Fetch

A library for Simple & Efficient data access in Scala and Scala.js

• Documentation

Installation

Add the following dependency to your project's build file.

"com.fortysevendeg" %% "fetch" %% "0.2.0"

Or, if using Scala.js:

"com.fortysevendeg" %%% "fetch" %% "0.2.0"

Supported versions

• Scala: 2.11.x
• Scala.js: 0.6.x

Remote data

Fetch is a library for making access to data both simple & efficient. Fetch is especially useful when querying data that has a latency cost, such as databases or web services.

Define your data sources

To tell Fetch how to get the data you want, you must implement the DataSource typeclass. Data sources have a fetch method that defines how to fetch such a piece of data.

Data Sources take two type parameters:

1. Identity is a type that has enough information to fetch the data
2. Result is the type of data we want to fetch

trait DataSource[Identity, Result]{
  def fetch(ids: NonEmptyList[Identity]): Eval[Map[Identity, Result]]
}

We'll implement a dummy data source that can convert integers to strings. For convenience, we define a fetchString function that lifts identities (Int in our dummy data source) to a Fetch.

import cats.Eval
import cats.data.NonEmptyList
import cats.std.list._

import fetch._

implicit object ToStringSource extends DataSource[Int, String]{
  override def fetch(ids: NonEmptyList[Int]): Eval[Map[Int, String]] = {
    Eval.later({
      println(s"ToStringSource $ids")
      ids.unwrap.map(i => (i, i.toString)).toMap
    })
  }
}

def fetchString(n: Int): Fetch[String] = Fetch(n) // or, more explicitly: Fetch(n)(ToStringSource)

Creating and running a fetch

Now that we can convert Int values to Fetch[String], let's try creating a fetch.

import fetch.implicits._
import fetch.syntax._

val fetchOne: Fetch[String] = fetchString(1)

Now that we have created a fetch, we can run it to a target monad. Note that the target monad (Eval in our example) needs to implement MonadError[M, Throwable], we provide an instance for Eval in fetch.implicits._, that's why we imported it.

val result: String = fetchOne.runA[Eval].value
// ToStringSource OneAnd(1,List())
// result: String = 1

As you can see in the previous example, the ToStringSource is queried once to get the value of 1.

Batching

Multiple fetches to the same data source are automatically batched. For illustrating it, we are going to compose three independent fetch results as a tuple.

import cats.syntax.cartesian._

val fetchThree: Fetch[(String, String, String)] = (fetchString(1) |@| fetchString(2) |@| fetchString(3)).tupled

When executing the above fetch, note how the three identities get batched and the data source is only queried once.

val result: (String, String, String) = fetchThree.runA[Eval].value
// ToStringSource OneAnd(1,List(2, 3))
// result: (String, String, String) = (1,2,3)

Concurrency

If we combine two independent fetches from different data sources, the fetches will be run concurrently. First, let's add a data source that fetches a string's size.

implicit object LengthSource extends DataSource[String, Int]{
  override def fetch(ids: NonEmptyList[String]): Eval[Map[String, Int]] = {
    Eval.later({
      println(s"LengthSource $ids")
      ids.unwrap.map(i => (i, i.size)).toMap
    })
  }
}

def fetchLength(s: String): Fetch[Int] = Fetch(s)

And now we can easily recieve data from the two sources in a single fetch.

val fetchMulti: Fetch[(String, Int)] = (fetchString(1) |@| fetchLength("one")).tupled

Note how the two independent data fetches are run concurrently, minimizing the latency cost of querying the two data sources. If our target monad was a concurrency monad like Future, they'd run in parallel, each in its own logical thread.

val result: (String, Int) = fetchMulti.runA[Eval].value
// ToStringSource OneAnd(1,List())
// LengthSource OneAnd(one,List())
// result: (String, Int) = (1,3)

Caching

When fetching an identity, subsequent fetches for the same identity are cached. Let's try creating a fetch that asks for the same identity twice.

val fetchTwice: Fetch[(String, String)] = for {
  one <- fetchString(1)
  two <- fetchString(1)
} yield (one, two)

While running it, notice that the data source is only queried once. The next time the identity is requested, it's served from the cache.

val result: (String, String) = fetchTwice.runA[Eval].value
// ToStringSource OneAnd(1,List())
// result: (String, String) = (1,1)