Managing Services

In the context of programming, a service refers to a reusable component or functionality that can be used by different parts of an application. Services are designed to provide specific capabilities and can be shared across multiple modules or components.

Services often encapsulate common tasks or operations that are needed by different parts of an application. They can handle complex operations, interact with external systems or APIs, manage data, or perform other specialized tasks.

Services are typically designed to be modular and decoupled from the rest of the application. This allows them to be easily maintained, tested, and replaced without affecting the overall functionality of the application.

When diving into services and their integration in application development, it helps to start from the basic principles of function management and dependency handling without relying on advanced constructs. Imagine having to manually pass a service around to every function that needs it:

const processData = (data: Data, databaseService: DatabaseService) => {
  // Operations using the database service
}

This approach becomes cumbersome and unmanageable as your application grows, with services needing to be passed through multiple layers of functions.

To streamline this, you might consider using an environment object that bundles various services:

type Context = {
  databaseService: DatabaseService
  loggingService: LoggingService
}

const processData = (data: Data, context: Context) => {
  // Using multiple services from the context
}

However, this introduces a new complexity: you must ensure that the environment is correctly set up with all necessary services before it’s used, which can lead to tightly coupled code and makes functional composition and testing more difficult.

Managing Services with Effect

The Effect library simplifies managing these dependencies by leveraging the type system. Instead of manually passing services or environment objects around, Effect allows you to declare service dependencies directly in the function’s type signature using the Requirements parameter in the Effect type:

                         ┌─── Represents required dependencies
                         ▼
Effect<Success, Error, Requirements>

This is how it works in practice when using Effect:

Dependency Declaration: You specify what services a function needs directly in its type, pushing the complexity of dependency management into the type system.

Service Provision: Effect.provideService is used to make a service implementation available to the functions that need it. By providing services at the start, you ensure that all parts of your application have consistent access to the required services, thus maintaining a clean and decoupled architecture.

This approach abstracts away manual service handling, letting developers focus on business logic while the compiler ensures all dependencies are correctly managed. It also makes code more maintainable and scalable.

Let’s walk through managing services in Effect step by step:

1. Creating a Service: Define a service with its unique functionality and interface.
2. Using the Service: Access and utilize the service within your application’s functions.
3. Providing a Service Implementation: Supply an actual implementation of the service to fulfill the declared requirements.

How It Works

Up to this point, our examples with the Effect framework have dealt with effects that operate independently of external services. This means the Requirements parameter in our Effect type signature has been set to never, indicating no dependencies.

However, real-world applications often need effects that rely on specific services to function correctly. These services are managed and accessed through a construct known as Context.

The Context serves as a repository or container for all services an effect may require. It acts like a store that maintains these services, allowing various parts of your application to access and use them as needed.

The services stored within the Context are directly reflected in the Requirements parameter of the Effect type. Each service within the Context is identified by a unique “tag,” which is essentially a unique identifier for the service.

When an effect needs to use a specific service, the service’s tag is included in the Requirements type parameter.

Creating a Service

To create a new service, you need two things:

1. A unique identifier.
2. A type describing the possible operations of the service.

Example (Defining a Random Number Generator Service)

Let’s create a service for generating random numbers.

1. Identifier. We’ll use the string "MyRandomService" as the unique identifier.
2. Type. The service type will have a single operation called next that returns a random number.

import { Effect, Context } from "effect"

// Declaring a tag for a service that generates random numbers
class Random extends Context.Tag("MyRandomService")<
  Random,
  { readonly next: Effect.Effect<number> }
>() {}

The exported Random value is known as a tag in Effect. It acts as a representation of the service and allows Effect to locate and use this service at runtime.

The service will be stored in a collection called Context, which can be thought of as a Map where the keys are tags and the values are services:

type Context = Map<Tag, Service>

Why Use Identifiers?

You need to specify an identifier to make the tag global. This ensures that two tags with the same identifier refer to the same instance.

Using a unique identifier is particularly useful in scenarios where live reloads can occur, as it helps preserve the instance across reloads. It ensures there is no duplication of instances (although it shouldn’t happen, some bundlers and frameworks can behave unpredictably).

Let’s summarize the concepts we’ve covered so far:

Concept	Description
service	A reusable component providing specific functionality, used across different parts of an application.
tag	A unique identifier representing a service, allowing Effect to locate and use it.
context	A collection storing service, functioning like a map with tags as keys and services as values.

Using the Service

Now that we have our service tag defined, let’s see how we can use it by building a simple program.

Example (Using the Random Service)

Using Effect.gen

import { Effect, Context } from "effect"

// Declaring a tag for a service that generates random numbers
class Random extends Context.Tag("MyRandomService")<
  Random,
  { readonly next: Effect.Effect<number> }
>() {}

// Using the service
const program = Effect.gen(function* () {
  const random = yield* Random
  const randomNumber = yield* random.next
  console.log(`random number: ${randomNumber}`)
})

In the code above, we can observe that we are able to yield the Random tag as if it were an effect itself. This allows us to access the next operation of the service.

Using pipe

import { Effect, Context, Console } from "effect"

// Declaring a tag for a service that generates random numbers
class Random extends Context.Tag("MyRandomService")<
  Random,
  { readonly next: Effect.Effect<number> }
>() {}

// Using the service
const program = Random.pipe(
  Effect.andThen((random) => random.next),
  Effect.andThen((randomNumber) =>
    Console.log(`random number: ${randomNumber}`)
  )
)

In the code above, we can observe that we are able to flat-map over the Random tag as if it were an effect itself. This allows us to access the next operation of the service within the Effect.andThen callback.

It’s worth noting that the type of the program variable includes Random in the Requirements type parameter:

const program: Effect<void, never, Random>

This indicates that our program requires the Random service to be provided in order to execute successfully.

If we attempt to execute the effect without providing the necessary service we will encounter a type-checking error:

Example (Type Error Without Service Provision)

import { Effect, Context } from "effect"

// Declaring a tag for a service that generates random numbers
class Random extends Context.Tag("MyRandomService")<
  Random,
  { readonly next: Effect.Effect<number> }
>() {}

// Using the service
const program = Effect.gen(function* () {
  const random = yield* Random
  const randomNumber = yield* random.next
  console.log(`random number: ${randomNumber}`)
})

// @ts-expect-error
Effect.runSync(program)
/*
Argument of type 'Effect<void, never, Random>' is not assignable to parameter of type 'Effect<void, never, never>'.
  Type 'Random' is not assignable to type 'never'.ts(2345)
*/

To resolve this error and successfully execute the program, we need to provide an actual implementation of the Random service.

In the next section, we will explore how to implement and provide the Random service to our program, enabling us to run it successfully.

Providing a Service Implementation

In order to provide an actual implementation of the Random service, we can utilize the Effect.provideService function.

Example (Providing a Random Number Implementation)

import { Effect, Context } from "effect"

// Declaring a tag for a service that generates random numbers
class Random extends Context.Tag("MyRandomService")<
  Random,
  { readonly next: Effect.Effect<number> }
>() {}

// Using the service
const program = Effect.gen(function* () {
  const random = yield* Random
  const randomNumber = yield* random.next
  console.log(`random number: ${randomNumber}`)
})

// Providing the implementation
const runnable = Effect.provideService(program, Random, {
  next: Effect.sync(() => Math.random())
})

// Run successfully
Effect.runPromise(runnable)
/*
Example Output:
random number: 0.8241872233134417
*/

In the code above, we provide the program we defined earlier with an implementation of the Random service.

We use the Effect.provideService function to associate the Random tag with its implementation, an object with a next operation that generates a random number.

Notice that the Requirements type parameter of the runnable effect is now never. This indicates that the effect no longer requires any service to be provided.

With the implementation of the Random service in place, we are able to run the program without any further requirements.

Extracting the Service Type

To retrieve the service type from a tag, use the Context.Tag.Service utility type.

Example (Extracting Service Type)

import { Effect, Context } from "effect"

// Declaring a tag
class Random extends Context.Tag("MyRandomService")<
  Random,
  { readonly next: Effect.Effect<number> }
>() {}

// Extracting the type
type RandomShape = Context.Tag.Service<Random>
/*
This is equivalent to:
type RandomShape = {
    readonly next: Effect.Effect<number>;
}
*/

Using Multiple Services

When we require the usage of more than one service, the process remains similar to what we’ve learned in defining a service, repeated for each service needed.

Example (Using Random and Logger Services)

Let’s examine an example where we need two services, namely Random and Logger:

import { Effect, Context } from "effect"

// Declaring a tag for a service that generates random numbers
class Random extends Context.Tag("MyRandomService")<
  Random,
  {
    readonly next: Effect.Effect<number>
  }
>() {}

// Declaring a tag for the logging service
class Logger extends Context.Tag("MyLoggerService")<
  Logger,
  {
    readonly log: (message: string) => Effect.Effect<void>
  }
>() {}

const program = Effect.gen(function* () {
  // Acquire instances of the 'Random' and 'Logger' services
  const random = yield* Random
  const logger = yield* Logger

  const randomNumber = yield* random.next

  yield* logger.log(String(randomNumber))
})

The program effect now has a Requirements type parameter of Random | Logger:

const program: Effect<void, never, Random | Logger>

indicating that it requires both the Random and Logger services to be provided.

To execute the program, we need to provide implementations for both services:

Example (Providing Multiple Services)

import { Effect, Context } from "effect"

// Declaring a tag for a service that generates random numbers
class Random extends Context.Tag("MyRandomService")<
  Random,
  {
    readonly next: Effect.Effect<number>
  }
>() {}

// Declaring a tag for the logging service
class Logger extends Context.Tag("MyLoggerService")<
  Logger,
  {
    readonly log: (message: string) => Effect.Effect<void>
  }
>() {}

const program = Effect.gen(function* () {
  const random = yield* Random
  const logger = yield* Logger
  const randomNumber = yield* random.next
  return yield* logger.log(String(randomNumber))
})

// Provide service implementations for 'Random' and 'Logger'
const runnable = program.pipe(
  Effect.provideService(Random, {
    next: Effect.sync(() => Math.random())
  }),
  Effect.provideService(Logger, {
    log: (message) => Effect.sync(() => console.log(message))
  })
)

Alternatively, instead of calling provideService multiple times, we can combine the service implementations into a single Context and then provide the entire context using the Effect.provide function:

Example (Combining Service Implementations)

import { Effect, Context } from "effect"

// Declaring a tag for a service that generates random numbers
class Random extends Context.Tag("MyRandomService")<
  Random,
  {
    readonly next: Effect.Effect<number>
  }
>() {}

// Declaring a tag for the logging service
class Logger extends Context.Tag("MyLoggerService")<
  Logger,
  {
    readonly log: (message: string) => Effect.Effect<void>
  }
>() {}

const program = Effect.gen(function* () {
  const random = yield* Random
  const logger = yield* Logger
  const randomNumber = yield* random.next
  return yield* logger.log(String(randomNumber))
})

// Combine service implementations into a single 'Context'
const context = Context.empty().pipe(
  Context.add(Random, { next: Effect.sync(() => Math.random()) }),
  Context.add(Logger, {
    log: (message) => Effect.sync(() => console.log(message))
  })
)

// Provide the entire context
const runnable = Effect.provide(program, context)

Optional Services

There are situations where we may want to access a service implementation only if it is available. In such cases, we can use the Effect.serviceOption function to handle this scenario.

The Effect.serviceOption function returns an implementation that is available only if it is actually provided before executing this effect. To represent this optionality it returns an Option of the implementation.

Example (Handling Optional Services)

To determine what action to take, we can use the Option.isNone function provided by the Option module. This function allows us to check if the service is available or not by returning true when the service is not available.

import { Effect, Context, Option } from "effect"

// Declaring a tag for a service that generates random numbers
class Random extends Context.Tag("MyRandomService")<
  Random,
  { readonly next: Effect.Effect<number> }
>() {}

const program = Effect.gen(function* () {
  const maybeRandom = yield* Effect.serviceOption(Random)
  const randomNumber = Option.isNone(maybeRandom)
    ? // the service is not available, return a default value
      -1
    : // the service is available
      yield* maybeRandom.value.next
  console.log(randomNumber)
})

In the code above, we can observe that the Requirements type parameter of the program effect is never, even though we are working with a service. This allows us to access something from the context only if it is actually provided before executing this effect.

When we run the program effect without providing the Random service:

Effect.runPromise(program).then(console.log)
// Output: -1

We see that the log message contains -1, which is the default value we provided when the service was not available.

However, if we provide the Random service implementation:

Effect.runPromise(
  Effect.provideService(program, Random, {
    next: Effect.sync(() => Math.random())
  })
).then(console.log)
// Example Output: 0.9957979486841035

We can observe that the log message now contains a random number generated by the next operation of the Random service.