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Version: 2.0.x

Introduction to the ZIO's Contextual Data Types

ZIO provides a contextual abstraction that encodes the environment of the running effect. This means, every effect can work within a specific context, called an environment.

So when we have a ZIO[R, E, A] effect, we can say "given R as the environment of the effect, the effect may fail with an error type of E, or may succeed with a value of type A".

For example, when we have an effect of type ZIO[DatabaseConnection, IOException, String], we can say that our effect works within the context of DatabaseConnection. In other words, we can say that our effect requires the DatabaseConnection service as a context to run.

We will see how layers can be used to eliminate the environment of an effect:

import zio._

import java.io.IOException

trait DatabaseConnection

// An effect which requires DatabaseConnection to run
val effect: ZIO[DatabaseConnection, IOException, String] = ???

// A layer that produces DatabaseConnection service
val dbConnection: ZLayer[Any, IOException, DatabaseConnection] = ???

// After applying dbConnection to our environmental effect the reurned
// effect has no dependency on the DatabaseConnection
val eliminated: ZIO[Any, IOException, String] =
dbConnection { // Provides DatabaseConnection context
effect // An effect running within `DatabaseConnection` context
}

ZIO provides this facility through the following concepts and data types:

  1. ZIO Environment — The R type parameter of ZIO[R, E, A] data type.
  2. ZEnvironment — Built-in type-level map for maintaining the environment of a ZIO data type.
  3. ZLayer — Describes how to build one or more services in our application.

Next, we will discuss ZIO Environment and ZLayer and finally how to write ZIO services using the Service Pattern.

1. ZIO Environment

The ZIO[-R, +E, +A] data type describes an effect that requires an input of type R, as an environment, may fail with an error of type E, or succeed with a value of type A.

The input type is also known as environment type. This type-parameter indicates that to run an effect we need one or some services as an environment of that effect. In other word, R represents the requirement for the effect to run, meaning we need to fulfill the requirement in order to make the effect runnable.

So we can think of ZIO[R, E, A] as a mental model of a function from a value of type R to the Either[E, A]:

type ZIO[R, E, A] = R => Either[E, A]

R represents dependencies; whatever services, config, or wiring a part of a ZIO program depends upon to work. We will explore what we can do with R, as it plays a crucial role in ZIO.

Motivation

One might ask "What is the motivation behind encoding the dependency in the type parameter of ZIO data type"? What is the benefit of doing so?

Let's see how writing an application which requires reading from or writing to the terminal. As part of making the application modular and testable we define a separate service called Terminal which is responsible for reading from and writing to the terminal. We do that simply by writing an interface:

import zio._

trait Terminal {
def print(line: Any): Task[Unit]

def printLine(line: Any): Task[Unit]

def readLine: Task[String]
}

Now we can write our application that accepts the Terminal interface as a parameter:

import zio._

def myApp(c: Terminal): Task[Unit] =
for {
_ <- c.print("Please enter your name: ")
name <- c.readLine
_ <- c.printLine(s"Hello, $name!")
} yield ()

Similar to the object-oriented paradigm we code to interface not implementation. In order to run the application, we need to implement a production version of the Terminal:

import zio._

object TerminalLive extends Terminal {
override def print(line: Any): Task[Unit] =
ZIO.attemptBlocking(scala.Predef.print(line))

override def printLine(line: Any): Task[Unit] =
ZIO.attemptBlocking(scala.Predef.println(line))

override def readLine: Task[String] =
ZIO.attemptBlocking(scala.io.StdIn.readLine())
}

Finally, we can provide the TerminalLive to our application and run the whole:

import zio._

object MainApp extends ZIOAppDefault {
def myApp(c: Terminal): Task[Unit] =
for {
_ <- c.print("Please enter your name: ")
name <- c.readLine
_ <- c.printLine(s"Hello, $name!")
} yield ()

def run = myApp(TerminalLive)
}

In the above example, we discard the fact that we could use the ZIO environment and utilize the R parameter of the ZIO data type. So instead we tried to write the application with the Task data type, which ignores the ZIO environment. To create our application testable, we gathered all terminal functionalities into the same interface called Terminal, and implemented that in another object called TerminalLive. Finally, at the end of the day, we provide the implementation of the Terminal service, i.e. TerminalLive, to our application.

While this technique works for small programs, it doesn't scale. Assume we have multiple services, and we use them in our application logic like below:

def foo(
s1: Service1,
s2: Service2,
s3: Service3
)(arg1: String, arg2: String, arg3: Int): Task[Int] = ???

def bar(
s1: Service1,
s12: Service12,
s18: Service18,
sn: ServiceN
)(arg1: Int, arg2: String, arg3: Double, arg4: Int): Task[Unit]

def myApp(s1: Service1, s2: Service2, ..., sn: ServiceN): Task[Unit] =
for {
a <- foo(s1, s2, s3)("arg1", "arg2", 4)
_ <- bar(s1, s12, s18, sn)(7, "arg2", 1.2, a)
...
} yield ()

Writing real applications using this technique is tedious and cumbersome because all dependencies have to be passed across all methods. We can simplify the process of writing our application by using the ZIO environment and Service Pattern.

def foo(arg1: String, arg2: String, arg3: Int): ZIO[Service1 & Service2 & Service3, Throwable, Int] = 
for {
s1 <- ZIO.service[Service1]
s2 <- ZIO.service[Service2]
...
} yield ()

def bar(arg1: Int, arg2: String, arg3: Double, arg4: Int): ZIO[Service1 & Service12 & Service18 & ServiceN, Throwable, Unit] =
for {
s1 <- ZIO.service[Service1]
s12 <- ZIO.service[Service12]
...
} yield ()

Advantage of Using ZIO Environment

ZIO environment facility enables us to:

  1. Code to Interface — Like object-oriented paradigm, in ZIO we are encouraged to code to interface and defer the implementation. It is the best practice, but ZIO does not enforce us to do that.

  2. Write a Testable Code — By coding to an interface, whenever we want to test our effects, we can easily mock any external services, by providing a test version of those instead of the live version.

  3. Compose Services with Strong Type Inference Facility — We can compose multiple effects that require various services, so the final effect requires the intersection of all those services:

import zio._

trait ServiceA
trait ServiceB
trait ServiceC

// Requires ServiceA and produces a value of type Int
def foo: ZIO[ServiceA, Nothing, Int] = ???

// Requires ServiceB and ServiceC and produces a value of type String
def bar: ZIO[ServiceB & ServiceC, Throwable, String] = ???

// Requires ServicB and produces a value of type Double
def baz(a: Int, b: String): ZIO[ServiceB, Nothing, Double] = ???

// Requires ServiceA and ServiceB and ServiceC and produces a value of type Double
val myApp: ZIO[ServiceA & ServiceB & ServiceC, Throwable, Double] =
for {
a <- foo
b <- bar
c <- baz(a, b)
} yield c

Another important note about the ZIO environment is that the type inference works well on effect composition. After we composed all the application logic together, the compiler and also IDE can infer the proper type for the environment of the final effect.

In the example above, the compiler can infer the environment type of the myApp effect which is ServiceA & ServiceB & ServiceC.

Accessing ZIO Environment

We have two types of accessors for the ZIO environment:

  1. Service Accessor (ZIO.service) is used to access a specific service from the environment.
  2. Service Member Accessors (ZIO.serviceWith and ZIO.serviceWithZIO) are used to access capabilities of a specific service from the environment.
note

To access the entire ZIO environment we can use ZIO.environment*, but we do not use these methods regularly to access ZIO services. Instead, we use service accessors and service member accessors.

Service Accessor

To access a service from the ZIO environment, we can use the ZIO.service constructor. For example, in the following program we are going to access the AppConfig from the environment:

import zio._

case class AppConfig(host: String, port: Int)

val myApp: ZIO[AppConfig, Nothing, Unit] =
for {
config <- ZIO.service[AppConfig]
_ <- ZIO.logInfo(s"Application started with config: $config")
} yield ()

To run the myApp effect, we should provide the AppConfig layer (we will talk about ZLayer on the next section):

object MainApp extends ZIOAppDefault {
def run = myApp.provide(ZLayer.succeed(AppConfig("localhost", 8080)))
}

To access multiple services from the ZIO environment, we can do the same:

import zio._

trait Foo
trait Bar
trait Baz

for {
foo <- ZIO.service[Foo]
bar <- ZIO.service[Bar]
bax <- ZIO.service[Baz]
} yield ()

When creating ZIO layers that have multiple dependencies, this can be helpful. We will discuss this pattern in the Service Pattern section.

Service Member Accessors

Sometimes instead of accessing a service, we need to access the capabilities (members) of a service. Based on the return type of each capability, we can use one of these accessors:

  • ZIO.serviceWith
  • ZIO.serviceWithZIO

In Service Pattern, we use these accessors to write "accessor methods" for ZIO services.

Let's look at each one in more detail:

  1. ZIO.serviceWith — When we are accessing service members whose return type is an ordinary value, we should use the ZIO.serviceWith.

In the following example, we need to use the ZIO.serviceWith to write accessor methods for all of the AppConfig members:

import zio._

case class AppConfig(host: String, port: Int, poolSize: Int)

object AppConfig {
// Accessor Methods
def host: ZIO[AppConfig, Nothing, String] = ZIO.serviceWith(_.host)
def port: ZIO[AppConfig, Nothing, Int] = ZIO.serviceWith(_.port)
def poolSize: ZIO[AppConfig, Nothing, Int] = ZIO.serviceWith(_.poolSize)
}

val myApp: ZIO[AppConfig, Nothing, Unit] =
for {
host <- AppConfig.host
port <- AppConfig.port
_ <- ZIO.logInfo(s"The service will be service at $host:$port")
poolSize <- AppConfig.poolSize
_ <- ZIO.logInfo(s"Application started with $poolSize pool size")
} yield ()
  1. ZIO.serviceWithZIO — When we are accessing service members whose return type is a ZIO effect, we should use the ZIO.serviceWithZIO.

For example, in order to write the accessor method for the foo member of the Foo service, we need to use the ZIO.serviceWithZIO function:

import zio._

trait Foo {
def foo(input: String): Task[Unit]
}

object Foo {
// Accessor Method
def foo(input: String): ZIO[Foo, Throwable, Unit] =
ZIO.serviceWithZIO(_.foo(input))
}

2. ZEnvironment

ZEnvironment is a built-in type-level map for maintaining the environment of a ZIO data type. We don't typically use this data type directly. It's okay to skip learning it at the moment. We have a separate article about this data type.

3. ZLayer

ZLayer[-RIn, +E, +ROut] is a recipe to build an environment of type ROut, starting from a value RIn, and possibly producing an error E during creation.