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日志记录

日志记录是软件开发的重要方面,特别是对于调试和监控应用程序行为。在本节中,我们将探索 Effect 的日志记录工具,并了解它们与传统日志记录方法的比较。

Effect 的日志记录工具相比传统日志记录方法提供了几个优势:

  1. 动态日志级别控制:使用 Effect 的日志记录,您可以动态更改日志级别。这意味着您可以根据严重程度控制显示哪些日志消息。例如,您可以配置应用程序仅记录警告或错误,这在生产环境中非常有用,可以减少噪音。

  2. 自定义日志输出:Effect 的日志记录工具允许您更改日志的处理方式。您可以使用自定义记录器将日志消息定向到各种目标,如服务或文件。这种灵活性确保日志以最适合您应用程序需求的方式存储和处理。

  3. 细粒度日志记录:Effect 支持对程序的每个部分进行细粒度的日志记录控制。您可以为应用程序的不同部分设置不同的日志级别,为每个特定组件定制详细程度。这对于调试和故障排除非常有价值,因为您可以专注于最重要的信息。

  4. 基于环境的日志记录:Effect 的日志记录工具可以与部署环境结合使用,实现细粒度的日志记录策略。例如,在开发期间,您可能选择记录跟踪级别及以上的所有内容以进行详细调试。相比之下,您的生产版本可以配置为仅记录错误或关键问题,最大限度地减少对性能的影响和生产日志中的噪音。

  5. 附加功能:Effect 的日志记录工具还提供附加功能,如测量时间跨度的能力、基于每个 Effect 更改日志级别,以及集成跨度进行性能监控。

Effect.log 函数允许您在默认的 INFO 级别记录消息。

示例(记录简单消息)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("Application started")
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO fiber=#0 message="Application started"
*/

Effect 中的默认记录器为每个日志条目添加了几个有用的详细信息:

注解描述
timestamp生成日志消息时的时间戳。
level记录消息的日志级别(例如,INFOERROR)。
fiber执行程序的纤程标识符。
message日志消息内容,可以包含多个字符串或值。
span(可选)跨度的持续时间(以毫秒为单位),提供对操作时间的洞察。

您也可以一次记录多个消息。

示例(记录多个消息)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("message1", "message2", "message3")
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO fiber=#0 message=message1 message=message2 message=message3
*/

为了增加上下文,您还可以在日志中包含一个或多个 Cause 实例, 这些实例在附加的 cause 注解下提供详细的错误信息:

示例(使用原因记录日志)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Cause
Cause
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
(
"message1",
"message2",
import Cause
Cause
.
const die: (defect: unknown) => Cause.Cause<never>

Creates a Die cause from an unexpected error.

Details

This function wraps an unhandled or unknown defect (like a runtime crash) into a Cause. It's useful for capturing unforeseen issues in a structured way.

@seeisDie Check if a Cause contains a defect

@since2.0.0

die
("Oh no!"),
import Cause
Cause
.
const die: (defect: unknown) => Cause.Cause<never>

Creates a Die cause from an unexpected error.

Details

This function wraps an unhandled or unknown defect (like a runtime crash) into a Cause. It's useful for capturing unforeseen issues in a structured way.

@seeisDie Check if a Cause contains a defect

@since2.0.0

die
("Oh uh!")
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
Error: Oh uh!"
*/

默认情况下,DEBUG 消息不会显示。要启用 DEBUG 日志,您可以使用 Logger.withMinimumLogLevel 调整日志记录配置,将最小级别设置为 LogLevel.Debug

示例(启用调试日志)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
,
import LogLevel
LogLevel
} from "effect"
const
const task1: Effect.Effect<void, never, never>
task1
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("2 seconds")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logDebug: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the DEBUG log level.

Details

This function logs messages at the DEBUG level, which is typically used for diagnosing application behavior during development. DEBUG messages provide less detailed information than TRACE logs but are still not shown by default. To view these logs, adjust the log level using Logger.withMinimumLogLevel.

Example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

logDebug
("task1 done") // 记录调试消息
}).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Logger
Logger
.
const withMinimumLogLevel: (level: LogLevel.LogLevel) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Sets the minimum log level for subsequent logging operations, allowing control over which log messages are displayed based on their severity.

@example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

withMinimumLogLevel
(
import LogLevel
LogLevel
.
const Debug: LogLevel.LogLevel

@since2.0.0

@since2.0.0

Debug
)) // 启用 DEBUG 级别
const
const task2: Effect.Effect<void, never, never>
task2
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("1 second")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logDebug: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the DEBUG log level.

Details

This function logs messages at the DEBUG level, which is typically used for diagnosing application behavior during development. DEBUG messages provide less detailed information than TRACE logs but are still not shown by default. To view these logs, adjust the log level using Logger.withMinimumLogLevel.

Example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

logDebug
("task2 done") // 此消息不会被记录
})
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("start")
yield*
const task1: Effect.Effect<void, never, never>
task1
yield*
const task2: Effect.Effect<void, never, never>
task2
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("done")
})
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO message=start
timestamp=... level=DEBUG message="task1 done" <-- 2 seconds later
timestamp=... level=INFO message=done <-- 1 second later
*/

INFO 日志级别默认显示。此级别通常用于一般应用程序事件或进度更新。

示例(在信息级别记录日志)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logInfo: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the INFO log level.

Details

This function logs messages at the INFO level, suitable for general application events or operational messages. INFO logs are shown by default and are commonly used for highlighting normal, non-error operations.

@since2.0.0

logInfo
("start")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("2 seconds")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("1 second")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logInfo: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the INFO log level.

Details

This function logs messages at the INFO level, suitable for general application events or operational messages. INFO logs are shown by default and are commonly used for highlighting normal, non-error operations.

@since2.0.0

logInfo
("done")
})
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO message=start
timestamp=... level=INFO message=done <-- 3 seconds later
*/

WARN 日志级别默认显示。此级别用于潜在问题或警告,这些问题不会立即中断程序流程,但应该被监控。

示例(在警告级别记录日志)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Either

@since2.0.0

@since2.0.0

Either
} from "effect"
const
const task: Effect.Effect<number, string, never>
task
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const fail: <string>(error: string) => Effect.Effect<never, string, never>

Creates an Effect that represents a recoverable error.

When to Use

Use this function to explicitly signal an error in an Effect. The error will keep propagating unless it is handled. You can handle the error with functions like

catchAll

or

catchTag

.

Example (Creating a Failed Effect)

import { Effect } from "effect"
// ┌─── Effect<never, Error, never>
// ▼
const failure = Effect.fail(
new Error("Operation failed due to network error")
)

@seesucceed to create an effect that represents a successful value.

@since2.0.0

fail
("Oh uh!").
Pipeable.pipe<Effect.Effect<never, string, never>, Effect.Effect<number, string, never>>(this: Effect.Effect<never, string, never>, ab: (_: Effect.Effect<never, string, never>) => Effect.Effect<number, string, never>): Effect.Effect<number, string, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const as: <number>(value: number) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<number, E, R> (+1 overload)

Replaces the value inside an effect with a constant value.

Details

This function allows you to ignore the original value inside an effect and replace it with a constant value.

When to Use

It is useful when you no longer need the value produced by an effect but want to ensure that the effect completes successfully with a specific constant result instead. For instance, you can replace the value produced by a computation with a predefined value, ignoring what was calculated before.

Example (Replacing a Value)

import { pipe, Effect } from "effect"
// Replaces the value 5 with the constant "new value"
const program = pipe(Effect.succeed(5), Effect.as("new value"))
Effect.runPromise(program).then(console.log)
// Output: "new value"

@since2.0.0

as
(2))
const
const program: Effect.Effect<number, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, number>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, number, never>) => Effect.Effect<number, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
const
const failureOrSuccess: Either.Either<number, string>
failureOrSuccess
= yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const either: <number, string, never>(self: Effect.Effect<number, string, never>) => Effect.Effect<Either.Either<number, string>, never, never>

Encapsulates both success and failure of an Effect into an Either type.

Details

This function converts an effect that may fail into an effect that always succeeds, wrapping the outcome in an Either type. The result will be Either.Left if the effect fails, containing the recoverable error, or Either.Right if it succeeds, containing the result.

Using this function, you can handle recoverable errors explicitly without causing the effect to fail. This is particularly useful in scenarios where you want to chain effects and manage both success and failure in the same logical flow.

It's important to note that unrecoverable errors, often referred to as "defects," are still thrown and not captured within the Either type. Only failures that are explicitly represented as recoverable errors in the effect are encapsulated.

The resulting effect cannot fail directly because all recoverable failures are represented inside the Either type.

Example

import { Effect, Either, Random } from "effect"
class HttpError {
readonly _tag = "HttpError"
}
class ValidationError {
readonly _tag = "ValidationError"
}
// ┌─── Effect<string, HttpError | ValidationError, never>
// ▼
const program = Effect.gen(function* () {
const n1 = yield* Random.next
const n2 = yield* Random.next
if (n1 < 0.5) {
yield* Effect.fail(new HttpError())
}
if (n2 < 0.5) {
yield* Effect.fail(new ValidationError())
}
return "some result"
})
// ┌─── Effect<string, never, never>
// ▼
const recovered = Effect.gen(function* () {
// ┌─── Either<string, HttpError | ValidationError>
// ▼
const failureOrSuccess = yield* Effect.either(program)
return Either.match(failureOrSuccess, {
onLeft: (error) => `Recovering from ${error._tag}`,
onRight: (value) => value // Do nothing in case of success
})
})

@seeoption for a version that uses Option instead.

@seeexit for a version that encapsulates both recoverable errors and defects in an Exit.

@since2.0.0

either
(
const task: Effect.Effect<number, string, never>
task
)
if (
import Either

@since2.0.0

@since2.0.0

Either
.
const isLeft: <number, string>(self: Either.Either<number, string>) => self is Either.Left<string, number>

Determine if a Either is a Left.

@example

import * as assert from "node:assert"
import { Either } from "effect"
assert.deepStrictEqual(Either.isLeft(Either.right(1)), false)
assert.deepStrictEqual(Either.isLeft(Either.left("a")), true)

@since2.0.0

isLeft
(
const failureOrSuccess: Either.Either<number, string>
failureOrSuccess
)) {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logWarning: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the WARNING log level.

Details

This function logs messages at the WARNING level, suitable for highlighting potential issues that are not errors but may require attention. These messages indicate that something unexpected occurred or might lead to errors in the future.

@since2.0.0

logWarning
(
const failureOrSuccess: Either.Left<string, number>
failureOrSuccess
.
Left<string, number>.left: string
left
)
return 0
} else {
return
const failureOrSuccess: Either.Right<string, number>
failureOrSuccess
.
Right<string, number>.right: number
right
}
})
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <number, never>(effect: Effect.Effect<number, never, never>, options?: RunForkOptions) => RuntimeFiber<number, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<number, never, never>
program
)
/*
Output:
timestamp=... level=WARN fiber=#0 message="Oh uh!"
*/

ERROR 日志级别默认显示。这些消息表示需要解决的问题。

示例(在错误级别记录日志)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Either

@since2.0.0

@since2.0.0

Either
} from "effect"
const
const task: Effect.Effect<number, string, never>
task
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const fail: <string>(error: string) => Effect.Effect<never, string, never>

Creates an Effect that represents a recoverable error.

When to Use

Use this function to explicitly signal an error in an Effect. The error will keep propagating unless it is handled. You can handle the error with functions like

catchAll

or

catchTag

.

Example (Creating a Failed Effect)

import { Effect } from "effect"
// ┌─── Effect<never, Error, never>
// ▼
const failure = Effect.fail(
new Error("Operation failed due to network error")
)

@seesucceed to create an effect that represents a successful value.

@since2.0.0

fail
("Oh uh!").
Pipeable.pipe<Effect.Effect<never, string, never>, Effect.Effect<number, string, never>>(this: Effect.Effect<never, string, never>, ab: (_: Effect.Effect<never, string, never>) => Effect.Effect<number, string, never>): Effect.Effect<number, string, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const as: <number>(value: number) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<number, E, R> (+1 overload)

Replaces the value inside an effect with a constant value.

Details

This function allows you to ignore the original value inside an effect and replace it with a constant value.

When to Use

It is useful when you no longer need the value produced by an effect but want to ensure that the effect completes successfully with a specific constant result instead. For instance, you can replace the value produced by a computation with a predefined value, ignoring what was calculated before.

Example (Replacing a Value)

import { pipe, Effect } from "effect"
// Replaces the value 5 with the constant "new value"
const program = pipe(Effect.succeed(5), Effect.as("new value"))
Effect.runPromise(program).then(console.log)
// Output: "new value"

@since2.0.0

as
(2))
const
const program: Effect.Effect<number, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, number>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, number, never>) => Effect.Effect<number, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
const
const failureOrSuccess: Either.Either<number, string>
failureOrSuccess
= yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const either: <number, string, never>(self: Effect.Effect<number, string, never>) => Effect.Effect<Either.Either<number, string>, never, never>

Encapsulates both success and failure of an Effect into an Either type.

Details

This function converts an effect that may fail into an effect that always succeeds, wrapping the outcome in an Either type. The result will be Either.Left if the effect fails, containing the recoverable error, or Either.Right if it succeeds, containing the result.

Using this function, you can handle recoverable errors explicitly without causing the effect to fail. This is particularly useful in scenarios where you want to chain effects and manage both success and failure in the same logical flow.

It's important to note that unrecoverable errors, often referred to as "defects," are still thrown and not captured within the Either type. Only failures that are explicitly represented as recoverable errors in the effect are encapsulated.

The resulting effect cannot fail directly because all recoverable failures are represented inside the Either type.

Example

import { Effect, Either, Random } from "effect"
class HttpError {
readonly _tag = "HttpError"
}
class ValidationError {
readonly _tag = "ValidationError"
}
// ┌─── Effect<string, HttpError | ValidationError, never>
// ▼
const program = Effect.gen(function* () {
const n1 = yield* Random.next
const n2 = yield* Random.next
if (n1 < 0.5) {
yield* Effect.fail(new HttpError())
}
if (n2 < 0.5) {
yield* Effect.fail(new ValidationError())
}
return "some result"
})
// ┌─── Effect<string, never, never>
// ▼
const recovered = Effect.gen(function* () {
// ┌─── Either<string, HttpError | ValidationError>
// ▼
const failureOrSuccess = yield* Effect.either(program)
return Either.match(failureOrSuccess, {
onLeft: (error) => `Recovering from ${error._tag}`,
onRight: (value) => value // Do nothing in case of success
})
})

@seeoption for a version that uses Option instead.

@seeexit for a version that encapsulates both recoverable errors and defects in an Exit.

@since2.0.0

either
(
const task: Effect.Effect<number, string, never>
task
)
if (
import Either

@since2.0.0

@since2.0.0

Either
.
const isLeft: <number, string>(self: Either.Either<number, string>) => self is Either.Left<string, number>

Determine if a Either is a Left.

@example

import * as assert from "node:assert"
import { Either } from "effect"
assert.deepStrictEqual(Either.isLeft(Either.right(1)), false)
assert.deepStrictEqual(Either.isLeft(Either.left("a")), true)

@since2.0.0

isLeft
(
const failureOrSuccess: Either.Either<number, string>
failureOrSuccess
)) {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logError: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the ERROR log level.

Details

This function logs messages at the ERROR level, suitable for reporting application errors or failures. These logs are typically used for unexpected issues that need immediate attention.

@since2.0.0

logError
(
const failureOrSuccess: Either.Left<string, number>
failureOrSuccess
.
Left<string, number>.left: string
left
)
return 0
} else {
return
const failureOrSuccess: Either.Right<string, number>
failureOrSuccess
.
Right<string, number>.right: number
right
}
})
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <number, never>(effect: Effect.Effect<number, never, never>, options?: RunForkOptions) => RuntimeFiber<number, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<number, never, never>
program
)
/*
Output:
timestamp=... level=ERROR fiber=#0 message="Oh uh!"
*/

FATAL 日志级别默认显示。此日志级别通常保留给不可恢复的错误。

示例(在致命级别记录日志)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Either

@since2.0.0

@since2.0.0

Either
} from "effect"
const
const task: Effect.Effect<number, string, never>
task
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const fail: <string>(error: string) => Effect.Effect<never, string, never>

Creates an Effect that represents a recoverable error.

When to Use

Use this function to explicitly signal an error in an Effect. The error will keep propagating unless it is handled. You can handle the error with functions like

catchAll

or

catchTag

.

Example (Creating a Failed Effect)

import { Effect } from "effect"
// ┌─── Effect<never, Error, never>
// ▼
const failure = Effect.fail(
new Error("Operation failed due to network error")
)

@seesucceed to create an effect that represents a successful value.

@since2.0.0

fail
("Oh uh!").
Pipeable.pipe<Effect.Effect<never, string, never>, Effect.Effect<number, string, never>>(this: Effect.Effect<never, string, never>, ab: (_: Effect.Effect<never, string, never>) => Effect.Effect<number, string, never>): Effect.Effect<number, string, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const as: <number>(value: number) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<number, E, R> (+1 overload)

Replaces the value inside an effect with a constant value.

Details

This function allows you to ignore the original value inside an effect and replace it with a constant value.

When to Use

It is useful when you no longer need the value produced by an effect but want to ensure that the effect completes successfully with a specific constant result instead. For instance, you can replace the value produced by a computation with a predefined value, ignoring what was calculated before.

Example (Replacing a Value)

import { pipe, Effect } from "effect"
// Replaces the value 5 with the constant "new value"
const program = pipe(Effect.succeed(5), Effect.as("new value"))
Effect.runPromise(program).then(console.log)
// Output: "new value"

@since2.0.0

as
(2))
const
const program: Effect.Effect<number, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, number>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, number, never>) => Effect.Effect<number, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
const
const failureOrSuccess: Either.Either<number, string>
failureOrSuccess
= yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const either: <number, string, never>(self: Effect.Effect<number, string, never>) => Effect.Effect<Either.Either<number, string>, never, never>

Encapsulates both success and failure of an Effect into an Either type.

Details

This function converts an effect that may fail into an effect that always succeeds, wrapping the outcome in an Either type. The result will be Either.Left if the effect fails, containing the recoverable error, or Either.Right if it succeeds, containing the result.

Using this function, you can handle recoverable errors explicitly without causing the effect to fail. This is particularly useful in scenarios where you want to chain effects and manage both success and failure in the same logical flow.

It's important to note that unrecoverable errors, often referred to as "defects," are still thrown and not captured within the Either type. Only failures that are explicitly represented as recoverable errors in the effect are encapsulated.

The resulting effect cannot fail directly because all recoverable failures are represented inside the Either type.

Example

import { Effect, Either, Random } from "effect"
class HttpError {
readonly _tag = "HttpError"
}
class ValidationError {
readonly _tag = "ValidationError"
}
// ┌─── Effect<string, HttpError | ValidationError, never>
// ▼
const program = Effect.gen(function* () {
const n1 = yield* Random.next
const n2 = yield* Random.next
if (n1 < 0.5) {
yield* Effect.fail(new HttpError())
}
if (n2 < 0.5) {
yield* Effect.fail(new ValidationError())
}
return "some result"
})
// ┌─── Effect<string, never, never>
// ▼
const recovered = Effect.gen(function* () {
// ┌─── Either<string, HttpError | ValidationError>
// ▼
const failureOrSuccess = yield* Effect.either(program)
return Either.match(failureOrSuccess, {
onLeft: (error) => `Recovering from ${error._tag}`,
onRight: (value) => value // Do nothing in case of success
})
})

@seeoption for a version that uses Option instead.

@seeexit for a version that encapsulates both recoverable errors and defects in an Exit.

@since2.0.0

either
(
const task: Effect.Effect<number, string, never>
task
)
if (
import Either

@since2.0.0

@since2.0.0

Either
.
const isLeft: <number, string>(self: Either.Either<number, string>) => self is Either.Left<string, number>

Determine if a Either is a Left.

@example

import * as assert from "node:assert"
import { Either } from "effect"
assert.deepStrictEqual(Either.isLeft(Either.right(1)), false)
assert.deepStrictEqual(Either.isLeft(Either.left("a")), true)

@since2.0.0

isLeft
(
const failureOrSuccess: Either.Either<number, string>
failureOrSuccess
)) {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logFatal: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the FATAL log level.

Details

This function logs messages at the FATAL level, suitable for reporting critical errors that cause the application to terminate or stop functioning. These logs are typically used for unrecoverable errors that require immediate attention.

@since2.0.0

logFatal
(
const failureOrSuccess: Either.Left<string, number>
failureOrSuccess
.
Left<string, number>.left: string
left
)
return 0
} else {
return
const failureOrSuccess: Either.Right<string, number>
failureOrSuccess
.
Right<string, number>.right: number
right
}
})
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <number, never>(effect: Effect.Effect<number, never, never>, options?: RunForkOptions) => RuntimeFiber<number, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<number, never, never>
program
)
/*
Output:
timestamp=... level=FATAL fiber=#0 message="Oh uh!"
*/

您可以使用 Effect.annotateLogs 函数添加自定义注解来增强日志输出。 这允许您为每个日志条目附加额外的元数据,提高可追溯性并提供额外的上下文。

您可以将单个注解作为键/值对应用于 Effect 内的所有日志条目。

示例(单个键/值注解)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("message1")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("message2")
}).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
// 注解作为键/值对
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const annotateLogs: (key: string, value: unknown) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+3 overloads)

Adds custom annotations to log entries generated within an effect.

Details

This function allows you to enhance log messages by appending additional context in the form of key-value pairs. These annotations are included in every log message created during the execution of the effect, making the logs more informative and easier to trace.

The annotations can be specified as a single key-value pair or as a record of multiple key-value pairs. This is particularly useful for tracking operations, debugging, or associating specific metadata with logs for better observability.

The annotated key-value pairs will appear alongside the log message in the output.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("message1")
yield* Effect.log("message2")
}).pipe(Effect.annotateLogs("taskId", "1234")) // Annotation as key/value pair
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message=message1 taskId=1234
// timestamp=... level=INFO fiber=#0 message=message2 taskId=1234

@seeannotateLogsScoped to add log annotations with a limited scope.

@since2.0.0

annotateLogs
("key", "value")
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO fiber=#0 message=message1 key=value
timestamp=... level=INFO fiber=#0 message=message2 key=value
*/

在此示例中,program 内生成的所有日志都将包含注解 key=value

注解会传播到嵌套或下游 Effect 内生成的所有日志。这确保来自任何子 Effect 的日志都继承父 Effect 的注解。

示例(将注解传播到嵌套 Effect)

在此示例中,注解 key=value 包含在所有日志中,甚至包括来自嵌套 anotherProgram Effect 的日志。

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
} from "effect"
// 定义一个记录错误的子程序
const
const anotherProgram: Effect.Effect<void, never, never>
anotherProgram
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logError: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the ERROR log level.

Details

This function logs messages at the ERROR level, suitable for reporting application errors or failures. These logs are typically used for unexpected issues that need immediate attention.

@since2.0.0

logError
("error1")
})
// 定义主程序
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("message1")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("message2")
yield*
const anotherProgram: Effect.Effect<void, never, never>
anotherProgram
// 调用嵌套程序
}).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
// 为作用域内的所有日志附加注解
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const annotateLogs: (key: string, value: unknown) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+3 overloads)

Adds custom annotations to log entries generated within an effect.

Details

This function allows you to enhance log messages by appending additional context in the form of key-value pairs. These annotations are included in every log message created during the execution of the effect, making the logs more informative and easier to trace.

The annotations can be specified as a single key-value pair or as a record of multiple key-value pairs. This is particularly useful for tracking operations, debugging, or associating specific metadata with logs for better observability.

The annotated key-value pairs will appear alongside the log message in the output.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("message1")
yield* Effect.log("message2")
}).pipe(Effect.annotateLogs("taskId", "1234")) // Annotation as key/value pair
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message=message1 taskId=1234
// timestamp=... level=INFO fiber=#0 message=message2 taskId=1234

@seeannotateLogsScoped to add log annotations with a limited scope.

@since2.0.0

annotateLogs
("key", "value")
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO fiber=#0 message=message1 key=value
timestamp=... level=INFO fiber=#0 message=message2 key=value
timestamp=... level=ERROR fiber=#0 message=error1 key=value
*/

您还可以通过传递包含键/值对的对象一次应用多个注解。每个键/值对都将添加到 Effect 内的每个日志条目中。

示例(多个注解)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("message1")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("message2")
}).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
// 添加多个注解
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const annotateLogs: (values: Record<string, unknown>) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+3 overloads)

Adds custom annotations to log entries generated within an effect.

Details

This function allows you to enhance log messages by appending additional context in the form of key-value pairs. These annotations are included in every log message created during the execution of the effect, making the logs more informative and easier to trace.

The annotations can be specified as a single key-value pair or as a record of multiple key-value pairs. This is particularly useful for tracking operations, debugging, or associating specific metadata with logs for better observability.

The annotated key-value pairs will appear alongside the log message in the output.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("message1")
yield* Effect.log("message2")
}).pipe(Effect.annotateLogs("taskId", "1234")) // Annotation as key/value pair
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message=message1 taskId=1234
// timestamp=... level=INFO fiber=#0 message=message2 taskId=1234

@seeannotateLogsScoped to add log annotations with a limited scope.

@since2.0.0

annotateLogs
({
key1: string
key1
: "value1",
key2: string
key2
: "value2" })
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO fiber=#0 message=message1 key2=value2 key1=value1
timestamp=... level=INFO fiber=#0 message=message2 key2=value2 key1=value1
*/

在这种情况下,每个日志都将包含 key1=value1key2=value2

如果您想限制注解的作用域,使其仅应用于某些日志条目,可以使用 Effect.annotateLogsScoped。此函数将注解限制在特定作用域内产生的日志。

示例(作用域注解)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, Scope>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, Scope>>, void, never>) => Effect.Effect<void, never, Scope> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("no annotations") // 无注解
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const annotateLogsScoped: (values: Record<string, unknown>) => Effect.Effect<void, never, Scope> (+1 overload)

Adds log annotations with a limited scope to enhance contextual logging.

Details

This function allows you to apply key-value annotations to log entries generated within a specific scope of your effect computations. The annotations are restricted to the defined Scope, ensuring that they are only applied to logs produced during that scope. Once the scope ends, the annotations are automatically removed, making it easier to manage context-specific logging without affecting other parts of your application.

The annotations can be provided as a single key-value pair or as a record of multiple key-value pairs. This flexibility enables fine-grained control over the additional metadata included in logs for specific tasks or operations.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("no annotations")
yield* Effect.annotateLogsScoped({ key: "value" })
yield* Effect.log("message1") // Annotation is applied to this log
yield* Effect.log("message2") // Annotation is applied to this log
}).pipe(Effect.scoped, Effect.andThen(Effect.log("no annotations again")))
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message="no annotations"
// timestamp=... level=INFO fiber=#0 message=message1 key=value
// timestamp=... level=INFO fiber=#0 message=message2 key=value
// timestamp=... level=INFO fiber=#0 message="no annotations again"

@seeannotateLogs to add custom annotations to log entries generated within an effect.

@since3.1.0

annotateLogsScoped
({
key: string
key
: "value" }) // 作用域注解
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("message1") // 应用注解
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("message2") // 应用注解
}).
Pipeable.pipe<Effect.Effect<void, never, Scope>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, Scope>, ab: (_: Effect.Effect<void, never, Scope>) => Effect.Effect<void, never, never>, bc: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const scoped: <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, Scope>>

Scopes all resources used in an effect to the lifetime of the effect.

Details

This function ensures that all resources used within an effect are tied to its lifetime. Finalizers for these resources are executed automatically when the effect completes, whether through success, failure, or interruption. This guarantees proper resource cleanup without requiring explicit management.

@since2.0.0

scoped
,
// 作用域外,无注解
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const andThen: <Effect.Effect<void, never, never>>(f: Effect.Effect<void, never, never>) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<void, E, R> (+3 overloads)

Chains two actions, where the second action can depend on the result of the first.

Syntax

const transformedEffect = pipe(myEffect, Effect.andThen(anotherEffect))
// or
const transformedEffect = Effect.andThen(myEffect, anotherEffect)
// or
const transformedEffect = myEffect.pipe(Effect.andThen(anotherEffect))

When to Use

Use andThen when you need to run multiple actions in sequence, with the second action depending on the result of the first. This is useful for combining effects or handling computations that must happen in order.

Details

The second action can be:

  • A constant value (similar to

as

)

  • A function returning a value (similar to

map

)

  • A Promise
  • A function returning a Promise
  • An Effect
  • A function returning an Effect (similar to

flatMap

)

Note: andThen works well with both Option and Either types, treating them as effects.

Example (Applying a Discount Based on Fetched Amount)

import { pipe, Effect } from "effect"
// Function to apply a discount safely to a transaction amount
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
// Simulated asynchronous task to fetch a transaction amount from database
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
// Using Effect.map and Effect.flatMap
const result1 = pipe(
fetchTransactionAmount,
Effect.map((amount) => amount * 2),
Effect.flatMap((amount) => applyDiscount(amount, 5))
)
Effect.runPromise(result1).then(console.log)
// Output: 190
// Using Effect.andThen
const result2 = pipe(
fetchTransactionAmount,
Effect.andThen((amount) => amount * 2),
Effect.andThen((amount) => applyDiscount(amount, 5))
)
Effect.runPromise(result2).then(console.log)
// Output: 190

@since2.0.0

andThen
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("no annotations again"))
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO fiber=#0 message="no annotations"
timestamp=... level=INFO fiber=#0 message=message1 key=value
timestamp=... level=INFO fiber=#0 message=message2 key=value
timestamp=... level=INFO fiber=#0 message="no annotations again"
*/

Effect 提供对日志跨度的内置支持,允许您测量和记录特定任务或代码段的持续时间。此功能有助于跟踪某些操作需要多长时间,让您更好地了解应用程序的性能。

示例(使用日志跨度测量任务持续时间)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
// 模拟延迟以表示任务需要时间
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("1 second")
// 记录表示作业完成的消息
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("The job is finished!")
}).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
// 应用标记为 "myspan" 的日志跨度来测量
// 此操作的持续时间
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const withLogSpan: (label: string) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Adds a log span to an effect for tracking and logging its execution duration.

Details

This function wraps an effect with a log span, providing performance monitoring and debugging capabilities. The log span tracks the duration of the wrapped effect and logs it with the specified label. This is particularly useful when analyzing time-sensitive operations or understanding the execution time of specific tasks in your application.

The logged output will include the label and the total time taken for the operation. The span information is included in the log metadata, making it easy to trace performance metrics in logs.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.sleep("1 second")
yield* Effect.log("The job is finished!")
}).pipe(Effect.withLogSpan("myspan"))
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message="The job is finished!" myspan=1011ms

@since2.0.0

withLogSpan
("myspan")
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO fiber=#0 message="The job is finished!" myspan=1011ms
*/

有时,也许在测试执行期间,您可能希望在应用程序中禁用默认日志记录。Effect 提供了几种在需要时关闭日志记录的方法。在本节中,我们将了解在 Effect 框架中禁用日志记录的不同方法。

示例(使用 Logger.withMinimumLogLevel

禁用日志记录的一种便捷方法是使用 Logger.withMinimumLogLevel 函数。这允许您将最小日志级别设置为 None,有效地关闭所有日志输出。

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
,
import LogLevel
LogLevel
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("Executing task...")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("100 millis")
var console: Console

The console module provides a simple debugging console that is similar to the JavaScript console mechanism provided by web browsers.

The module exports two specific components:

  • A Console class with methods such as console.log(), console.error() and console.warn() that can be used to write to any Node.js stream.
  • A global console instance configured to write to process.stdout and process.stderr. The global console can be used without importing the node:console module.

Warning: The global console object's methods are neither consistently synchronous like the browser APIs they resemble, nor are they consistently asynchronous like all other Node.js streams. See the note on process I/O for more information.

Example using the global console:

console.log('hello world');
// Prints: hello world, to stdout
console.log('hello %s', 'world');
// Prints: hello world, to stdout
console.error(new Error('Whoops, something bad happened'));
// Prints error message and stack trace to stderr:
// Error: Whoops, something bad happened
// at [eval]:5:15
// at Script.runInThisContext (node:vm:132:18)
// at Object.runInThisContext (node:vm:309:38)
// at node:internal/process/execution:77:19
// at [eval]-wrapper:6:22
// at evalScript (node:internal/process/execution:76:60)
// at node:internal/main/eval_string:23:3
const name = 'Will Robinson';
console.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to stderr

Example using the Console class:

const out = getStreamSomehow();
const err = getStreamSomehow();
const myConsole = new console.Console(out, err);
myConsole.log('hello world');
// Prints: hello world, to out
myConsole.log('hello %s', 'world');
// Prints: hello world, to out
myConsole.error(new Error('Whoops, something bad happened'));
// Prints: [Error: Whoops, something bad happened], to err
const name = 'Will Robinson';
myConsole.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to err

@seesource

console
.
Console.log(message?: any, ...optionalParams: any[]): void

Prints to stdout with newline. Multiple arguments can be passed, with the first used as the primary message and all additional used as substitution values similar to printf(3) (the arguments are all passed to util.format()).

const count = 5;
console.log('count: %d', count);
// Prints: count: 5, to stdout
console.log('count:', count);
// Prints: count: 5, to stdout

See util.format() for more information.

@sincev0.1.100

log
("task done")
})
// 默认行为:启用日志记录
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
timestamp=... level=INFO fiber=#0 message="Executing task..."
task done
*/
// 通过将最小日志级别设置为 'None' 来禁用日志记录
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
.
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Logger
Logger
.
const withMinimumLogLevel: (level: LogLevel.LogLevel) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Sets the minimum log level for subsequent logging operations, allowing control over which log messages are displayed based on their severity.

@example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

withMinimumLogLevel
(
import LogLevel
LogLevel
.
const None: LogLevel.LogLevel

@since2.0.0

@since2.0.0

None
)))
/*
Output:
task done
*/

示例(使用层)

禁用日志记录的另一种方法是创建一个将最小日志级别设置为 LogLevel.None 的层,有效地关闭所有日志输出。

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
,
import LogLevel
LogLevel
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("Executing task...")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("100 millis")
var console: Console

The console module provides a simple debugging console that is similar to the JavaScript console mechanism provided by web browsers.

The module exports two specific components:

  • A Console class with methods such as console.log(), console.error() and console.warn() that can be used to write to any Node.js stream.
  • A global console instance configured to write to process.stdout and process.stderr. The global console can be used without importing the node:console module.

Warning: The global console object's methods are neither consistently synchronous like the browser APIs they resemble, nor are they consistently asynchronous like all other Node.js streams. See the note on process I/O for more information.

Example using the global console:

console.log('hello world');
// Prints: hello world, to stdout
console.log('hello %s', 'world');
// Prints: hello world, to stdout
console.error(new Error('Whoops, something bad happened'));
// Prints error message and stack trace to stderr:
// Error: Whoops, something bad happened
// at [eval]:5:15
// at Script.runInThisContext (node:vm:132:18)
// at Object.runInThisContext (node:vm:309:38)
// at node:internal/process/execution:77:19
// at [eval]-wrapper:6:22
// at evalScript (node:internal/process/execution:76:60)
// at node:internal/main/eval_string:23:3
const name = 'Will Robinson';
console.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to stderr

Example using the Console class:

const out = getStreamSomehow();
const err = getStreamSomehow();
const myConsole = new console.Console(out, err);
myConsole.log('hello world');
// Prints: hello world, to out
myConsole.log('hello %s', 'world');
// Prints: hello world, to out
myConsole.error(new Error('Whoops, something bad happened'));
// Prints: [Error: Whoops, something bad happened], to err
const name = 'Will Robinson';
myConsole.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to err

@seesource

console
.
Console.log(message?: any, ...optionalParams: any[]): void

Prints to stdout with newline. Multiple arguments can be passed, with the first used as the primary message and all additional used as substitution values similar to printf(3) (the arguments are all passed to util.format()).

const count = 5;
console.log('count: %d', count);
// Prints: count: 5, to stdout
console.log('count:', count);
// Prints: count: 5, to stdout

See util.format() for more information.

@sincev0.1.100

log
("task done")
})
// 创建禁用日志记录的层
const
const layer: Layer<never, never, never>
layer
=
import Logger
Logger
.
const minimumLogLevel: (level: LogLevel.LogLevel) => Layer<never>

Sets the minimum log level for logging operations, allowing control over which log messages are displayed based on their severity.

@example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("Executing task...")
yield* Effect.sleep("100 millis")
console.log("task done")
})
// Logging disabled using a layer
Effect.runFork(program.pipe(Effect.provide(Logger.minimumLogLevel(LogLevel.None))))
// task done

@since2.0.0

minimumLogLevel
(
import LogLevel
LogLevel
.
const None: LogLevel.LogLevel

@since2.0.0

@since2.0.0

None
)
// 应用层以禁用日志记录
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
.
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const provide: <never, never, never>(layer: Layer<never, never, never>) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, never>> (+9 overloads)

Provides necessary dependencies to an effect, removing its environmental requirements.

Details

This function allows you to supply the required environment for an effect. The environment can be provided in the form of one or more Layers, a Context, a Runtime, or a ManagedRuntime. Once the environment is provided, the effect can run without requiring external dependencies.

You can compose layers to create a modular and reusable way of setting up the environment for effects. For example, layers can be used to configure databases, logging services, or any other required dependencies.

Example

import { Context, Effect, Layer } from "effect"
class Database extends Context.Tag("Database")<
Database,
{ readonly query: (sql: string) => Effect.Effect<Array<unknown>> }
>() {}
const DatabaseLive = Layer.succeed(
Database,
{
// Simulate a database query
query: (sql: string) => Effect.log(`Executing query: ${sql}`).pipe(Effect.as([]))
}
)
// ┌─── Effect<unknown[], never, Database>
// ▼
const program = Effect.gen(function*() {
const database = yield* Database
const result = yield* database.query("SELECT * FROM users")
return result
})
// ┌─── Effect<unknown[], never, never>
// ▼
const runnable = Effect.provide(program, DatabaseLive)
Effect.runPromise(runnable).then(console.log)
// Output:
// timestamp=... level=INFO fiber=#0 message="Executing query: SELECT * FROM users"
// []

@seeprovideService for providing a service to an effect.

@since2.0.0

provide
(
const layer: Layer<never, never, never>
layer
)))
/*
Output:
task done
*/

示例(使用自定义运行时)

您还可以通过创建包含关闭日志记录配置的自定义运行时来禁用日志记录:

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
,
import LogLevel
LogLevel
,
import ManagedRuntime
ManagedRuntime
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("Executing task...")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("100 millis")
var console: Console

The console module provides a simple debugging console that is similar to the JavaScript console mechanism provided by web browsers.

The module exports two specific components:

  • A Console class with methods such as console.log(), console.error() and console.warn() that can be used to write to any Node.js stream.
  • A global console instance configured to write to process.stdout and process.stderr. The global console can be used without importing the node:console module.

Warning: The global console object's methods are neither consistently synchronous like the browser APIs they resemble, nor are they consistently asynchronous like all other Node.js streams. See the note on process I/O for more information.

Example using the global console:

console.log('hello world');
// Prints: hello world, to stdout
console.log('hello %s', 'world');
// Prints: hello world, to stdout
console.error(new Error('Whoops, something bad happened'));
// Prints error message and stack trace to stderr:
// Error: Whoops, something bad happened
// at [eval]:5:15
// at Script.runInThisContext (node:vm:132:18)
// at Object.runInThisContext (node:vm:309:38)
// at node:internal/process/execution:77:19
// at [eval]-wrapper:6:22
// at evalScript (node:internal/process/execution:76:60)
// at node:internal/main/eval_string:23:3
const name = 'Will Robinson';
console.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to stderr

Example using the Console class:

const out = getStreamSomehow();
const err = getStreamSomehow();
const myConsole = new console.Console(out, err);
myConsole.log('hello world');
// Prints: hello world, to out
myConsole.log('hello %s', 'world');
// Prints: hello world, to out
myConsole.error(new Error('Whoops, something bad happened'));
// Prints: [Error: Whoops, something bad happened], to err
const name = 'Will Robinson';
myConsole.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to err

@seesource

console
.
Console.log(message?: any, ...optionalParams: any[]): void

Prints to stdout with newline. Multiple arguments can be passed, with the first used as the primary message and all additional used as substitution values similar to printf(3) (the arguments are all passed to util.format()).

const count = 5;
console.log('count: %d', count);
// Prints: count: 5, to stdout
console.log('count:', count);
// Prints: count: 5, to stdout

See util.format() for more information.

@sincev0.1.100

log
("task done")
})
// 创建禁用日志记录的自定义运行时
const
const customRuntime: ManagedRuntime.ManagedRuntime<never, never>
customRuntime
=
import ManagedRuntime
ManagedRuntime
.
const make: <never, never>(layer: Layer<never, never, never>, memoMap?: MemoMap | undefined) => ManagedRuntime.ManagedRuntime<never, never>

Convert a Layer into an ManagedRuntime, that can be used to run Effect's using your services.

@since2.0.0

@example

import { Console, Effect, Layer, ManagedRuntime } from "effect"
class Notifications extends Effect.Tag("Notifications")<
Notifications,
{ readonly notify: (message: string) => Effect.Effect<void> }
>() {
static Live = Layer.succeed(this, { notify: (message) => Console.log(message) })
}
async function main() {
const runtime = ManagedRuntime.make(Notifications.Live)
await runtime.runPromise(Notifications.notify("Hello, world!"))
await runtime.dispose()
}
main()

make
(
import Logger
Logger
.
const minimumLogLevel: (level: LogLevel.LogLevel) => Layer<never>

Sets the minimum log level for logging operations, allowing control over which log messages are displayed based on their severity.

@example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("Executing task...")
yield* Effect.sleep("100 millis")
console.log("task done")
})
// Logging disabled using a layer
Effect.runFork(program.pipe(Effect.provide(Logger.minimumLogLevel(LogLevel.None))))
// task done

@since2.0.0

minimumLogLevel
(
import LogLevel
LogLevel
.
const None: LogLevel.LogLevel

@since2.0.0

@since2.0.0

None
)
)
// 使用自定义运行时运行程序
const customRuntime: ManagedRuntime.ManagedRuntime<never, never>
customRuntime
.
ManagedRuntime<never, never>.runFork: <void, never>(self: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Executes the effect using the provided Scheduler or using the global Scheduler if not provided

runFork
(
const program: Effect.Effect<void, never, never>
program
)
/*
Output:
task done
*/

要从配置动态加载日志级别并将其应用于程序,可以使用 Logger.minimumLogLevel 层。这允许您的应用程序根据外部配置调整其日志记录行为。

示例(从配置加载日志级别)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Config
Config
,
import Logger
Logger
,
import Layer
Layer
,
import ConfigProvider
ConfigProvider
,
import LogLevel
LogLevel
} from "effect"
// 模拟带有日志的程序
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logError: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the ERROR log level.

Details

This function logs messages at the ERROR level, suitable for reporting application errors or failures. These logs are typically used for unexpected issues that need immediate attention.

@since2.0.0

logError
("ERROR!")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logWarning: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the WARNING log level.

Details

This function logs messages at the WARNING level, suitable for highlighting potential issues that are not errors but may require attention. These messages indicate that something unexpected occurred or might lead to errors in the future.

@since2.0.0

logWarning
("WARNING!")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logInfo: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the INFO log level.

Details

This function logs messages at the INFO level, suitable for general application events or operational messages. INFO logs are shown by default and are commonly used for highlighting normal, non-error operations.

@since2.0.0

logInfo
("INFO!")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logDebug: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the DEBUG log level.

Details

This function logs messages at the DEBUG level, which is typically used for diagnosing application behavior during development. DEBUG messages provide less detailed information than TRACE logs but are still not shown by default. To view these logs, adjust the log level using Logger.withMinimumLogLevel.

Example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

logDebug
("DEBUG!")
})
// 从配置加载日志级别并将其作为层应用
const
const LogLevelLive: Layer.Layer<never, ConfigError, never>
LogLevelLive
=
import Config
Config
.
const logLevel: (name?: string) => Config.Config<LogLevel.LogLevel>

Constructs a config for a LogLevel value.

@since2.0.0

logLevel
("LOG_LEVEL").
Pipeable.pipe<Config.Config<LogLevel.LogLevel>, Effect.Effect<Layer.Layer<never, never, never>, ConfigError, never>, Layer.Layer<never, ConfigError, never>>(this: Config.Config<...>, ab: (_: Config.Config<LogLevel.LogLevel>) => Effect.Effect<Layer.Layer<never, never, never>, ConfigError, never>, bc: (_: Effect.Effect<Layer.Layer<never, never, never>, ConfigError, never>) => Layer.Layer<never, ConfigError, never>): Layer.Layer<...> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const andThen: <LogLevel.LogLevel, Layer.Layer<never, never, never>>(f: (a: LogLevel.LogLevel) => Layer.Layer<never, never, never>) => <E, R>(self: Effect.Effect<LogLevel.LogLevel, E, R>) => Effect.Effect<Layer.Layer<never, never, never>, E, R> (+3 overloads)

Chains two actions, where the second action can depend on the result of the first.

Syntax

const transformedEffect = pipe(myEffect, Effect.andThen(anotherEffect))
// or
const transformedEffect = Effect.andThen(myEffect, anotherEffect)
// or
const transformedEffect = myEffect.pipe(Effect.andThen(anotherEffect))

When to Use

Use andThen when you need to run multiple actions in sequence, with the second action depending on the result of the first. This is useful for combining effects or handling computations that must happen in order.

Details

The second action can be:

  • A constant value (similar to

as

)

  • A function returning a value (similar to

map

)

  • A Promise
  • A function returning a Promise
  • An Effect
  • A function returning an Effect (similar to

flatMap

)

Note: andThen works well with both Option and Either types, treating them as effects.

Example (Applying a Discount Based on Fetched Amount)

import { pipe, Effect } from "effect"
// Function to apply a discount safely to a transaction amount
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
// Simulated asynchronous task to fetch a transaction amount from database
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
// Using Effect.map and Effect.flatMap
const result1 = pipe(
fetchTransactionAmount,
Effect.map((amount) => amount * 2),
Effect.flatMap((amount) => applyDiscount(amount, 5))
)
Effect.runPromise(result1).then(console.log)
// Output: 190
// Using Effect.andThen
const result2 = pipe(
fetchTransactionAmount,
Effect.andThen((amount) => amount * 2),
Effect.andThen((amount) => applyDiscount(amount, 5))
)
Effect.runPromise(result2).then(console.log)
// Output: 190

@since2.0.0

andThen
((
level: LogLevel.LogLevel
level
) =>
// 设置最小日志级别
import Logger
Logger
.
const minimumLogLevel: (level: LogLevel.LogLevel) => Layer.Layer<never>

Sets the minimum log level for logging operations, allowing control over which log messages are displayed based on their severity.

@example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("Executing task...")
yield* Effect.sleep("100 millis")
console.log("task done")
})
// Logging disabled using a layer
Effect.runFork(program.pipe(Effect.provide(Logger.minimumLogLevel(LogLevel.None))))
// task done

@since2.0.0

minimumLogLevel
(
level: LogLevel.LogLevel
level
)
),
import Layer
Layer
.
const unwrapEffect: <A, E1, R1, E, R>(self: Effect.Effect<Layer.Layer<A, E1, R1>, E, R>) => Layer.Layer<A, E | E1, R | R1>

@since2.0.0

unwrapEffect
// 将 Effect 转换为层
)
// 为程序提供加载的日志级别
const
const configured: Effect.Effect<void, ConfigError, never>
configured
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const provide: <void, never, never, never, ConfigError, never>(self: Effect.Effect<void, never, never>, layer: Layer.Layer<never, ConfigError, never>) => Effect.Effect<void, ConfigError, never> (+9 overloads)

Provides necessary dependencies to an effect, removing its environmental requirements.

Details

This function allows you to supply the required environment for an effect. The environment can be provided in the form of one or more Layers, a Context, a Runtime, or a ManagedRuntime. Once the environment is provided, the effect can run without requiring external dependencies.

You can compose layers to create a modular and reusable way of setting up the environment for effects. For example, layers can be used to configure databases, logging services, or any other required dependencies.

Example

import { Context, Effect, Layer } from "effect"
class Database extends Context.Tag("Database")<
Database,
{ readonly query: (sql: string) => Effect.Effect<Array<unknown>> }
>() {}
const DatabaseLive = Layer.succeed(
Database,
{
// Simulate a database query
query: (sql: string) => Effect.log(`Executing query: ${sql}`).pipe(Effect.as([]))
}
)
// ┌─── Effect<unknown[], never, Database>
// ▼
const program = Effect.gen(function*() {
const database = yield* Database
const result = yield* database.query("SELECT * FROM users")
return result
})
// ┌─── Effect<unknown[], never, never>
// ▼
const runnable = Effect.provide(program, DatabaseLive)
Effect.runPromise(runnable).then(console.log)
// Output:
// timestamp=... level=INFO fiber=#0 message="Executing query: SELECT * FROM users"
// []

@seeprovideService for providing a service to an effect.

@since2.0.0

provide
(
const program: Effect.Effect<void, never, never>
program
,
const LogLevelLive: Layer.Layer<never, ConfigError, never>
LogLevelLive
)
// 使用模拟配置提供者测试程序
const
const test: Effect.Effect<void, ConfigError, never>
test
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const provide: <void, ConfigError, never, never, never, never>(self: Effect.Effect<void, ConfigError, never>, layer: Layer.Layer<never, never, never>) => Effect.Effect<void, ConfigError, never> (+9 overloads)

Provides necessary dependencies to an effect, removing its environmental requirements.

Details

This function allows you to supply the required environment for an effect. The environment can be provided in the form of one or more Layers, a Context, a Runtime, or a ManagedRuntime. Once the environment is provided, the effect can run without requiring external dependencies.

You can compose layers to create a modular and reusable way of setting up the environment for effects. For example, layers can be used to configure databases, logging services, or any other required dependencies.

Example

import { Context, Effect, Layer } from "effect"
class Database extends Context.Tag("Database")<
Database,
{ readonly query: (sql: string) => Effect.Effect<Array<unknown>> }
>() {}
const DatabaseLive = Layer.succeed(
Database,
{
// Simulate a database query
query: (sql: string) => Effect.log(`Executing query: ${sql}`).pipe(Effect.as([]))
}
)
// ┌─── Effect<unknown[], never, Database>
// ▼
const program = Effect.gen(function*() {
const database = yield* Database
const result = yield* database.query("SELECT * FROM users")
return result
})
// ┌─── Effect<unknown[], never, never>
// ▼
const runnable = Effect.provide(program, DatabaseLive)
Effect.runPromise(runnable).then(console.log)
// Output:
// timestamp=... level=INFO fiber=#0 message="Executing query: SELECT * FROM users"
// []

@seeprovideService for providing a service to an effect.

@since2.0.0

provide
(
const configured: Effect.Effect<void, ConfigError, never>
configured
,
import Layer
Layer
.
const setConfigProvider: (configProvider: ConfigProvider.ConfigProvider) => Layer.Layer<never>

Sets the current ConfigProvider.

@since2.0.0

setConfigProvider
(
import ConfigProvider
ConfigProvider
.
const fromMap: (map: Map<string, string>, config?: Partial<ConfigProvider.ConfigProvider.FromMapConfig>) => ConfigProvider.ConfigProvider

Constructs a ConfigProvider using a map and the specified delimiter string, which determines how to split the keys in the map into path segments.

@since2.0.0

fromMap
(
new
var Map: MapConstructor
new <string, "ALL" | "FATAL" | "ERROR" | "WARN" | "INFO" | "DEBUG" | "TRACE" | "OFF">(iterable?: Iterable<readonly [string, "ALL" | "FATAL" | "ERROR" | "WARN" | "INFO" | "DEBUG" | "TRACE" | "OFF"]> | null | undefined) => Map<string, "ALL" | "FATAL" | "ERROR" | "WARN" | "INFO" | "DEBUG" | "TRACE" | "OFF"> (+3 overloads)
Map
([["LOG_LEVEL",
import LogLevel
LogLevel
.
const Warning: LogLevel.LogLevel

@since2.0.0

@since2.0.0

Warning
.
label: "ALL" | "FATAL" | "ERROR" | "WARN" | "INFO" | "DEBUG" | "TRACE" | "OFF"
label
]])
)
)
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, ConfigError>(effect: Effect.Effect<void, ConfigError, never>, options?: RunForkOptions) => RuntimeFiber<void, ConfigError>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const test: Effect.Effect<void, ConfigError, never>
test
)
/*
Output:
... level=ERROR fiber=#0 message=ERROR!
... level=WARN fiber=#0 message=WARNING!
*/

在本节中,您将学习如何定义自定义记录器并将其设置为应用程序中的默认记录器。自定义记录器让您可以控制日志消息的处理方式,例如将它们路由到外部服务、写入文件或以特定方式格式化日志。

您可以使用 Logger.make 函数定义自己的记录器。此函数允许您指定应如何处理日志消息。

示例(定义简单的自定义记录器)

import {
import Logger
Logger
} from "effect"
// 将日志消息输出到控制台的自定义记录器
const
const logger: Logger.Logger<unknown, void>
logger
=
import Logger
Logger
.
const make: <unknown, void>(log: (options: Logger.Logger<in Message, out Output>.Options<unknown>) => void) => Logger.Logger<unknown, void>

Creates a custom logger that formats log messages according to the provided function.

@example

import { Effect, Logger, LogLevel } from "effect"
const logger = Logger.make(({ logLevel, message }) => {
globalThis.console.log(`[${logLevel.label}] ${message}`)
})
const task1 = Effect.logDebug("task1 done")
const task2 = Effect.logDebug("task2 done")
const program = Effect.gen(function*() {
yield* Effect.log("start")
yield* task1
yield* task2
yield* Effect.log("done")
}).pipe(
Logger.withMinimumLogLevel(LogLevel.Debug),
Effect.provide(Logger.replace(Logger.defaultLogger, logger))
)
Effect.runFork(program)
// [INFO] start
// [DEBUG] task1 done
// [DEBUG] task2 done
// [INFO] done

@since2.0.0

make
(({
logLevel: LogLevel
logLevel
,
message: unknown
message
}) => {
module globalThis
globalThis
.
var console: Console

The console module provides a simple debugging console that is similar to the JavaScript console mechanism provided by web browsers.

The module exports two specific components:

  • A Console class with methods such as console.log(), console.error() and console.warn() that can be used to write to any Node.js stream.
  • A global console instance configured to write to process.stdout and process.stderr. The global console can be used without importing the node:console module.

Warning: The global console object's methods are neither consistently synchronous like the browser APIs they resemble, nor are they consistently asynchronous like all other Node.js streams. See the note on process I/O for more information.

Example using the global console:

console.log('hello world');
// Prints: hello world, to stdout
console.log('hello %s', 'world');
// Prints: hello world, to stdout
console.error(new Error('Whoops, something bad happened'));
// Prints error message and stack trace to stderr:
// Error: Whoops, something bad happened
// at [eval]:5:15
// at Script.runInThisContext (node:vm:132:18)
// at Object.runInThisContext (node:vm:309:38)
// at node:internal/process/execution:77:19
// at [eval]-wrapper:6:22
// at evalScript (node:internal/process/execution:76:60)
// at node:internal/main/eval_string:23:3
const name = 'Will Robinson';
console.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to stderr

Example using the Console class:

const out = getStreamSomehow();
const err = getStreamSomehow();
const myConsole = new console.Console(out, err);
myConsole.log('hello world');
// Prints: hello world, to out
myConsole.log('hello %s', 'world');
// Prints: hello world, to out
myConsole.error(new Error('Whoops, something bad happened'));
// Prints: [Error: Whoops, something bad happened], to err
const name = 'Will Robinson';
myConsole.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to err

@seesource

console
.
Console.log(message?: any, ...optionalParams: any[]): void

Prints to stdout with newline. Multiple arguments can be passed, with the first used as the primary message and all additional used as substitution values similar to printf(3) (the arguments are all passed to util.format()).

const count = 5;
console.log('count: %d', count);
// Prints: count: 5, to stdout
console.log('count:', count);
// Prints: count: 5, to stdout

See util.format() for more information.

@sincev0.1.100

log
(`[${
logLevel: LogLevel
logLevel
.
label: "ALL" | "FATAL" | "ERROR" | "WARN" | "INFO" | "DEBUG" | "TRACE" | "OFF"
label
}] ${
message: unknown
message
}`)
})

在此示例中,自定义记录器将消息记录到控制台,日志级别和消息格式化为 [LogLevel] Message

假设您有以下任务和一个记录一些消息的程序:

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
} from "effect"
4 collapsed lines
// 将日志消息输出到控制台的自定义记录器
const
const logger: Logger.Logger<unknown, void>
logger
=
import Logger
Logger
.
const make: <unknown, void>(log: (options: Logger.Logger<in Message, out Output>.Options<unknown>) => void) => Logger.Logger<unknown, void>

Creates a custom logger that formats log messages according to the provided function.

@example

import { Effect, Logger, LogLevel } from "effect"
const logger = Logger.make(({ logLevel, message }) => {
globalThis.console.log(`[${logLevel.label}] ${message}`)
})
const task1 = Effect.logDebug("task1 done")
const task2 = Effect.logDebug("task2 done")
const program = Effect.gen(function*() {
yield* Effect.log("start")
yield* task1
yield* task2
yield* Effect.log("done")
}).pipe(
Logger.withMinimumLogLevel(LogLevel.Debug),
Effect.provide(Logger.replace(Logger.defaultLogger, logger))
)
Effect.runFork(program)
// [INFO] start
// [DEBUG] task1 done
// [DEBUG] task2 done
// [INFO] done

@since2.0.0

make
(({
logLevel: LogLevel
logLevel
,
message: unknown
message
}) => {
module globalThis
globalThis
.
var console: Console

The console module provides a simple debugging console that is similar to the JavaScript console mechanism provided by web browsers.

The module exports two specific components:

  • A Console class with methods such as console.log(), console.error() and console.warn() that can be used to write to any Node.js stream.
  • A global console instance configured to write to process.stdout and process.stderr. The global console can be used without importing the node:console module.

Warning: The global console object's methods are neither consistently synchronous like the browser APIs they resemble, nor are they consistently asynchronous like all other Node.js streams. See the note on process I/O for more information.

Example using the global console:

console.log('hello world');
// Prints: hello world, to stdout
console.log('hello %s', 'world');
// Prints: hello world, to stdout
console.error(new Error('Whoops, something bad happened'));
// Prints error message and stack trace to stderr:
// Error: Whoops, something bad happened
// at [eval]:5:15
// at Script.runInThisContext (node:vm:132:18)
// at Object.runInThisContext (node:vm:309:38)
// at node:internal/process/execution:77:19
// at [eval]-wrapper:6:22
// at evalScript (node:internal/process/execution:76:60)
// at node:internal/main/eval_string:23:3
const name = 'Will Robinson';
console.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to stderr

Example using the Console class:

const out = getStreamSomehow();
const err = getStreamSomehow();
const myConsole = new console.Console(out, err);
myConsole.log('hello world');
// Prints: hello world, to out
myConsole.log('hello %s', 'world');
// Prints: hello world, to out
myConsole.error(new Error('Whoops, something bad happened'));
// Prints: [Error: Whoops, something bad happened], to err
const name = 'Will Robinson';
myConsole.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to err

@seesource

console
.
Console.log(message?: any, ...optionalParams: any[]): void

Prints to stdout with newline. Multiple arguments can be passed, with the first used as the primary message and all additional used as substitution values similar to printf(3) (the arguments are all passed to util.format()).

const count = 5;
console.log('count: %d', count);
// Prints: count: 5, to stdout
console.log('count:', count);
// Prints: count: 5, to stdout

See util.format() for more information.

@sincev0.1.100

log
(`[${
logLevel: LogLevel
logLevel
.
label: "ALL" | "FATAL" | "ERROR" | "WARN" | "INFO" | "DEBUG" | "TRACE" | "OFF"
label
}] ${
message: unknown
message
}`)
})
const
const task1: Effect.Effect<void, never, never>
task1
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("2 seconds")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logDebug: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the DEBUG log level.

Details

This function logs messages at the DEBUG level, which is typically used for diagnosing application behavior during development. DEBUG messages provide less detailed information than TRACE logs but are still not shown by default. To view these logs, adjust the log level using Logger.withMinimumLogLevel.

Example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

logDebug
("task1 done")
})
const
const task2: Effect.Effect<void, never, never>
task2
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("1 second")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logDebug: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the DEBUG log level.

Details

This function logs messages at the DEBUG level, which is typically used for diagnosing application behavior during development. DEBUG messages provide less detailed information than TRACE logs but are still not shown by default. To view these logs, adjust the log level using Logger.withMinimumLogLevel.

Example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

logDebug
("task2 done")
})
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("start")
yield*
const task1: Effect.Effect<void, never, never>
task1
yield*
const task2: Effect.Effect<void, never, never>
task2
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("done")
})

要用自定义记录器替换默认记录器,可以使用 Logger.replace 函数。创建替换默认记录器的层后,使用 Effect.provide 将其提供给程序。

示例(用自定义记录器替换默认记录器)

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
,
import LogLevel
LogLevel
} from "effect"
21 collapsed lines
// 将日志消息输出到控制台的自定义记录器
const
const logger: Logger.Logger<unknown, void>
logger
=
import Logger
Logger
.
const make: <unknown, void>(log: (options: Logger.Logger<in Message, out Output>.Options<unknown>) => void) => Logger.Logger<unknown, void>

Creates a custom logger that formats log messages according to the provided function.

@example

import { Effect, Logger, LogLevel } from "effect"
const logger = Logger.make(({ logLevel, message }) => {
globalThis.console.log(`[${logLevel.label}] ${message}`)
})
const task1 = Effect.logDebug("task1 done")
const task2 = Effect.logDebug("task2 done")
const program = Effect.gen(function*() {
yield* Effect.log("start")
yield* task1
yield* task2
yield* Effect.log("done")
}).pipe(
Logger.withMinimumLogLevel(LogLevel.Debug),
Effect.provide(Logger.replace(Logger.defaultLogger, logger))
)
Effect.runFork(program)
// [INFO] start
// [DEBUG] task1 done
// [DEBUG] task2 done
// [INFO] done

@since2.0.0

make
(({
logLevel: LogLevel.LogLevel
logLevel
,
message: unknown
message
}) => {
module globalThis
globalThis
.
var console: Console

The console module provides a simple debugging console that is similar to the JavaScript console mechanism provided by web browsers.

The module exports two specific components:

  • A Console class with methods such as console.log(), console.error() and console.warn() that can be used to write to any Node.js stream.
  • A global console instance configured to write to process.stdout and process.stderr. The global console can be used without importing the node:console module.

Warning: The global console object's methods are neither consistently synchronous like the browser APIs they resemble, nor are they consistently asynchronous like all other Node.js streams. See the note on process I/O for more information.

Example using the global console:

console.log('hello world');
// Prints: hello world, to stdout
console.log('hello %s', 'world');
// Prints: hello world, to stdout
console.error(new Error('Whoops, something bad happened'));
// Prints error message and stack trace to stderr:
// Error: Whoops, something bad happened
// at [eval]:5:15
// at Script.runInThisContext (node:vm:132:18)
// at Object.runInThisContext (node:vm:309:38)
// at node:internal/process/execution:77:19
// at [eval]-wrapper:6:22
// at evalScript (node:internal/process/execution:76:60)
// at node:internal/main/eval_string:23:3
const name = 'Will Robinson';
console.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to stderr

Example using the Console class:

const out = getStreamSomehow();
const err = getStreamSomehow();
const myConsole = new console.Console(out, err);
myConsole.log('hello world');
// Prints: hello world, to out
myConsole.log('hello %s', 'world');
// Prints: hello world, to out
myConsole.error(new Error('Whoops, something bad happened'));
// Prints: [Error: Whoops, something bad happened], to err
const name = 'Will Robinson';
myConsole.warn(`Danger ${name}! Danger!`);
// Prints: Danger Will Robinson! Danger!, to err

@seesource

console
.
Console.log(message?: any, ...optionalParams: any[]): void

Prints to stdout with newline. Multiple arguments can be passed, with the first used as the primary message and all additional used as substitution values similar to printf(3) (the arguments are all passed to util.format()).

const count = 5;
console.log('count: %d', count);
// Prints: count: 5, to stdout
console.log('count:', count);
// Prints: count: 5, to stdout

See util.format() for more information.

@sincev0.1.100

log
(`[${
logLevel: LogLevel.LogLevel
logLevel
.
label: "ALL" | "FATAL" | "ERROR" | "WARN" | "INFO" | "DEBUG" | "TRACE" | "OFF"
label
}] ${
message: unknown
message
}`)
})
const
const task1: Effect.Effect<void, never, never>
task1
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("2 seconds")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logDebug: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the DEBUG log level.

Details

This function logs messages at the DEBUG level, which is typically used for diagnosing application behavior during development. DEBUG messages provide less detailed information than TRACE logs but are still not shown by default. To view these logs, adjust the log level using Logger.withMinimumLogLevel.

Example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

logDebug
("task1 done")
})
const
const task2: Effect.Effect<void, never, never>
task2
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const sleep: (duration: DurationInput) => Effect.Effect<void>

Suspends the execution of an effect for a specified Duration.

Details

This function pauses the execution of an effect for a given duration. It is asynchronous, meaning that it does not block the fiber executing the effect. Instead, the fiber is suspended during the delay period and can resume once the specified time has passed.

The duration can be specified using various formats supported by the Duration module, such as a string ("2 seconds") or numeric value representing milliseconds.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
console.log("Starting task...")
yield* Effect.sleep("3 seconds") // Waits for 3 seconds
console.log("Task completed!")
})
Effect.runFork(program)
// Output:
// Starting task...
// Task completed!

@since2.0.0

sleep
("1 second")
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const logDebug: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs messages at the DEBUG log level.

Details

This function logs messages at the DEBUG level, which is typically used for diagnosing application behavior during development. DEBUG messages provide less detailed information than TRACE logs but are still not shown by default. To view these logs, adjust the log level using Logger.withMinimumLogLevel.

Example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

logDebug
("task2 done")
})
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const gen: <YieldWrap<Effect.Effect<void, never, never>>, void>(f: (resume: Effect.Adapter) => Generator<YieldWrap<Effect.Effect<void, never, never>>, void, never>) => Effect.Effect<void, never, never> (+1 overload)

Provides a way to write effectful code using generator functions, simplifying control flow and error handling.

When to Use

Effect.gen allows you to write code that looks and behaves like synchronous code, but it can handle asynchronous tasks, errors, and complex control flow (like loops and conditions). It helps make asynchronous code more readable and easier to manage.

The generator functions work similarly to async/await but with more explicit control over the execution of effects. You can yield* values from effects and return the final result at the end.

Example

import { Effect } from "effect"
const addServiceCharge = (amount: number) => amount + 1
const applyDiscount = (
total: number,
discountRate: number
): Effect.Effect<number, Error> =>
discountRate === 0
? Effect.fail(new Error("Discount rate cannot be zero"))
: Effect.succeed(total - (total * discountRate) / 100)
const fetchTransactionAmount = Effect.promise(() => Promise.resolve(100))
const fetchDiscountRate = Effect.promise(() => Promise.resolve(5))
export const program = Effect.gen(function* () {
const transactionAmount = yield* fetchTransactionAmount
const discountRate = yield* fetchDiscountRate
const discountedAmount = yield* applyDiscount(
transactionAmount,
discountRate
)
const finalAmount = addServiceCharge(discountedAmount)
return `Final amount to charge: ${finalAmount}`
})

@since2.0.0

gen
(function* () {
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("start")
yield*
const task1: Effect.Effect<void, never, never>
task1
yield*
const task2: Effect.Effect<void, never, never>
task2
yield*
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("done")
})
// 用自定义记录器替换默认记录器
const
const layer: Layer<never, never, never>
layer
=
import Logger
Logger
.
const replace: <void, void>(self: Logger.Logger<unknown, void>, that: Logger.Logger<unknown, void>) => Layer<never> (+1 overload)

@since2.0.0

replace
(
import Logger
Logger
.
const defaultLogger: Logger.Logger<unknown, void>

@since2.0.0

defaultLogger
,
const logger: Logger.Logger<unknown, void>
logger
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
.
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, bc: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Logger
Logger
.
const withMinimumLogLevel: (level: LogLevel.LogLevel) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Sets the minimum log level for subsequent logging operations, allowing control over which log messages are displayed based on their severity.

@example

import { Effect, Logger, LogLevel } from "effect"
const program = Effect.logDebug("message1").pipe(Logger.withMinimumLogLevel(LogLevel.Debug))
Effect.runFork(program)
// timestamp=... level=DEBUG fiber=#0 message=message1

@since2.0.0

withMinimumLogLevel
(
import LogLevel
LogLevel
.
const Debug: LogLevel.LogLevel

@since2.0.0

@since2.0.0

Debug
),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const provide: <never, never, never>(layer: Layer<never, never, never>) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, never>> (+9 overloads)

Provides necessary dependencies to an effect, removing its environmental requirements.

Details

This function allows you to supply the required environment for an effect. The environment can be provided in the form of one or more Layers, a Context, a Runtime, or a ManagedRuntime. Once the environment is provided, the effect can run without requiring external dependencies.

You can compose layers to create a modular and reusable way of setting up the environment for effects. For example, layers can be used to configure databases, logging services, or any other required dependencies.

Example

import { Context, Effect, Layer } from "effect"
class Database extends Context.Tag("Database")<
Database,
{ readonly query: (sql: string) => Effect.Effect<Array<unknown>> }
>() {}
const DatabaseLive = Layer.succeed(
Database,
{
// Simulate a database query
query: (sql: string) => Effect.log(`Executing query: ${sql}`).pipe(Effect.as([]))
}
)
// ┌─── Effect<unknown[], never, Database>
// ▼
const program = Effect.gen(function*() {
const database = yield* Database
const result = yield* database.query("SELECT * FROM users")
return result
})
// ┌─── Effect<unknown[], never, never>
// ▼
const runnable = Effect.provide(program, DatabaseLive)
Effect.runPromise(runnable).then(console.log)
// Output:
// timestamp=... level=INFO fiber=#0 message="Executing query: SELECT * FROM users"
// []

@seeprovideService for providing a service to an effect.

@since2.0.0

provide
(
const layer: Layer<never, never, never>
layer
)
)
)

当您运行上述程序时,以下日志消息将打印到控制台:

Terminal window
[INFO] start
[DEBUG] task1 done
[DEBUG] task2 done
[INFO] done

Effect 提供了几个内置记录器,您可以根据日志记录需求使用它们。这些记录器提供不同的格式,每种格式都适合不同的环境或目的,例如开发、生产或与外部日志记录服务集成。

每个记录器都有两种形式:记录器本身,以及使用记录器并将其输出发送到 Console 默认服务的层。例如,structuredLogger 记录器以详细的基于对象的格式生成日志,而 structured 层使用相同的记录器并将输出写入 Console 服务。

stringLogger 记录器以人类可读的键值样式生成日志。这种格式在开发和生产中很常用,因为它简单且在控制台中易于阅读。

此记录器没有对应的层,因为它是默认记录器。

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("msg1", "msg2", ["msg3", "msg4"]).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, bc: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, cd: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const delay: (duration: DurationInput) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Delays the execution of an effect by a specified Duration.

**Details

This function postpones the execution of the provided effect by the specified duration. The duration can be provided in various formats supported by the Duration module.

Internally, this function does not block the thread; instead, it uses an efficient, non-blocking mechanism to introduce the delay.

Example

import { Console, Effect } from "effect"
const task = Console.log("Task executed")
const program = Console.log("start").pipe(
Effect.andThen(
// Delays the log message by 2 seconds
task.pipe(Effect.delay("2 seconds"))
)
)
Effect.runFork(program)
// Output:
// start
// Task executed

@since2.0.0

delay
("100 millis"),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const annotateLogs: (values: Record<string, unknown>) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+3 overloads)

Adds custom annotations to log entries generated within an effect.

Details

This function allows you to enhance log messages by appending additional context in the form of key-value pairs. These annotations are included in every log message created during the execution of the effect, making the logs more informative and easier to trace.

The annotations can be specified as a single key-value pair or as a record of multiple key-value pairs. This is particularly useful for tracking operations, debugging, or associating specific metadata with logs for better observability.

The annotated key-value pairs will appear alongside the log message in the output.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("message1")
yield* Effect.log("message2")
}).pipe(Effect.annotateLogs("taskId", "1234")) // Annotation as key/value pair
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message=message1 taskId=1234
// timestamp=... level=INFO fiber=#0 message=message2 taskId=1234

@seeannotateLogsScoped to add log annotations with a limited scope.

@since2.0.0

annotateLogs
({
key1: string
key1
: "value1",
key2: string
key2
: "value2" }),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const withLogSpan: (label: string) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Adds a log span to an effect for tracking and logging its execution duration.

Details

This function wraps an effect with a log span, providing performance monitoring and debugging capabilities. The log span tracks the duration of the wrapped effect and logs it with the specified label. This is particularly useful when analyzing time-sensitive operations or understanding the execution time of specific tasks in your application.

The logged output will include the label and the total time taken for the operation. The span information is included in the log metadata, making it easy to trace performance metrics in logs.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.sleep("1 second")
yield* Effect.log("The job is finished!")
}).pipe(Effect.withLogSpan("myspan"))
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message="The job is finished!" myspan=1011ms

@since2.0.0

withLogSpan
("myspan")
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
)

输出:

Terminal window
timestamp=2024-12-28T10:44:31.281Z level=INFO fiber=#0 message=msg1 message=msg2 message="[
\"msg3\",
\"msg4\"
]" myspan=102ms key2=value2 key1=value1

logfmtLogger 记录器以人类可读的键值格式生成日志,类似于 stringLogger 记录器。主要区别是 logfmtLogger 删除额外的空格以使日志更紧凑。

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("msg1", "msg2", ["msg3", "msg4"]).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, bc: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, cd: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const delay: (duration: DurationInput) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Delays the execution of an effect by a specified Duration.

**Details

This function postpones the execution of the provided effect by the specified duration. The duration can be provided in various formats supported by the Duration module.

Internally, this function does not block the thread; instead, it uses an efficient, non-blocking mechanism to introduce the delay.

Example

import { Console, Effect } from "effect"
const task = Console.log("Task executed")
const program = Console.log("start").pipe(
Effect.andThen(
// Delays the log message by 2 seconds
task.pipe(Effect.delay("2 seconds"))
)
)
Effect.runFork(program)
// Output:
// start
// Task executed

@since2.0.0

delay
("100 millis"),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const annotateLogs: (values: Record<string, unknown>) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+3 overloads)

Adds custom annotations to log entries generated within an effect.

Details

This function allows you to enhance log messages by appending additional context in the form of key-value pairs. These annotations are included in every log message created during the execution of the effect, making the logs more informative and easier to trace.

The annotations can be specified as a single key-value pair or as a record of multiple key-value pairs. This is particularly useful for tracking operations, debugging, or associating specific metadata with logs for better observability.

The annotated key-value pairs will appear alongside the log message in the output.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("message1")
yield* Effect.log("message2")
}).pipe(Effect.annotateLogs("taskId", "1234")) // Annotation as key/value pair
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message=message1 taskId=1234
// timestamp=... level=INFO fiber=#0 message=message2 taskId=1234

@seeannotateLogsScoped to add log annotations with a limited scope.

@since2.0.0

annotateLogs
({
key1: string
key1
: "value1",
key2: string
key2
: "value2" }),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const withLogSpan: (label: string) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Adds a log span to an effect for tracking and logging its execution duration.

Details

This function wraps an effect with a log span, providing performance monitoring and debugging capabilities. The log span tracks the duration of the wrapped effect and logs it with the specified label. This is particularly useful when analyzing time-sensitive operations or understanding the execution time of specific tasks in your application.

The logged output will include the label and the total time taken for the operation. The span information is included in the log metadata, making it easy to trace performance metrics in logs.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.sleep("1 second")
yield* Effect.log("The job is finished!")
}).pipe(Effect.withLogSpan("myspan"))
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message="The job is finished!" myspan=1011ms

@since2.0.0

withLogSpan
("myspan")
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
.
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const provide: <never, never, never>(layer: Layer<never, never, never>) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, never>> (+9 overloads)

Provides necessary dependencies to an effect, removing its environmental requirements.

Details

This function allows you to supply the required environment for an effect. The environment can be provided in the form of one or more Layers, a Context, a Runtime, or a ManagedRuntime. Once the environment is provided, the effect can run without requiring external dependencies.

You can compose layers to create a modular and reusable way of setting up the environment for effects. For example, layers can be used to configure databases, logging services, or any other required dependencies.

Example

import { Context, Effect, Layer } from "effect"
class Database extends Context.Tag("Database")<
Database,
{ readonly query: (sql: string) => Effect.Effect<Array<unknown>> }
>() {}
const DatabaseLive = Layer.succeed(
Database,
{
// Simulate a database query
query: (sql: string) => Effect.log(`Executing query: ${sql}`).pipe(Effect.as([]))
}
)
// ┌─── Effect<unknown[], never, Database>
// ▼
const program = Effect.gen(function*() {
const database = yield* Database
const result = yield* database.query("SELECT * FROM users")
return result
})
// ┌─── Effect<unknown[], never, never>
// ▼
const runnable = Effect.provide(program, DatabaseLive)
Effect.runPromise(runnable).then(console.log)
// Output:
// timestamp=... level=INFO fiber=#0 message="Executing query: SELECT * FROM users"
// []

@seeprovideService for providing a service to an effect.

@since2.0.0

provide
(
import Logger
Logger
.
const logFmt: Layer<never, never, never>

This logger outputs logs in a human-readable format that is easy to read during development or in a production console.

@example

import { Effect, Logger } from "effect"
const program = Effect.log("message1", "message2").pipe(
Effect.annotateLogs({ key1: "value1", key2: "value2" }),
Effect.withLogSpan("myspan")
)
Effect.runFork(program.pipe(Effect.provide(Logger.logFmt)))
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 myspan=0ms key2=value2 key1=value1

@since2.0.0

logFmt
)))

输出:

Terminal window
timestamp=2024-12-28T10:44:31.281Z level=INFO fiber=#0 message=msg1 message=msg2 message="[\"msg3\",\"msg4\"]" myspan=102ms key2=value2 key1=value1

prettyLogger 记录器通过使用颜色和缩进来增强日志输出的可读性,在开发期间在控制台中可视化扫描日志时特别有用。

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("msg1", "msg2", ["msg3", "msg4"]).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, bc: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, cd: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const delay: (duration: DurationInput) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Delays the execution of an effect by a specified Duration.

**Details

This function postpones the execution of the provided effect by the specified duration. The duration can be provided in various formats supported by the Duration module.

Internally, this function does not block the thread; instead, it uses an efficient, non-blocking mechanism to introduce the delay.

Example

import { Console, Effect } from "effect"
const task = Console.log("Task executed")
const program = Console.log("start").pipe(
Effect.andThen(
// Delays the log message by 2 seconds
task.pipe(Effect.delay("2 seconds"))
)
)
Effect.runFork(program)
// Output:
// start
// Task executed

@since2.0.0

delay
("100 millis"),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const annotateLogs: (values: Record<string, unknown>) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+3 overloads)

Adds custom annotations to log entries generated within an effect.

Details

This function allows you to enhance log messages by appending additional context in the form of key-value pairs. These annotations are included in every log message created during the execution of the effect, making the logs more informative and easier to trace.

The annotations can be specified as a single key-value pair or as a record of multiple key-value pairs. This is particularly useful for tracking operations, debugging, or associating specific metadata with logs for better observability.

The annotated key-value pairs will appear alongside the log message in the output.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("message1")
yield* Effect.log("message2")
}).pipe(Effect.annotateLogs("taskId", "1234")) // Annotation as key/value pair
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message=message1 taskId=1234
// timestamp=... level=INFO fiber=#0 message=message2 taskId=1234

@seeannotateLogsScoped to add log annotations with a limited scope.

@since2.0.0

annotateLogs
({
key1: string
key1
: "value1",
key2: string
key2
: "value2" }),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const withLogSpan: (label: string) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Adds a log span to an effect for tracking and logging its execution duration.

Details

This function wraps an effect with a log span, providing performance monitoring and debugging capabilities. The log span tracks the duration of the wrapped effect and logs it with the specified label. This is particularly useful when analyzing time-sensitive operations or understanding the execution time of specific tasks in your application.

The logged output will include the label and the total time taken for the operation. The span information is included in the log metadata, making it easy to trace performance metrics in logs.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.sleep("1 second")
yield* Effect.log("The job is finished!")
}).pipe(Effect.withLogSpan("myspan"))
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message="The job is finished!" myspan=1011ms

@since2.0.0

withLogSpan
("myspan")
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
.
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const provide: <never, never, never>(layer: Layer<never, never, never>) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, never>> (+9 overloads)

Provides necessary dependencies to an effect, removing its environmental requirements.

Details

This function allows you to supply the required environment for an effect. The environment can be provided in the form of one or more Layers, a Context, a Runtime, or a ManagedRuntime. Once the environment is provided, the effect can run without requiring external dependencies.

You can compose layers to create a modular and reusable way of setting up the environment for effects. For example, layers can be used to configure databases, logging services, or any other required dependencies.

Example

import { Context, Effect, Layer } from "effect"
class Database extends Context.Tag("Database")<
Database,
{ readonly query: (sql: string) => Effect.Effect<Array<unknown>> }
>() {}
const DatabaseLive = Layer.succeed(
Database,
{
// Simulate a database query
query: (sql: string) => Effect.log(`Executing query: ${sql}`).pipe(Effect.as([]))
}
)
// ┌─── Effect<unknown[], never, Database>
// ▼
const program = Effect.gen(function*() {
const database = yield* Database
const result = yield* database.query("SELECT * FROM users")
return result
})
// ┌─── Effect<unknown[], never, never>
// ▼
const runnable = Effect.provide(program, DatabaseLive)
Effect.runPromise(runnable).then(console.log)
// Output:
// timestamp=... level=INFO fiber=#0 message="Executing query: SELECT * FROM users"
// []

@seeprovideService for providing a service to an effect.

@since2.0.0

provide
(
import Logger
Logger
.
const pretty: Layer<never, never, never>

The pretty logger utilizes the capabilities of the console API to generate visually engaging and color-enhanced log outputs. This feature is particularly useful for improving the readability of log messages during development and debugging processes.

@example

import { Effect, Logger } from "effect"
const program = Effect.log("message1", "message2").pipe(
Effect.annotateLogs({ key1: "value1", key2: "value2" }),
Effect.withLogSpan("myspan")
)
Effect.runFork(program.pipe(Effect.provide(Logger.pretty)))
// green --v v-- bold and cyan
// [07:51:54.434] INFO (#0) myspan=1ms: message1
// message2
// v-- bold
// key2: value2
// key1: value1

@since3.5.0

pretty
)))

输出:

Terminal window
[11:37:14.265] [32mINFO[0m (#0) myspan=101ms: [1;36mmsg1[0m
msg2
[ [32m'msg3'[0m, [32m'msg4'[0m ]
key2: value2
key1: value1

structuredLogger 记录器以详细的基于对象的格式生成日志。当您需要更可追踪的日志时,此格式很有用,特别是当其他系统分析它们或存储它们以供以后审查时。

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("msg1", "msg2", ["msg3", "msg4"]).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, bc: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, cd: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const delay: (duration: DurationInput) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Delays the execution of an effect by a specified Duration.

**Details

This function postpones the execution of the provided effect by the specified duration. The duration can be provided in various formats supported by the Duration module.

Internally, this function does not block the thread; instead, it uses an efficient, non-blocking mechanism to introduce the delay.

Example

import { Console, Effect } from "effect"
const task = Console.log("Task executed")
const program = Console.log("start").pipe(
Effect.andThen(
// Delays the log message by 2 seconds
task.pipe(Effect.delay("2 seconds"))
)
)
Effect.runFork(program)
// Output:
// start
// Task executed

@since2.0.0

delay
("100 millis"),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const annotateLogs: (values: Record<string, unknown>) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+3 overloads)

Adds custom annotations to log entries generated within an effect.

Details

This function allows you to enhance log messages by appending additional context in the form of key-value pairs. These annotations are included in every log message created during the execution of the effect, making the logs more informative and easier to trace.

The annotations can be specified as a single key-value pair or as a record of multiple key-value pairs. This is particularly useful for tracking operations, debugging, or associating specific metadata with logs for better observability.

The annotated key-value pairs will appear alongside the log message in the output.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("message1")
yield* Effect.log("message2")
}).pipe(Effect.annotateLogs("taskId", "1234")) // Annotation as key/value pair
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message=message1 taskId=1234
// timestamp=... level=INFO fiber=#0 message=message2 taskId=1234

@seeannotateLogsScoped to add log annotations with a limited scope.

@since2.0.0

annotateLogs
({
key1: string
key1
: "value1",
key2: string
key2
: "value2" }),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const withLogSpan: (label: string) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Adds a log span to an effect for tracking and logging its execution duration.

Details

This function wraps an effect with a log span, providing performance monitoring and debugging capabilities. The log span tracks the duration of the wrapped effect and logs it with the specified label. This is particularly useful when analyzing time-sensitive operations or understanding the execution time of specific tasks in your application.

The logged output will include the label and the total time taken for the operation. The span information is included in the log metadata, making it easy to trace performance metrics in logs.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.sleep("1 second")
yield* Effect.log("The job is finished!")
}).pipe(Effect.withLogSpan("myspan"))
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message="The job is finished!" myspan=1011ms

@since2.0.0

withLogSpan
("myspan")
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
.
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const provide: <never, never, never>(layer: Layer<never, never, never>) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, never>> (+9 overloads)

Provides necessary dependencies to an effect, removing its environmental requirements.

Details

This function allows you to supply the required environment for an effect. The environment can be provided in the form of one or more Layers, a Context, a Runtime, or a ManagedRuntime. Once the environment is provided, the effect can run without requiring external dependencies.

You can compose layers to create a modular and reusable way of setting up the environment for effects. For example, layers can be used to configure databases, logging services, or any other required dependencies.

Example

import { Context, Effect, Layer } from "effect"
class Database extends Context.Tag("Database")<
Database,
{ readonly query: (sql: string) => Effect.Effect<Array<unknown>> }
>() {}
const DatabaseLive = Layer.succeed(
Database,
{
// Simulate a database query
query: (sql: string) => Effect.log(`Executing query: ${sql}`).pipe(Effect.as([]))
}
)
// ┌─── Effect<unknown[], never, Database>
// ▼
const program = Effect.gen(function*() {
const database = yield* Database
const result = yield* database.query("SELECT * FROM users")
return result
})
// ┌─── Effect<unknown[], never, never>
// ▼
const runnable = Effect.provide(program, DatabaseLive)
Effect.runPromise(runnable).then(console.log)
// Output:
// timestamp=... level=INFO fiber=#0 message="Executing query: SELECT * FROM users"
// []

@seeprovideService for providing a service to an effect.

@since2.0.0

provide
(
import Logger
Logger
.
const structured: Layer<never, never, never>

The structured logger provides detailed log outputs, structured in a way that retains comprehensive traceability of the events, suitable for deeper analysis and troubleshooting.

@example

import { Effect, Logger } from "effect"
const program = Effect.log("message1", "message2").pipe(
Effect.annotateLogs({ key1: "value1", key2: "value2" }),
Effect.withLogSpan("myspan")
)
Effect.runFork(program.pipe(Effect.provide(Logger.structured)))
// {
// message: [ 'message1', 'message2' ],
// logLevel: 'INFO',
// timestamp: '2024-07-09T14:05:41.623Z',
// cause: undefined,
// annotations: { key2: 'value2', key1: 'value1' },
// spans: { myspan: 0 },
// fiberId: '#0'
// }

@since2.0.0

structured
)))

输出:

Terminal window
{
message: [ 'msg1', 'msg2', [ 'msg3', 'msg4' ] ],
logLevel: 'INFO',
timestamp: '2024-12-28T10:44:31.281Z',
cause: undefined,
annotations: { key2: 'value2', key1: 'value1' },
spans: { myspan: 102 },
fiberId: '#0'
}
FieldDescription
messageEither a single processed value or an array of processed values, depending on how many messages are logged.
logLevelA string that indicates the log level label (for example, “INFO” or “DEBUG”).
timestampAn ISO 8601 timestamp for when the log was generated (for example, “2024-01-01T00:00:00.000Z”).
causeA string that shows detailed error information, or undefined if no cause was provided.
annotationsAn object where each key is an annotation label and the corresponding value is parsed into a structured format (for instance, {"key": "value"}).
spansAn object mapping each span label to its duration in milliseconds, measured from its start time until the moment the logger was called (for example, {"myspan": 102}).
fiberIdThe identifier of the fiber that generated this log (for example, “#0”).

jsonLogger 记录器以 JSON 格式生成日志。这对于解析和存储 JSON 日志的工具或服务很有用。 它对 structuredLogger 记录器创建的对象调用 JSON.stringify

import {
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
,
import Logger
Logger
} from "effect"
const
const program: Effect.Effect<void, never, never>
program
=
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const log: (...message: ReadonlyArray<any>) => Effect.Effect<void, never, never>

Logs one or more messages or error causes at the current log level.

Details

This function provides a simple way to log messages or error causes during the execution of your effects. By default, logs are recorded at the INFO level, but this can be adjusted using other logging utilities (Logger.withMinimumLogLevel). Multiple items, including Cause instances, can be logged in a single call. When logging Cause instances, detailed error information is included in the log output.

The log output includes useful metadata like the current timestamp, log level, and fiber ID, making it suitable for debugging and tracking purposes. This function does not interrupt or alter the effect's execution flow.

Example

import { Cause, Effect } from "effect"
const program = Effect.log(
"message1",
"message2",
Cause.die("Oh no!"),
Cause.die("Oh uh!")
)
Effect.runFork(program)
// Output:
// timestamp=... level=INFO fiber=#0 message=message1 message=message2 cause="Error: Oh no!
// Error: Oh uh!"

@since2.0.0

log
("msg1", "msg2", ["msg3", "msg4"]).
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, bc: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>, cd: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const delay: (duration: DurationInput) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Delays the execution of an effect by a specified Duration.

**Details

This function postpones the execution of the provided effect by the specified duration. The duration can be provided in various formats supported by the Duration module.

Internally, this function does not block the thread; instead, it uses an efficient, non-blocking mechanism to introduce the delay.

Example

import { Console, Effect } from "effect"
const task = Console.log("Task executed")
const program = Console.log("start").pipe(
Effect.andThen(
// Delays the log message by 2 seconds
task.pipe(Effect.delay("2 seconds"))
)
)
Effect.runFork(program)
// Output:
// start
// Task executed

@since2.0.0

delay
("100 millis"),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const annotateLogs: (values: Record<string, unknown>) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+3 overloads)

Adds custom annotations to log entries generated within an effect.

Details

This function allows you to enhance log messages by appending additional context in the form of key-value pairs. These annotations are included in every log message created during the execution of the effect, making the logs more informative and easier to trace.

The annotations can be specified as a single key-value pair or as a record of multiple key-value pairs. This is particularly useful for tracking operations, debugging, or associating specific metadata with logs for better observability.

The annotated key-value pairs will appear alongside the log message in the output.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.log("message1")
yield* Effect.log("message2")
}).pipe(Effect.annotateLogs("taskId", "1234")) // Annotation as key/value pair
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message=message1 taskId=1234
// timestamp=... level=INFO fiber=#0 message=message2 taskId=1234

@seeannotateLogsScoped to add log annotations with a limited scope.

@since2.0.0

annotateLogs
({
key1: string
key1
: "value1",
key2: string
key2
: "value2" }),
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const withLogSpan: (label: string) => <A, E, R>(effect: Effect.Effect<A, E, R>) => Effect.Effect<A, E, R> (+1 overload)

Adds a log span to an effect for tracking and logging its execution duration.

Details

This function wraps an effect with a log span, providing performance monitoring and debugging capabilities. The log span tracks the duration of the wrapped effect and logs it with the specified label. This is particularly useful when analyzing time-sensitive operations or understanding the execution time of specific tasks in your application.

The logged output will include the label and the total time taken for the operation. The span information is included in the log metadata, making it easy to trace performance metrics in logs.

Example

import { Effect } from "effect"
const program = Effect.gen(function*() {
yield* Effect.sleep("1 second")
yield* Effect.log("The job is finished!")
}).pipe(Effect.withLogSpan("myspan"))
Effect.runFork(program)
// timestamp=... level=INFO fiber=#0 message="The job is finished!" myspan=1011ms

@since2.0.0

withLogSpan
("myspan")
)
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const runFork: <void, never>(effect: Effect.Effect<void, never, never>, options?: RunForkOptions) => RuntimeFiber<void, never>

Runs an effect in the background, returning a fiber that can be observed or interrupted.

Unless you specifically need a Promise or synchronous operation, runFork is a good default choice.

Details

This function is the foundational way to execute an effect in the background. It creates a "fiber," a lightweight, cooperative thread of execution that can be observed (to access its result), interrupted, or joined. Fibers are useful for concurrent programming and allow effects to run independently of the main program flow.

Once the effect is running in a fiber, you can monitor its progress, cancel it if necessary, or retrieve its result when it completes. If the effect fails, the fiber will propagate the failure, which you can observe and handle.

When to Use

Use this function when you need to run an effect in the background, especially if the effect is long-running or performs periodic tasks. It's suitable for tasks that need to run independently but might still need observation or management, like logging, monitoring, or scheduled tasks.

This function is ideal if you don't need the result immediately or if the effect is part of a larger concurrent workflow.

Example (Running an Effect in the Background)

import { Effect, Console, Schedule, Fiber } from "effect"
// ┌─── Effect<number, never, never>
// ▼
const program = Effect.repeat(
Console.log("running..."),
Schedule.spaced("200 millis")
)
// ┌─── RuntimeFiber<number, never>
// ▼
const fiber = Effect.runFork(program)
setTimeout(() => {
Effect.runFork(Fiber.interrupt(fiber))
}, 500)

@since2.0.0

runFork
(
const program: Effect.Effect<void, never, never>
program
.
Pipeable.pipe<Effect.Effect<void, never, never>, Effect.Effect<void, never, never>>(this: Effect.Effect<void, never, never>, ab: (_: Effect.Effect<void, never, never>) => Effect.Effect<void, never, never>): Effect.Effect<void, never, never> (+21 overloads)
pipe
(
import Effect

@since2.0.0

@since2.0.0

@since2.0.0

Effect
.
const provide: <never, never, never>(layer: Layer<never, never, never>) => <A, E, R>(self: Effect.Effect<A, E, R>) => Effect.Effect<A, E, Exclude<R, never>> (+9 overloads)

Provides necessary dependencies to an effect, removing its environmental requirements.

Details

This function allows you to supply the required environment for an effect. The environment can be provided in the form of one or more Layers, a Context, a Runtime, or a ManagedRuntime. Once the environment is provided, the effect can run without requiring external dependencies.

You can compose layers to create a modular and reusable way of setting up the environment for effects. For example, layers can be used to configure databases, logging services, or any other required dependencies.

Example

import { Context, Effect, Layer } from "effect"
class Database extends Context.Tag("Database")<
Database,
{ readonly query: (sql: string) => Effect.Effect<Array<unknown>> }
>() {}
const DatabaseLive = Layer.succeed(
Database,
{
// Simulate a database query
query: (sql: string) => Effect.log(`Executing query: ${sql}`).pipe(Effect.as([]))
}
)
// ┌─── Effect<unknown[], never, Database>
// ▼
const program = Effect.gen(function*() {
const database = yield* Database
const result = yield* database.query("SELECT * FROM users")
return result
})
// ┌─── Effect<unknown[], never, never>
// ▼
const runnable = Effect.provide(program, DatabaseLive)
Effect.runPromise(runnable).then(console.log)
// Output:
// timestamp=... level=INFO fiber=#0 message="Executing query: SELECT * FROM users"
// []

@seeprovideService for providing a service to an effect.

@since2.0.0

provide
(
import Logger
Logger
.
const json: Layer<never, never, never>

The json logger formats log entries as JSON objects, making them easy to integrate with logging systems that consume JSON data.

@example

import { Effect, Logger } from "effect"
const program = Effect.log("message1", "message2").pipe(
Effect.annotateLogs({ key1: "value1", key2: "value2" }),
Effect.withLogSpan("myspan")
)
Effect.runFork(program.pipe(Effect.provide(Logger.json)))
// {"message":["message1","message2"],"logLevel":"INFO","timestamp":"...","annotations":{"key2":"value2","key1":"value1"},"spans":{"myspan":0},"fiberId":"#0"}

@since2.0.0

json
)))

输出:

Terminal window
{"message":["msg1","msg2",["msg3","msg4"]],"logLevel":"INFO","timestamp":"2024-12-28T10:44:31.281Z","annotations":{"key2":"value2","key1":"value1"},"spans":{"myspan":102},"fiberId":"#0"}

Logger.zip 函数将两个记录器组合成一个新的记录器。这个新记录器将日志消息转发给两个原始记录器。

示例(组合两个记录器)

import { Effect, Logger } from "effect"
// 定义一个记录到控制台的自定义记录器
const logger = Logger.make(({ logLevel, message }) => {
globalThis.console.log(`[${logLevel.label}] ${message}`)
})
// 组合默认记录器和自定义记录器
//
// ┌─── Logger<unknown, [void, void]>
// ▼
const combined = Logger.zip(Logger.defaultLogger, logger)
const program = Effect.log("something")
Effect.runFork(
program.pipe(
// 用组合记录器替换默认记录器
Effect.provide(Logger.replace(Logger.defaultLogger, combined))
)
)
/*
Output:
timestamp=2025-01-09T13:50:58.655Z level=INFO fiber=#0 message=something
[INFO] something
*/