[2.0-scala] Migrating from Anorm in 1.x to 2.x
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Matt Raible
May 30, 2012, 12:00:50 PM5/30/12
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Hello all,
I'm trying to migrate my Play 1.2.4 (with Scala) app to Play 2 Scala. The first issue I've run into is pagination. The only good example I've found is in the computer-database project. Is this the recommended solution or does someone have a simpler example (like the prevNext method in 1.x)?
My second issue is how to create the same method signature I had in one of my models from 1.x. In my Workout.scala class, I had the following method:
object Workout extends Magic[Workout] {
def byIdWithAthleteAndComments(id: Long): Option[(Workout, Athlete, List[Comment])] =
SQL(
"""
select * from Workout w
join Athlete a on w.athleteId = a.id
left join Comment c on c.workoutId = w.id
where w.id = {id}
"""
).on("id" -> id).as(Workout ~< Athlete ~< Workout.spanM(Comment) ^^ flatten ?)
}In 2.x, I'm having issues getting this same method signature. I've gotten close, but the Comment is singular instead of a List.
val withAthleteAndComments = withAthlete ~ Comment.simple map { case workout~comments => (workout, comments) } def byIdWithAthleteAndComments(id: Long): List[((Workout, Athlete), Comment)] = DB.withConnection { implicit connection => SQL( """ select * from Workout w join Athlete a on w.athleteId = a.id left join Comment c on c.workoutId = w.id where w.id = {id} """ ).on('id -> id).as(Workout.withAthleteAndComments *) }You can find the full classes in the following gist.https://gist.github.com/2837139Thanks in advance for any advice.Cheers,Matt
Julien Tournay
May 30, 2012, 12:06:50 PM5/30/12
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Hi
spanM was removed, you need to group results using groupBy (standard scala List api).
Here's an example extracted from one of my models (a Project has a List[Author]):
val simple = {val rs =get[String]("project.description") ~get[Int]("project.score") ~get[Boolean]("project.validated") ~get[String]("project.image") ~get[Option[String]]("project.url") ~get[String]("project.repo") ~Author.simple).map {case id ~ description ~ name ~ score ~ validated ~ image ~ url ~ repo ~ author=> (id, description, name, score, validated, image, url, repo, author)} *;rs.map(r =>r.groupBy(_._1).flatMap{ case (k, ps) =>ps.headOption.map{ p =>val (id, description, name, score, validated, image, url, repo, author) = pProject(id, name, description, repo, score, validated, image, ps.map(_._9), url)}}.toList)}jto.
Julien Tournay
May 30, 2012, 12:09:29 PM5/30/12
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It could be slightly easier using flatten:
val rs =get[String]("project.description") ~get[Int]("project.score") ~get[Boolean]("project.validated") ~get[String]("project.image") ~get[Option[String]]("project.url") ~get[String]("project.repo") ~Author.simple).map {
flatten} *;
Guillaume Bort
May 30, 2012, 12:26:24 PM5/30/12
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It should be something like:
val withAthleteAndComments = {
(Workout.withAthlete ~ Comment.simple *) map {
case all => all.groupBy(_._1).headOption.map {
case (workoutWithAthlete, comments) => (workout, athlete,
comment.map(_._2))
}
}
}
That will get you a Option[((Workout,Athlete),List[Comment])]
Btw the type is pretty complicated, it should be simpler by using a
case class instead, something like:
XXXX(workout: Workout, athlete: Athlete, comments: List[Comment])
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Guillaume Bort, http://guillaume.bort.fr
val withAthleteAndComments = {
(Workout.withAthlete ~ Comment.simple *) map {
case all => all.groupBy(_._1).headOption.map {
case (workoutWithAthlete, comments) => (workout, athlete,
comment.map(_._2))
}
}
}
That will get you a Option[((Workout,Athlete),List[Comment])]
Btw the type is pretty complicated, it should be simpler by using a
case class instead, something like:
XXXX(workout: Workout, athlete: Athlete, comments: List[Comment])
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Matt Raible
May 31, 2012, 8:48:16 AM5/31/12
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On Wednesday, May 30, 2012 10:26:24 AM UTC-6, Guillaume Bort wrote:
It should be something like:
val withAthleteAndComments = {
(Workout.withAthlete ~ Comment.simple *) map {
case all => all.groupBy(_._1).headOption.map {
case (workoutWithAthlete, comments) => (workout, athlete,
comment.map(_._2))
}
}
}
That will get you a Option[((Workout,Athlete),List[Comment])]
If I try that, I get errors about the lowercase variables:
error: not found: value workout
case (workoutWithAthlete, comments) => (workout, athlete, comment.map(_._2))
Changing them to uppercase seems to help, but not much:
val withAthleteAndComments = {
(withAthlete ~ Comment.simple *) map {
case all => all.groupBy(_._1).headOption.map {
case (workoutWithAthlete, comments) => (Workout, Athlete, Comment.map(_._2))
}
}
}
error: value map is not a member of object models.Comment
case (workoutWithAthlete, comments) => (Workout, Athlete, Comment.map(_._2))
Thanks,
Matt
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Guillaume Bort
May 31, 2012, 10:38:15 AM5/31/12
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Oh yes, of course this is wrong. It should be something like:
case (workoutWithAthlete, comments) => (workoutWithAthlete, comment.map(_._2))
Btw, to explain what I'm trying to do here:
1) You already have a RowParser[(Workout,Athlete)] called
Workout.withAthlete that is able to extract a tuple (Workout,Athlete)
from a ResultSet row.
2) You already have a RowParser[Comment] called Comment.simple that is
able to extract a Commet from a ResultSet row.
3) Let's compose both to have a RowParser[(Workout,Athlete)~Comment]:
----
Workout.withAthlete ~ Comment.simple
----
4) Now, let's use this to construct a
ResultSetParser[List[(Workout,Athlete)~Comment]]. This is a parser
able to give me a List[(Workout,Athlete)~Comment] from a ResultSet:
----
(Workout.withAthlete ~ Comment.simple) *
----
This parser will give you something like:
----
List(
(myWorkout1,myAthlete1)~comment1,
(myWorkout1,myAthlete1)~comment2,
(myWorkout1,myAthlete1)~comment3
)
----
That is a simple representation of your JDBC ResultSet
5) Let's transform this
ResultSetParser[List[(Workout,Athlete)~Comment]] to a
ResultSetParser[Option[((Workout,Athlete),List[Comment]]] because this
is what you want.
We use the `map` operation to do that (it transforms a
ResultSetParser[A] to a ResultSetParser[B] given a A => B function).
We want to transform:
----
List(
(myWorkout1,myAthlete1)~comment1,
(myWorkout1,myAthlete1)~comment2,
(myWorkout1,myAthlete1)~comment3
)
----
to
----
Some( ( (myWorkout1,myAthlete1), List(comment1,comment2comment3) ) )
----
And
----
List()
----
to
----
None
----
Let's start by grouping by the first item:
----
items.groupBy(_._1)
----
So we get:
----
Map(
(myWorkout1,myAthlete1),
List(
(myWorkout1,myAthlete1)~comment1,
(myWorkout1,myAthlete1)~comment2,
(myWorkout1,myAthlete1)~comment3
)
)
----
Basically we get a Map with a single key if the query returned any
result, or an empty Map if the query returned no results.
Let's transform it to an Option:
----
items.groupBy(_._1).headOption
----
So we get:
----
Some(
(
(myWorkout1,myAthlete1),
List(
(myWorkout1,myAthlete1)~comment1,
(myWorkout1,myAthlete1)~comment2,
(myWorkout1,myAthlete1)~comment3
)
)
)
----
(or None if the Map was empty)
Now, we just want to filter out the repeated (myWorkout1,myAthlete1)
in the List to keep the comment only:
----
items.groupBy(_._1).headOption.map {
case (workoutWithAthlete, list) => (workoutWithAthlete, list.map(_._2))
}
----
And we finally get:
----
Some(
(
(myWorkout1,myAthlete1),
List(
comment1,
comment2,
comment3
)
)
)
----
Or None if the initial list was empty.
Finally, here is the whole stuff altogether that you can assign to a
value and reuse as a generic parser to parse the result of several
different queries:
----
val withAthleteAndComments = {
(Workout.withAthlete ~ Comment.simple *) map { items =>
items.groupBy(_._1).headOption.map {
case (workoutWithAthlete, list) => (workoutWithAthlete, list.map(_._2))
}
}
}
----
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case (workoutWithAthlete, comments) => (workoutWithAthlete, comment.map(_._2))
Btw, to explain what I'm trying to do here:
1) You already have a RowParser[(Workout,Athlete)] called
Workout.withAthlete that is able to extract a tuple (Workout,Athlete)
from a ResultSet row.
2) You already have a RowParser[Comment] called Comment.simple that is
able to extract a Commet from a ResultSet row.
3) Let's compose both to have a RowParser[(Workout,Athlete)~Comment]:
----
Workout.withAthlete ~ Comment.simple
----
4) Now, let's use this to construct a
ResultSetParser[List[(Workout,Athlete)~Comment]]. This is a parser
able to give me a List[(Workout,Athlete)~Comment] from a ResultSet:
----
(Workout.withAthlete ~ Comment.simple) *
----
This parser will give you something like:
----
List(
(myWorkout1,myAthlete1)~comment1,
(myWorkout1,myAthlete1)~comment2,
(myWorkout1,myAthlete1)~comment3
)
----
That is a simple representation of your JDBC ResultSet
5) Let's transform this
ResultSetParser[List[(Workout,Athlete)~Comment]] to a
ResultSetParser[Option[((Workout,Athlete),List[Comment]]] because this
is what you want.
We use the `map` operation to do that (it transforms a
ResultSetParser[A] to a ResultSetParser[B] given a A => B function).
We want to transform:
----
List(
(myWorkout1,myAthlete1)~comment1,
(myWorkout1,myAthlete1)~comment2,
(myWorkout1,myAthlete1)~comment3
)
----
to
----
Some( ( (myWorkout1,myAthlete1), List(comment1,comment2comment3) ) )
----
And
----
List()
----
to
----
None
----
Let's start by grouping by the first item:
----
items.groupBy(_._1)
----
So we get:
----
Map(
(myWorkout1,myAthlete1),
List(
(myWorkout1,myAthlete1)~comment1,
(myWorkout1,myAthlete1)~comment2,
(myWorkout1,myAthlete1)~comment3
)
)
----
Basically we get a Map with a single key if the query returned any
result, or an empty Map if the query returned no results.
Let's transform it to an Option:
----
items.groupBy(_._1).headOption
----
So we get:
----
Some(
(
(myWorkout1,myAthlete1),
List(
(myWorkout1,myAthlete1)~comment1,
(myWorkout1,myAthlete1)~comment2,
(myWorkout1,myAthlete1)~comment3
)
)
)
----
(or None if the Map was empty)
Now, we just want to filter out the repeated (myWorkout1,myAthlete1)
in the List to keep the comment only:
----
items.groupBy(_._1).headOption.map {
case (workoutWithAthlete, list) => (workoutWithAthlete, list.map(_._2))
}
----
And we finally get:
----
Some(
(
(myWorkout1,myAthlete1),
List(
comment1,
comment2,
comment3
)
)
)
----
Or None if the initial list was empty.
Finally, here is the whole stuff altogether that you can assign to a
value and reuse as a generic parser to parse the result of several
different queries:
----
val withAthleteAndComments = {
(Workout.withAthlete ~ Comment.simple *) map { items =>
items.groupBy(_._1).headOption.map {
case (workoutWithAthlete, list) => (workoutWithAthlete, list.map(_._2))
}
}
}
----
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>>
>>
>>
>> --
>> Guillaume Bort, http://guillaume.bort.fr
>
>> > http://groups.google.com/group/play-framework?hl=en.
>>
>>
>>
>> --
>> Guillaume Bort, http://guillaume.bort.fr
>
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Matt Raible
Jun 1, 2012, 10:02:59 AM6/1/12
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Thanks Guillaume, I appreciate the detailed response.
Now I'm trying to get the following method to work with this parser:
def allWithAthleteAndComments: List[((Workout, Athlete), List[Comment])] = DB.withConnection {
order by w.postedAt desc
"""
).as(Workout.withAthleteAndComments).toList
}
This compiles, but I'm not sure it's correct. I have the following test:
"Global" should {
"load seed data into DB" in {
running(FakeApplication(additionalConfiguration = inMemoryDatabase())) {
InitialData.insert()
Athlete.count() must be_==(2)
Workout.count() must be_==(3)
Comment.count() must be_==(3)
Athlete.connect("mra...@gmail.com", "beer") should not be (None)
Athlete.connect("trishm...@gmail.com", "whiskey") should not be (None)
Athlete.connect("trishm...@gmail.com", "badpassword") must be_==(None)
Athlete.connect("fr...@gmail.com", "secret") must be_==(None)
val allWorkoutsWithAthleteAndComments = Workout.allWithAthleteAndComments
allWorkoutsWithAthleteAndComments must be_==(3)
}
}
}
Running it results in the following error:
[info] Global should
[error] ! load seed data into DB
[error] RuntimeException: UnexpectedNullableFound(COMMENT.ID) (Predef.scala:66)
[error] anorm.Sql$.as(Anorm.scala:513)
[error] anorm.Sql$class.as(Anorm.scala:433)
[error] anorm.SqlQuery.as(Anorm.scala:459)
[error] models.Workout$$anonfun$allWithAthleteAndComments$1.apply(Workout.scala:83)
[error] models.Workout$$anonfun$allWithAthleteAndComments$1.apply(Workout.scala:75)
[error] play.api.db.DBApi$class.withConnection(DB.scala:77)
[error] play.api.db.BoneCPApi.withConnection(DB.scala:264)
[error] play.api.db.DB$$anonfun$withConnection$3.apply(DB.scala:156)
[error] play.api.db.DB$$anonfun$withConnection$3.apply(DB.scala:156)
[error] play.api.db.DB$.withConnection(DB.scala:156)
[error] models.Workout$.allWithAthleteAndComments(Workout.scala:74)
[error] UnitTests$$anonfun$3$$anonfun$apply$82$$anonfun$apply$83.apply(UnitTests.scala:110)
[error] UnitTests$$anonfun$3$$anonfun$apply$82$$anonfun$apply$83.apply(UnitTests.scala:97)
[error] play.api.test.Helpers$.running(Helpers.scala:33)
[error] UnitTests$$anonfun$3$$anonfun$apply$82.apply(UnitTests.scala:97)
[error] UnitTests$$anonfun$3$$anonfun$apply$82.apply(UnitTests.scala:97)
Any advice is appreciated.
Thanks,
Matt
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>>
>> --
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>
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Guillaume Bort
Jun 1, 2012, 12:28:37 PM6/1/12
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Well, by using a "left join" for the comments, you should expect null
values there (because it will select Workout and Athlete without any
comments). So you need to handle Comment parsing as optional:
Workout.withAthlete ~ (Comment.simple?)
Then you will have to manage Option[Comment] values instead. It is
really easy to transform a List[Option[Comment]] into a List[Comment]
by filtering undefined value using `flatten`.
You should end with something like this:
val withAthleteAndComments = {
(Workout.withAthlete ~ (Comment.simple?) *) map { items =>
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values there (because it will select Workout and Athlete without any
comments). So you need to handle Comment parsing as optional:
Workout.withAthlete ~ (Comment.simple?)
Then you will have to manage Option[Comment] values instead. It is
really easy to transform a List[Option[Comment]] into a List[Comment]
by filtering undefined value using `flatten`.
You should end with something like this:
val withAthleteAndComments = {
(Workout.withAthlete ~ (Comment.simple?) *) map { items =>
items.groupBy(_._1).headOption.map {
case (workoutWithAthlete, list) => (workoutWithAthlete,
list.map(_._2).flatten)
case (workoutWithAthlete, list) => (workoutWithAthlete,
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>> >>
>> >>
>> >>
>> >> --
>> >> Guillaume Bort, http://guillaume.bort.fr
>> >
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>> >>
>> >>
>> >>
>> >> --
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>> >
>> > --
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>>
>>
>> --
>> Guillaume Bort, http://guillaume.bort.fr
>
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>>
>>
>>
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>
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Matt Raible
Jun 4, 2012, 9:33:36 AM6/4/12
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I still get the same error after this change:
lazy val withAthleteAndComments = {
(Workout.withAthlete ~ (Comment.simple?) *) map {
items =>
items.groupBy(_._1).headOption.map {
case (workoutWithAthlete, list) => (workoutWithAthlete, list.map(_._2).flatten)
}
}
}
def allWithAthleteAndComments: List[((Workout, Athlete), List[Comment])] = DB.withConnection {
implicit connection =>
SQL(
"""
select * from Workout w
join Athlete a on w.athleteId = a.id
left join Comment c on c.workoutId = w.id
order by w.postedAt desc
"""
).as(Workout.withAthleteAndComments).toList
}
[info] Global should
[error] ! load seed data into DB
[error] RuntimeException: UnexpectedNullableFound(comment.id) (Predef.scala:66)
[error] anorm.Sql$.as(Anorm.scala:513)
[error] anorm.Sql$class.as(Anorm.scala:433)
[error] anorm.SqlQuery.as(Anorm.scala:459)
[error] models.Workout$$anonfun$allWithAthleteAndComments$1.apply(Workout.scala:83)
[error] models.Workout$$anonfun$allWithAthleteAndComments$1.apply(Workout.scala:75)
[error] play.api.db.DBApi$class.withConnection(DB.scala:77)
[error] play.api.db.BoneCPApi.withConnection(DB.scala:264)
[error] play.api.db.DB$$anonfun$withConnection$3.apply(DB.scala:156)
[error] play.api.db.DB$$anonfun$withConnection$3.apply(DB.scala:156)
[error] play.api.db.DB$.withConnection(DB.scala:156)
> Athlete.connect("mraible@gmail.com", "beer") should not be (None)
> Athlete.connect("trishmcginity@gmail.com", "whiskey") should not be
> (None)
> Athlete.connect("trishmcginity@gmail.com", "badpassword") must
> be_==(None)
> Athlete.connect("fred@gmail.com", "secret") must be_==(None)
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>> >>
>> >>
>> >>
>> >> --
>> >> Guillaume Bort, http://guillaume.bort.fr
>> >
>> > --
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>>
>>
>>
>> --
>> Guillaume Bort, http://guillaume.bort.fr
>
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Guillaume Bort
Jun 4, 2012, 1:38:25 PM6/4/12
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Can you share your database creation script? I don't see why it would fail this way.
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Matt Raible
Jun 4, 2012, 3:07:40 PM6/4/12
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Here's my evolution to create the table:
# --- !Ups
CREATE TABLE Comment (
id SERIAL PRIMARY KEY,
author varchar(255) NOT NULL,
content text NOT NULL,
postedAt timestamp NOT NULL,
workoutId bigint NOT NULL REFERENCES Workout ON DELETE CASCADE
);
# --- !Downs
DROP TABLE Comment;
And my Comment class:
package models
import anorm._
import anorm.SqlParser._
import java.util.Date
import play.api.db.DB
import play.api.Play.current
case class Comment(
id: Pk[Long],
author: String, content: String, postedAt: Date, workoutId: Long
)
object Comment {
def apply(workoutId: Long, author: String, content: String) = {
new Comment(NotAssigned, author, content, new Date(), workoutId)
}
val simple = {
get[Pk[Long]]("comment.id") ~
get[String]("comment.author") ~
get[String]("comment.content") ~
get[Long]("comment.postedAt") ~
get[Long]("comment.workoutId") map {
case id~author~content~postedAt~workoutId =>
Comment(id, author, content, new Date(postedAt), workoutId)
}
}
def count(): Long = {
DB.withConnection {
implicit connection =>
SQL("select count(*) from comment").as(scalar[Long].single)
}
}
def create(comment: Comment) = {
DB.withConnection {
implicit connection =>
SQL("insert into comment (author, content, postedAt, workoutId) values " +
"({author}, {content}, {postedAt}, {workoutId})").on(
'author -> comment.author,
'content -> comment.content,
'postedAt -> new Date(),
'workoutId -> comment.workoutId
).executeInsert()
}
}
}
Matt Raible
Jun 5, 2012, 1:58:19 AM6/5/12
to play-fr...@googlegroups.com
I was able to solve this using the Yabe project that's been updated for Play 2:
Since I used Play 1's Yabe example to learn, this was a great help in seeing how to do the same thing in Play 2.
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