Merge pull request #590 from 47degrees/fix-traverse

Replace implicit traverse behavior with explicit batching

README.md

@@ -21,16 +21,16 @@ A library for Simple & Efficient data access in Scala and Scala.js
 
 Add the following dependency to your project's build file.
 
-For Scala 2.11.x and 2.12.x:
+For Scala 2.12.x through 3.x:
 
 ```scala
-"com.47deg" %% "fetch" % "2.1.1"
+"com.47deg" %% "fetch" % "3.0.0"
 ```
 
-Or, if using Scala.js (0.6.x):
+Or, if using Scala.js (1.8.x):
 
 ```scala
-"com.47deg" %%% "fetch" % "2.1.1"
+"com.47deg" %%% "fetch" % "3.0.0"
 ```
 
 
@@ -105,20 +105,15 @@ def fetchString[F[_] : Async](n: Int): Fetch[F, String] =
 
 ## Creating a runtime
 
-Since `Fetch` relies on `Concurrent` from the `cats-effect` library, we'll need a runtime for executing our effects. We'll be using `IO` from `cats-effect` to run fetches, but you can use any type that has a `Concurrent` instance.
+Since we'll use `IO` from the `cats-effect` library to execute our fetches, we'll need an `IORuntime` for executing our `IO` instances.
 
-For executing `IO`, we need a `ContextShift[IO]` used for running `IO` instances and a `Timer[IO]` that is used for scheduling. Let's go ahead and create them. We'll use a `java.util.concurrent.ScheduledThreadPoolExecutor` with a couple of threads to run our fetches.
-
-```scala
-import java.util.concurrent._
-import scala.concurrent.ExecutionContext
-
-val executor = new ScheduledThreadPoolExecutor(4)
-val executionContext: ExecutionContext = ExecutionContext.fromExecutor(executor)
-
-import cats.effect.unsafe.implicits.global
+```scala mdoc:silent
+import cats.effect.unsafe.implicits.global //Gives us an IORuntime in places it is normally not provided
 ```
 
+Normally, in your applications, this is provided by `IOApp`, and you should not need to import this except in limited scenarios such as test environments that do not have Cats Effect integration.
+For more information, and particularly on why you would usually not want to make one of these yourself, [see this post by Daniel Spiewak](https://github.com/typelevel/cats-effect/discussions/1562#discussioncomment-254838)
+
 ## Creating and running a fetch
 
 Now that we can convert `Int` values to `Fetch[F, String]`, let's try creating a fetch.

docs/README.md

@@ -13,13 +13,13 @@ A library for Simple & Efficient data access in Scala and Scala.js
 
 Add the following dependency to your project's build file.
 
-For Scala 2.11.x and 2.12.x:
+For Scala 2.12.x through 3.x:
 
 ```scala
 "com.47deg" %% "fetch" % "@VERSION@"
 ```
 
-Or, if using Scala.js (0.6.x):
+Or, if using Scala.js (1.8.x):
 
 ```scala
 "com.47deg" %%% "fetch" % "@VERSION@"
@@ -106,20 +106,15 @@ def fetchString[F[_] : Async](n: Int): Fetch[F, String] =
 
 ## Creating a runtime
 
-Since `Fetch` relies on `Concurrent` from the `cats-effect` library, we'll need a runtime for executing our effects. We'll be using `IO` from `cats-effect` to run fetches, but you can use any type that has a `Concurrent` instance.
-
-For executing `IO`, we need a `ContextShift[IO]` used for running `IO` instances and a `Timer[IO]` that is used for scheduling. Let's go ahead and create them. We'll use a `java.util.concurrent.ScheduledThreadPoolExecutor` with a couple of threads to run our fetches.
+Since we'll use `IO` from the `cats-effect` library to execute our fetches, we'll need an `IORuntime` for executing our `IO` instances.
 
 ```scala mdoc:silent
-import java.util.concurrent._
-import scala.concurrent.ExecutionContext
-
-val executor = new ScheduledThreadPoolExecutor(4)
-val executionContext: ExecutionContext = ExecutionContext.fromExecutor(executor)
-
-import cats.effect.unsafe.implicits.global
+import cats.effect.unsafe.implicits.global //Gives us an IORuntime in places it is normally not provided
 ```
 
+Normally, in your applications, this is provided by `IOApp`, and you should not need to import this except in limited scenarios such as test environments that do not have Cats Effect integration.
+For more information, and particularly on why you would usually not want to make one of these yourself, [see this post by Daniel Spiewak](https://github.com/typelevel/cats-effect/discussions/1562#discussioncomment-254838)
+
 ## Creating and running a fetch
 
 Now that we can convert `Int` values to `Fetch[F, String]`, let's try creating a fetch.
@@ -282,10 +277,6 @@ runFetchFourTimesSharedCache.unsafeRunTimed(5.seconds)
 
 As you can see above, the cache will now work between calls and can be used to deduplicate requests over a period of time.
 Note that this does not support any kind of automatic cache invalidation, so you will need to keep track of which values you want to re-fetch if you plan on sharing the cache.
-
-```scala mdoc:invisible
-executor.shutdownNow()
-```
 ---
 
 For more in-depth information, take a look at our [documentation](https://47degrees.github.io/fetch/docs.html).

fetch-examples/src/test/scala/DoobieExample.scala

@@ -31,6 +31,7 @@ import scala.concurrent.ExecutionContext
 import java.util.concurrent.Executors
 
 import fetch._
+import fetch.syntax._
 
 object DatabaseExample {
   case class AuthorId(id: Int)
@@ -150,7 +151,7 @@ class DoobieExample extends AnyWordSpec with Matchers with BeforeAndAfterAll {
 
   "We can fetch multiple authors from the DB in parallel" in {
     def fetch[F[_]: Async]: Fetch[F, List[Author]] =
-      List(1, 2).traverse(Authors.fetchAuthor[F])
+      List(1, 2).map(Authors.fetchAuthor[F]).batchAll
 
     val io: IO[(Log, List[Author])] = Fetch.runLog[IO](fetch)
 

fetch-examples/src/test/scala/GithubExample.scala

@@ -17,6 +17,7 @@
 import cats.effect._
 import cats.syntax.all._
 import fetch.{Data, DataSource, Fetch}
+import fetch.syntax._
 import io.circe._
 import io.circe.generic.semiauto._
 import org.http4s._
@@ -204,7 +205,7 @@ class GithubExample extends AnyWordSpec with Matchers {
   def fetchOrg[F[_]: Async](org: String) =
     for {
       repos    <- orgRepos(org)
-      projects <- repos.traverse(fetchProject[F])
+      projects <- repos.batchAllWith(fetchProject[F])
     } yield projects
 
   def fetchOrgStars[F[_]: Async](org: String): Fetch[F, Int] =

fetch-examples/src/test/scala/GraphQLExample.scala

@@ -23,6 +23,7 @@ import atto._, Atto._
 import cats.syntax.all._
 import cats.data.NonEmptyList
 import cats.effect._
+import fetch.syntax._
 import scala.concurrent.ExecutionContext
 import scala.concurrent.duration._
 
@@ -199,14 +200,15 @@ class GraphQLExample extends AnyWordSpec with Matchers {
       case RepositoriesQuery(n, name, Some(_), Some(_)) =>
         for {
           repos <- Repos.fetch(org)
-          projects <-
-            repos
-              .take(n)
-              .traverse(repo =>
-                (Languages.fetch(repo), Collaborators.fetch(repo)).mapN { case (ls, cs) =>
-                  Project(name >> Some(repo.name), ls, cs)
-                }
-              )
+          projects <- {
+            val nRepos = repos.take(n)
+            val fetches = nRepos.map { repo =>
+              (Languages.fetch(repo), Collaborators.fetch(repo)).mapN { case (ls, cs) =>
+                Project(name >> Some(repo.name), ls, cs)
+              }
+            }
+            fetches.batchAll
+          }
         } yield projects
 
       case RepositoriesQuery(n, name, None, None) =>
@@ -215,16 +217,22 @@ class GraphQLExample extends AnyWordSpec with Matchers {
       case RepositoriesQuery(n, name, Some(_), None) =>
         for {
           repos <- Repos.fetch(org)
-          projects <- repos.traverse { r =>
-            Languages.fetch(r).map(ls => Project(name >> Some(r.name), ls, List()))
+          projects <- {
+            val fetches = repos.map { r =>
+              Languages.fetch(r).map(ls => Project(name >> Some(r.name), ls, List()))
+            }
+            fetches.batchAll
           }
         } yield projects
 
       case RepositoriesQuery(n, name, None, Some(_)) =>
         for {
           repos <- Repos.fetch(org)
-          projects <- repos.traverse { r =>
-            Collaborators.fetch(r).map(cs => Project(name >> Some(r.name), List(), cs))
+          projects <- {
+            val fetches = repos.map { r =>
+              Collaborators.fetch(r).map(cs => Project(name >> Some(r.name), List(), cs))
+            }
+            fetches.batchAll
           }
         } yield projects
     }

fetch-examples/src/test/scala/Http4sExample.scala

@@ -34,6 +34,7 @@ import org.scalatest.wordspec.AnyWordSpec
 import java.util.concurrent._
 
 import fetch._
+import fetch.syntax._
 
 object HttpExample {
   case class UserId(id: Int)
@@ -114,7 +115,7 @@ object HttpExample {
     fetchUserById(UserId(id))
 
   def fetchManyUsers[F[_]: Async](ids: List[Int]): Fetch[F, List[User]] =
-    ids.traverse(i => fetchUserById(UserId(i)))
+    ids.map(i => fetchUserById(UserId(i))).batchAll
 
   def fetchPosts[F[_]: Async](user: User): Fetch[F, (User, List[Post])] =
     fetchPostsForUser(user.id).map(posts => (user, posts))
@@ -149,7 +150,7 @@ class Http4sExample extends AnyWordSpec with Matchers {
     def fetch[F[_]: Async]: Fetch[F, List[(User, List[Post])]] =
       for {
         users          <- fetchManyUsers(List(1, 2))
-        usersWithPosts <- users.traverse(fetchPosts[F])
+        usersWithPosts <- users.map(fetchPosts[F]).batchAll
       } yield usersWithPosts
 
     val io = Fetch.runLog[IO](fetch)

fetch/src/main/scala/fetch.scala

@@ -303,7 +303,7 @@ object `package` {
           }
         } yield result)
 
-      override def product[A, B](fa: Fetch[F, A], fb: Fetch[F, B]): Fetch[F, (A, B)] =
+      override def product[A, B](fa: Fetch[F, A], fb: Fetch[F, B]): Fetch[F, (A, B)] = {
         Unfetch[F, (A, B)](for {
           fab <- (fa.run, fb.run).tupled
           result = fab match {
@@ -321,6 +321,7 @@ object `package` {
               Throw[F, (A, B)](e)
           }
         } yield result)
+      }
 
       override def productR[A, B](fa: Fetch[F, A])(fb: Fetch[F, B]): Fetch[F, B] =
         Unfetch[F, B](for {
@@ -360,6 +361,26 @@ object `package` {
     def pure[F[_]: Applicative, A](a: A): Fetch[F, A] =
       Unfetch(Applicative[F].pure(Done(a)))
 
+    /**
+     * Given a number of fetches, returns all of the results in a `List`. In the event that multiple
+     * fetches are made to the same data source, this will attempt to batch them together.
+     *
+     * This should be used in code that previously relied on the auto-batching behavior of calling
+     * `traverse` on lists of `Fetch` values.
+     */
+    def batchAll[F[_]: Monad, A](fetches: Fetch[F, A]*): Fetch[F, List[A]] = {
+      fetches.toList.toNel
+        .map { nes =>
+          nes
+            .map(_.map(Chain.one(_)))
+            .reduceLeft { (fa, fb) =>
+              fetchM[F].map2(fa, fb)((a, b) => a ++ b)
+            }
+            .map(_.toList)
+        }
+        .getOrElse(Fetch.pure[F, List[A]](List.empty))
+    }
+
     def exception[F[_]: Applicative, A](e: Log => FetchException): Fetch[F, A] =
       Unfetch(Applicative[F].pure(Throw[F, A](e)))
 

fetch/src/main/scala/syntax.scala

@@ -18,6 +18,7 @@ package fetch
 
 import cats._
 import cats.effect._
+import fetch.Fetch
 
 object syntax {
 
@@ -38,4 +39,14 @@ object syntax {
     def fetch[F[_]: Concurrent]: Fetch[F, B] =
       Fetch.error[F, B](a)
   }
+
+  implicit class FetchSeqBatchSyntax[F[_]: Monad, A](fetches: Seq[Fetch[F, A]]) {
+
+    def batchAll: Fetch[F, List[A]] = Fetch.batchAll(fetches: _*)
+  }
+
+  implicit class SeqSyntax[A](val as: Seq[A]) extends AnyVal {
+
+    def batchAllWith[F[_]: Monad, B](f: A => Fetch[F, B]) = Fetch.batchAll(as.map(f): _*)
+  }
 }

fetch/src/test/scala/FetchBatchingTests.scala

@@ -22,6 +22,7 @@ import cats.instances.list._
 import cats.syntax.all._
 import cats.effect._
 import fetch._
+import fetch.syntax._
 
 import java.util.concurrent.atomic.AtomicInteger
 import scala.concurrent.duration.{DurationInt, FiniteDuration}
@@ -152,7 +153,7 @@ class FetchBatchingTests extends FetchSpec {
 
   "A large fetch to a datasource with a maximum batch size is split and executed in sequence" in {
     def fetch[F[_]: Concurrent]: Fetch[F, List[Int]] =
-      List.range(1, 6).traverse(fetchBatchedDataSeq[F])
+      List.range(1, 6).map(fetchBatchedDataSeq[F]).batchAll
 
     val io = Fetch.runLog[IO](fetch)
 
@@ -166,7 +167,7 @@ class FetchBatchingTests extends FetchSpec {
 
   "A large fetch to a datasource with a maximum batch size is split and executed in parallel" in {
     def fetch[F[_]: Concurrent]: Fetch[F, List[Int]] =
-      List.range(1, 6).traverse(fetchBatchedDataPar[F])
+      List.range(1, 6).map(fetchBatchedDataPar[F]).batchAll
 
     val io = Fetch.runLog[IO](fetch)
 
@@ -180,8 +181,8 @@ class FetchBatchingTests extends FetchSpec {
 
   "Fetches to datasources with a maximum batch size should be split and executed in parallel and sequentially when using productR" in {
     def fetch[F[_]: Concurrent]: Fetch[F, List[Int]] =
-      List.range(1, 6).traverse(fetchBatchedDataPar[F]) *>
-        List.range(1, 6).traverse(fetchBatchedDataSeq[F])
+      List.range(1, 6).map(fetchBatchedDataPar[F]).batchAll *>
+        List.range(1, 6).map(fetchBatchedDataSeq[F]).batchAll
 
     val io = Fetch.runLog[IO](fetch)
 
@@ -195,8 +196,8 @@ class FetchBatchingTests extends FetchSpec {
 
   "Fetches to datasources with a maximum batch size should be split and executed in parallel and sequentially when using productL" in {
     def fetch[F[_]: Concurrent]: Fetch[F, List[Int]] =
-      List.range(1, 6).traverse(fetchBatchedDataPar[F]) <*
-        List.range(1, 6).traverse(fetchBatchedDataSeq[F])
+      List.range(1, 6).map(fetchBatchedDataPar[F]).batchAll <*
+        List.range(1, 6).map(fetchBatchedDataSeq[F]).batchAll
 
     val io = Fetch.runLog[IO](fetch)
 
@@ -210,7 +211,7 @@ class FetchBatchingTests extends FetchSpec {
 
   "A large (many) fetch to a datasource with a maximum batch size is split and executed in sequence" in {
     def fetch[F[_]: Concurrent]: Fetch[F, List[Int]] =
-      List(fetchBatchedDataSeq[F](1), fetchBatchedDataSeq[F](2), fetchBatchedDataSeq[F](3)).sequence
+      List(1, 2, 3).map(fetchBatchedDataSeq[F]).batchAll
 
     val io = Fetch.runLog[IO](fetch)
 
@@ -224,7 +225,7 @@ class FetchBatchingTests extends FetchSpec {
 
   "A large (many) fetch to a datasource with a maximum batch size is split and executed in parallel" in {
     def fetch[F[_]: Concurrent]: Fetch[F, List[Int]] =
-      List(fetchBatchedDataPar[F](1), fetchBatchedDataPar[F](2), fetchBatchedDataPar[F](3)).sequence
+      List(1, 2, 3).map(fetchBatchedDataPar[F]).batchAll
 
     val io = Fetch.runLog[IO](fetch)
 
@@ -247,7 +248,7 @@ class FetchBatchingTests extends FetchSpec {
     )
 
     val io = Fetch.runLog[IO](
-      ids.toList.traverse(fetchBatchedDataBigId[IO])
+      ids.toList.map(fetchBatchedDataBigId[IO]).batchAll
     )
 
     io.map { case (log, result) =>

fetch/src/test/scala/FetchReportingTests.scala

@@ -84,11 +84,25 @@ class FetchReportingTests extends FetchSpec {
     }.unsafeToFuture()
   }
 
-  "Single fetches combined with traverse are run in one round" in {
+  "Single fetches combined with traverse are NOT run in one round" in {
     def fetch[F[_]: Concurrent] =
       for {
         manies <- many(3)                 // round 1
-        ones   <- manies.traverse(one[F]) // round 2
+        ones   <- manies.traverse(one[F]) // rounds 2, 3, 4
+      } yield ones
+
+    val io = Fetch.runLog[IO](fetch)
+
+    io.map { case (log, result) =>
+      log.rounds.size shouldEqual 4
+    }.unsafeToFuture()
+  }
+
+  "Single fetches combined with Fetch.batchAll are run in one round" in {
+    def fetch[F[_]: Concurrent] =
+      for {
+        manies <- many(3)                                // round 1
+        ones   <- Fetch.batchAll(manies.map(one[F]): _*) // round 2
       } yield ones
 
     val io = Fetch.runLog[IO](fetch)