Slick: create query conjunctions/disjunctions dyna

Question

I'm trying to create a typesafe dynamic DSL for a Slick table but not sure how to achieve this.

Users can post filters to the server by sending filters in form/json format, and I need to build a Slick query with all that.

So basically this means transforming a Scala case class representing my filters to a Slick query.

It seems the "predicates" can have 3 different shapes. I've seen the trait CanBeQueryCondition. Can I fold over these different possible shapes?

I've seen the extension methods && and || and know there is something to do with this but I just don't know how to do.

Basically, I have a list of predicates which takes the following types:

(PatientTable) => Column[Option[Boolean]]

or

(PatientTable) => Column[Boolean]

The problem to me is that there is not a single supertype for all the 3 different types that have a CanBeQueryCondition, so I don't really know how do fold the predicates with && as once added to the list these differently shaped predicate takes a very generic type List[(PatientTable) => Column[_ >: Boolean with Option[Boolean]]].

Also, I'm not sure about what can be considered a predicate in Slick. A composable predicate seems to be Column[Boolean], but actually the filter method only accept parameters of type (PatientTable) => Column[Boolean]

Answer 1

"fold" is already the keyword here. Or "reduce" since you don't need a seeding value. buildFilter.reduce(_ && _)

Answer 2

Seems like to want a more general version of this: Dynamic OR filtering - Slick. I think my last example on this page is exactly what you want - it is just what cvogt proposes. I hope this helps.

Answer 3

I was looking for the same thing, and came across this question - the accepted answer was a very heavy inspiration to what I eventually landed on. Details are here.

The only comments I'd make about the accepted answer - TablePredicate[Item, T <: Table[Item]] can just be simplified to TablePredicate[T <: Table[_]] because Item is never used (at least in the sample). LiteralColumn(1) === LiteralColumn(1) can also just be LiteralColumn(Some(true)) (makes the generated queries slightly less awkward) - I'm pretty sure with a little more work, these could be eliminated entirely.

Answer 4

I'm answering my own question with what I've finally built.

Let's define a simple case class and row mapper

case class User(
                    id: String = java.util.UUID.randomUUID().toString,
                    companyScopeId: String,
                    firstName: Option[String] = None,
                    lastName: Option[String] = None
                    ) 


class UserTable(tag: Tag) extends Table[User](tag,"USER") {
  override def id = column[String]("id", O.PrimaryKey)
  def companyScopeId = column[String]("company_scope_id", O.NotNull)
  def firstName = column[Option[String]]("first_name", O.Nullable)
  def lastName = column[Option[String]]("last_name", O.Nullable)

  def * = (id, companyScopeId, firstName, lastName) <>
    (User.tupled,User.unapply)
}

Notion of predicate in Slick

I assume that the notion of "predicate" is what can be put inside TableQuery.filter. But this type is rather complex as it is a function that takes a Table and returns a type that has an implicit CanBeQueryCondition

Unfornunately for me there are 3 different types that have a CanBeQueryCondition and putting them in a list to be folded into a single predicate seems not easy (ie filter is easy to apply, but the && and || operators are hard to apply (as far as I've tried)). But fortunately it seems we can convert easily a Boolean to a Colunm[Boolean] to a Column[Option[Boolean]] with the .? extension method.

So let's define our predicate type:

type TablePredicate[Item, T <: Table[Item]] = T => Column[Option[Boolean]]

Folding a list of predicates (ie using conjunctions/disjunctions, ie composing AND and OR clauses)

Now we only have one type so we can easily fold a list of predicates into a single

  // A predicate that never filter the result
  def matchAll[Item, T <: Table[Item]]: TablePredicate[Item,T] = { table: T => LiteralColumn(1) === LiteralColumn(1) }

  // A predicate that always filter the result
  def matchNone[Item, T <: Table[Item]]: TablePredicate[Item,T] = { table: T => LiteralColumn(1) =!= LiteralColumn(1) }

  def conjunction[Item, T <: Table[Item]](predicates: TraversableOnce[TablePredicate[Item, T]]): TablePredicate[Item,T]  = {
    if ( predicates.isEmpty ) matchAll[Item,T]
    else {
      predicates.reduce { (predicate1, predicate2) => table: T =>
        predicate1(table) && predicate2(table)
      }
    }
  }

  def disjunction[Item, T <: Table[Item]](predicates: TraversableOnce[TablePredicate[Item, T]]): TablePredicate[Item,T] = {
    if ( predicates.isEmpty ) matchNone[Item,T]
    else {
      predicates.reduce { (predicate1, predicate2) => table: T =>
        predicate1(table) || predicate2(table)
      }
    }
  }

---

The dynamic filtering case class

From these predicate primitives we can start creating our dynamic, composable and typesafe query DSL based on a case class.

case class UserFilters(
                           companyScopeIds: Option[Set[String]] = None,
                           firstNames: Option[Set[String]] = None,
                           lastNames: Option[Set[String]] = None
                           ) {

  type UserPredicate = TablePredicate[User,UserTable]


  def withFirstNames(firstNames: Set[String]): UserFilters = this.copy(firstNames = Some(firstNames))
  def withFirstNames(firstNames: String*): UserFilters = withFirstNames(firstNames.toSet)

  def withLastNames(lastNames: Set[String]): UserFilters = this.copy(lastNames = Some(lastNames))
  def withLastNames(lastNames: String*): UserFilters = withLastNames(lastNames.toSet)

  def withCompanyScopeIds(companyScopeIds: Set[String]): UserFilters = this.copy(companyScopeIds = Some(companyScopeIds))
  def withCompanyScopeIds(companyScopeIds: String*): UserFilters = withCompanyScopeIds(companyScopeIds.toSet)


  private def filterByFirstNames(firstNames: Set[String]): UserPredicate = { table: UserTable => table.firstName inSet firstNames }
  private def filterByLastNames(lastNames: Set[String]): UserPredicate = { table: UserTable => table.lastName inSet lastNames }
  private def filterByCompanyScopeIds(companyScopeIds: Set[String]): UserPredicate = { table: UserTable => (table.companyScopeId.? inSet companyScopeIds) }


  def predicate: UserPredicate = {
    // Build the list of predicate options (because filters are actually optional)
    val optionalPredicates: List[Option[UserPredicate]] = List(
      firstNames.map(filterByFirstNames(_)),
      lastNames.map(filterByLastNames(_)),
      companyScopeIds.map(filterByCompanyScopeIds(_))
    )
    // Filter the list to remove None's
    val predicates: List[UserPredicate] = optionalPredicates.flatten
    // By default, create a conjunction (AND) of the predicates of the represented by this case class
    conjunction[User,UserTable](predicates)
  }

}

Notice the usage of .? for the companyScopeId field which permits to fit a non-optional column to our definition of a Slick predicate

Using the DSL

val Users = TableQuery(new UserTable(_))

val filter1 = UserFilters().withLastNames("lorber","silhol").withFirstName("robert")
val filter2 = UserFilters().withFirstName("sebastien")

val filter = disjunction[User,UserTable](Set(filter1.predicate,filter2.predicate))

val users = Users.filter(filter.predicate).list

// results in 
// ( last_name in ("lorber","silhol") AND first_name in ("robert") ) 
// OR 
// ( first_name in ("sebastien") )

Conclusion

This is far from being perfect but is a first draft and at least can give you some inspiration :) I would like Slick to make it easier to build such things that are very common in other query DSL (like Hibernate/JPA Criteria API)

See also this Gist for up-to-date solutions