to write there extracted from a case class.
It works fine, but it's annoying to create a repo and write the whole update function for every table. I want to create a generic form of this function, and make my table and it's companion object to extend some trait. But I cannot come up with correct type definitions.
Slick expects output of map() to be somehow compatible with the output of update. And I don't know how to make a generic type for tuples.
Is it even possible to accomplish? Or is there an alternative way to limit code duplication? Ideally I want to avoid writing Repos at all and just either instantiate a generic class or call a generic method.
object ProjectsRepo extends BaseRepository[Projects, Project] {
protected val query = lifted.TableQuery[Projects]
def update(id: Long, c: Project): Future[Option[Project]] = {
val q = filterByIdQuery(id).map(_.writableFields)
.update(Projects.mapFormToTable(c))
(db run q).flatMap(
affected =>
if (affected > 0) {
findOneById(id)
} else {
Future(None)
}
)
}
}
class Projects(tag: Tag) extends Table[Project](tag, "projects") with IdentifiableTable[Long] {
val id = column[Long]("id", O.PrimaryKey, O.AutoInc)
val title = column[String]("title")
val slug = column[String]("slug")
val created_at = column[Timestamp]("created_at")
val updated_at = column[Timestamp]("updated_at")
def writableFields =
(
title,
slug
)
def readableFields =
(
id,
created_at,
updated_at
)
def allFields = writableFields ++ readableFields // shapeless
def * = allFields <> (Projects.mapFromTable, (_: Project) => None)
}
object Projects {
def mapFormToTable(c: Project): FormFields =
(
c.title,
c.slug
)
}
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
I'm new to Slick thus I'm not sure whether the problem caused by incorrect usage of implicits or Slick doesn't allow doing what I'm trying to do.
In short I use Slick-pg extension for JSONB support in Postgres. I also use spray-json to deserialize JSONB fields into case classes.
In order to automagically convert columns into objects I wrote generic implicit JsonColumnType that you can see below. It allows me to have any case class for which I defined json formatter to be converted to jsonb field.
On the other hand I want to have alias of JsValue type for the same column so that I can use JSONB-operators.
import com.github.tminglei.slickpg._
import com.github.tminglei.slickpg.json.PgJsonExtensions
import org.bson.types.ObjectId
import slick.ast.BaseTypedType
import slick.jdbc.JdbcType
import spray.json.{JsValue, RootJsonWriter, RootJsonReader}
import scala.reflect.ClassTag
trait MyPostgresDriver extends ExPostgresDriver with PgArraySupport with PgDate2Support with PgRangeSupport with PgHStoreSupport with PgSprayJsonSupport with PgJsonExtensions with PgSearchSupport with PgNetSupport with PgLTreeSupport {
override def pgjson = "jsonb" // jsonb support is in postgres 9.4.0 onward; for 9.3.x use "json"
override val api = MyAPI
private val plainAPI = new API with SprayJsonPlainImplicits
object MyAPI extends API with DateTimeImplicits with JsonImplicits with NetImplicits with LTreeImplicits with RangeImplicits with HStoreImplicits with SearchImplicits with SearchAssistants { //with ArrayImplicits
implicit val ObjectIdColumnType = MappedColumnType.base[ObjectId, Array[Byte]](
{ obj => obj.toByteArray }, { arr => new ObjectId(arr) }
)
implicit def JsonColumnType[T: ClassTag](implicit reader: RootJsonReader[T], writer: RootJsonWriter[T]) = {
val columnType: JdbcType[T] with BaseTypedType[T] = MappedColumnType.base[T, JsValue]({ obj => writer.write(obj) }, { json => reader.read(json) })
columnType
}
}
}
object MyPostgresDriver extends MyPostgresDriver
Here is how my table is defined (minimized version)
case class Article(id : ObjectId, ids : Ids)
case class Ids(doi: Option[String], pmid: Option[Long])
class ArticleRow(tag: Tag) extends Table[Article](tag, "articles") {
def id = column[ObjectId]("id", O.PrimaryKey)
def idsJson = column[JsValue]("ext_ids")
def ids = column[Ids]("ext_ids")
private val fromTuple: ((ObjectId, Ids)) => Article = {
case (id, ids) => Article(id, ids)
}
private val toTuple = (v: Article) => Option((v.id, v.ids))
def * = ProvenShape.proveShapeOf((id, ids) <> (fromTuple, toTuple))(MappedProjection.mappedProjectionShape)
}
private val articles = TableQuery[ArticleRow]
Finally I have function that looks up articles by value of json field
def getArticleByDoi(doi : String): Future[Article] = {
val query = (for (a <- articles if (a.idsJson +>> "doi").asColumnOf[String] === doi) yield a).take(1).result
slickDb.run(query).map { items =>
items.headOption.getOrElse(throw new RuntimeException(s"Article with doi $doi is not found"))
}
}
Sadly I get following exception in runtime
java.lang.ClassCastException: spray.json.JsObject cannot be cast to server.models.db.Ids
The problem is in SpecializedJdbcResultConverter.base where ti.getValue is being called with wrong ti. It should be slick.driver.JdbcTypesComponent$MappedJdbcType but instead it's com.github.tminglei.slickpg.utils.PgCommonJdbcTypes$GenericJdbcType. As result wrong type is passed into my tuple converter.
What makes Slick choose different type for column even though there is explicit definition of projection in table row class ?
Sample project that demonstrates the issue is here.
I have a Model, corresponding Table and a Repository. In my repository, using TableQuery I want to find a model object based on some criteria (a function from model to boolean), which the repository have no control, it is injected as a parameter. E.g.
case class JournalEntryModel(id: Option[Long] = None, isDebit: Boolean, principal: Double)
class JournalEntryTable(tag: Tag) extends Table[JournalEntryModel](tag, "journal_entries") {
def id = column[Long]("id", O.PrimaryKey, O.AutoInc)
def isDebit = column[Boolean]("is_debit")
def principal = column[Double]("principal")
def * = (id.?, isDebit, principal) <>
(JournalEntryModel.tupled, JournalEntryModel.unapply)
}
object journalEntries extends TableQuery(new JournalEntryTable(_))
object Repository {
def find(criteria: JournalEntryModel => Boolean): List[JournalEntryModel] = db.run {
journalEntries.filter(je => criteria(je)).result
} toList
}
val credits = Repository.find(!_.isDebit && _.principal > 500.0)
How do I write a such a filter function ?
I think your question is "How do I write a function literal for JournalEntryModel => Boolean"?
If you want to do it with a literal like you have, you need to define your parameters:
// Parameter list ("model" here) is required. You also need the argument type(s).
// Here, they're inferred from the argument to "find".
val credits = Repository.find(model => !model.isDebit && model.principal > 500.0)
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)