<Input, State>(
metric: Metric.Metric<Input, State>,
f: (duration: Duration.Duration) => Input
): <A, E, R>(self: Effect<A, E, R>) => Effect<A, E, R>
<State, E>(metric: Metric.Metric<Duration.Duration, State>): <A, R>(
self: Effect<A, E, R>
) => Effect<A, E, R>
<A, E, R, Input, State>(
self: Effect<A, E, R>,
metric: Metric.Metric<Input, State>,
f: (duration: Duration.Duration) => Input
): Effect<A, E, R>
<A, E, R, State>(
self: Effect<A, E, R>,
metric: Metric.Metric<Duration.Duration, State>
): Effect<A, E, R>Updates the provided Metric with the Duration of time (in nanoseconds)
that the wrapped Effect took to complete.
Details
Also accepts an optional function which can be used to map the Duration
that the wrapped Effect took to complete into a valid Input for the
Metric.
Example (Recording execution duration)
import { Effect, Metric } from "effect"
const executionTimer = Metric.timer("execution_time")
const program = Effect.sleep("100 millis").pipe(
Effect.trackDuration(executionTimer)
)
Effect.runPromise(program).then(() =>
Effect.runPromise(Metric.value(executionTimer)).then(console.log)
// Output: { count: 1, min: 100000000, max: 100000000, sum: 100000000 }
)Example (Mapping duration before tracking)
import { Duration, Effect, Metric } from "effect"
// Track execution time in milliseconds using custom mapping
const durationGauge = Metric.gauge("execution_millis")
const program = Effect.sleep("200 millis").pipe(
Effect.trackDuration(durationGauge, (duration) => Duration.toMillis(duration))
)
Effect.runPromise(program).then(() =>
Effect.runPromise(Metric.value(durationGauge)).then(console.log)
// Output: { value: 200 }
)export const const trackDuration: {
<Input, State>(
metric: Metric.Metric<Input, State>,
f: (duration: Duration.Duration) => Input
): <A, E, R>(
self: Effect<A, E, R>
) => Effect<A, E, R>
<State, E>(
metric: Metric.Metric<
Duration.Duration,
State
>
): <A, R>(
self: Effect<A, E, R>
) => Effect<A, E, R>
<A, E, R, Input, State>(
self: Effect<A, E, R>,
metric: Metric.Metric<Input, State>,
f: (duration: Duration.Duration) => Input
): Effect<A, E, R>
<A, E, R, State>(
self: Effect<A, E, R>,
metric: Metric.Metric<
Duration.Duration,
State
>
): Effect<A, E, R>
}
Updates the provided Metric with the Duration of time (in nanoseconds)
that the wrapped Effect took to complete.
Details
Also accepts an optional function which can be used to map the Duration
that the wrapped Effect took to complete into a valid Input for the
Metric.
Example (Recording execution duration)
import { Effect, Metric } from "effect"
const executionTimer = Metric.timer("execution_time")
const program = Effect.sleep("100 millis").pipe(
Effect.trackDuration(executionTimer)
)
Effect.runPromise(program).then(() =>
Effect.runPromise(Metric.value(executionTimer)).then(console.log)
// Output: { count: 1, min: 100000000, max: 100000000, sum: 100000000 }
)
Example (Mapping duration before tracking)
import { Duration, Effect, Metric } from "effect"
// Track execution time in milliseconds using custom mapping
const durationGauge = Metric.gauge("execution_millis")
const program = Effect.sleep("200 millis").pipe(
Effect.trackDuration(durationGauge, (duration) => Duration.toMillis(duration))
)
Effect.runPromise(program).then(() =>
Effect.runPromise(Metric.value(durationGauge)).then(console.log)
// Output: { value: 200 }
)
trackDuration: {
<function (type parameter) Input in <Input, State>(metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): <A, E, R>(self: Effect<A, E, R>) => Effect<A, E, R>Input, function (type parameter) State in <Input, State>(metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): <A, E, R>(self: Effect<A, E, R>) => Effect<A, E, R>State>(
metric: Metric.Metric<Input, State>(parameter) metric: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
import MetricMetric.interface Metric<in Input, out State>A Metric<Input, State> represents a concurrent metric which accepts update
values of type Input and are aggregated to a value of type State.
Details
For example, a counter metric would have type Metric<number, number>,
representing the fact that the metric can be updated with numbers (the amount
to increment or decrement the counter by), and the state of the counter is a
number.
There are five primitive metric types supported by Effect:
- Counters
- Frequencies
- Gauges
- Histograms
- Summaries
Example (Using multiple metric types)
import { Data, Effect, Metric } from "effect"
class MetricExample extends Data.TaggedError("MetricExample")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter: Metric.Counter<number> = Metric.counter("requests", {
description: "Total requests processed"
})
const memoryGauge: Metric.Gauge<number> = Metric.gauge("memory_usage", {
description: "Current memory usage in MB"
})
const statusFrequency: Metric.Frequency = Metric.frequency("status_codes", {
description: "HTTP status code frequency"
})
// All metrics share the same interface for updates and reads
yield* Metric.update(requestCounter, 1)
yield* Metric.update(memoryGauge, 128)
yield* Metric.update(statusFrequency, "200")
// All metrics can be read with Metric.value
const counterState = yield* Metric.value(requestCounter)
const gaugeState = yield* Metric.value(memoryGauge)
const frequencyState = yield* Metric.value(statusFrequency)
// Metrics have common properties accessible through the interface:
// - id: unique identifier
// - type: metric type ("Counter", "Gauge", "Frequency", etc.)
// - description: optional human-readable description
// - attributes: optional key-value attributes for tagging
return {
counter: {
id: requestCounter.id,
type: requestCounter.type,
state: counterState
},
gauge: { id: memoryGauge.id, type: memoryGauge.type, state: gaugeState },
frequency: {
id: statusFrequency.id,
type: statusFrequency.type,
state: frequencyState
}
}
})
The Metric namespace provides a comprehensive system for collecting, aggregating, and observing
application metrics in Effect applications.
Example (Collecting application metrics)
import { Data, Effect, Metric } from "effect"
class MetricsError extends Data.TaggedError("MetricsError")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter = Metric.counter("http_requests_total")
const responseTimeHistogram = Metric.histogram("http_response_time", {
boundaries: Metric.linearBoundaries({ start: 0, width: 10, count: 10 })
})
const activeConnectionsGauge = Metric.gauge("active_connections")
const statusFrequency = Metric.frequency("http_status_codes")
// Update metrics
yield* Metric.update(requestCounter, 1)
yield* Metric.update(responseTimeHistogram, 45.2)
yield* Metric.update(activeConnectionsGauge, 12)
yield* Metric.update(statusFrequency, "200")
// Get metric values
const counterValue = yield* Metric.value(requestCounter)
const histogramValue = yield* Metric.value(responseTimeHistogram)
const gaugeValue = yield* Metric.value(activeConnectionsGauge)
const frequencyValue = yield* Metric.value(statusFrequency)
return {
counter: counterValue,
histogram: histogramValue,
gauge: gaugeValue,
frequency: frequencyValue
}
})
Metric<function (type parameter) Input in <Input, State>(metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): <A, E, R>(self: Effect<A, E, R>) => Effect<A, E, R>Input, function (type parameter) State in <Input, State>(metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): <A, E, R>(self: Effect<A, E, R>) => Effect<A, E, R>State>,
f: (duration: Duration.Duration) => Inputf: (duration: Duration.Duration(parameter) duration: {
value: DurationValue;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
import DurationDuration.type Duration.Duration = /*unresolved*/ anyDuration) => function (type parameter) Input in <Input, State>(metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): <A, E, R>(self: Effect<A, E, R>) => Effect<A, E, R>Input
): <function (type parameter) A in <A, E, R>(self: Effect<A, E, R>): Effect<A, E, R>A, function (type parameter) E in <A, E, R>(self: Effect<A, E, R>): Effect<A, E, R>E, function (type parameter) R in <A, E, R>(self: Effect<A, E, R>): Effect<A, E, R>R>(self: Effect<A, E, R>(parameter) self: {
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, E, R>(self: Effect<A, E, R>): Effect<A, E, R>A, function (type parameter) E in <A, E, R>(self: Effect<A, E, R>): Effect<A, E, R>E, function (type parameter) R in <A, E, R>(self: Effect<A, E, R>): Effect<A, E, R>R>) => interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, E, R>(self: Effect<A, E, R>): Effect<A, E, R>A, function (type parameter) E in <A, E, R>(self: Effect<A, E, R>): Effect<A, E, R>E, function (type parameter) R in <A, E, R>(self: Effect<A, E, R>): Effect<A, E, R>R>
<function (type parameter) State in <State, E>(metric: Metric.Metric<Duration.Duration, State>): <A, R>(self: Effect<A, E, R>) => Effect<A, E, R>State, function (type parameter) E in <State, E>(metric: Metric.Metric<Duration.Duration, State>): <A, R>(self: Effect<A, E, R>) => Effect<A, E, R>E>(
metric: Metric.Metric<Duration.Duration, State>(parameter) metric: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
import MetricMetric.interface Metric<in Input, out State>A Metric<Input, State> represents a concurrent metric which accepts update
values of type Input and are aggregated to a value of type State.
Details
For example, a counter metric would have type Metric<number, number>,
representing the fact that the metric can be updated with numbers (the amount
to increment or decrement the counter by), and the state of the counter is a
number.
There are five primitive metric types supported by Effect:
- Counters
- Frequencies
- Gauges
- Histograms
- Summaries
Example (Using multiple metric types)
import { Data, Effect, Metric } from "effect"
class MetricExample extends Data.TaggedError("MetricExample")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter: Metric.Counter<number> = Metric.counter("requests", {
description: "Total requests processed"
})
const memoryGauge: Metric.Gauge<number> = Metric.gauge("memory_usage", {
description: "Current memory usage in MB"
})
const statusFrequency: Metric.Frequency = Metric.frequency("status_codes", {
description: "HTTP status code frequency"
})
// All metrics share the same interface for updates and reads
yield* Metric.update(requestCounter, 1)
yield* Metric.update(memoryGauge, 128)
yield* Metric.update(statusFrequency, "200")
// All metrics can be read with Metric.value
const counterState = yield* Metric.value(requestCounter)
const gaugeState = yield* Metric.value(memoryGauge)
const frequencyState = yield* Metric.value(statusFrequency)
// Metrics have common properties accessible through the interface:
// - id: unique identifier
// - type: metric type ("Counter", "Gauge", "Frequency", etc.)
// - description: optional human-readable description
// - attributes: optional key-value attributes for tagging
return {
counter: {
id: requestCounter.id,
type: requestCounter.type,
state: counterState
},
gauge: { id: memoryGauge.id, type: memoryGauge.type, state: gaugeState },
frequency: {
id: statusFrequency.id,
type: statusFrequency.type,
state: frequencyState
}
}
})
The Metric namespace provides a comprehensive system for collecting, aggregating, and observing
application metrics in Effect applications.
Example (Collecting application metrics)
import { Data, Effect, Metric } from "effect"
class MetricsError extends Data.TaggedError("MetricsError")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter = Metric.counter("http_requests_total")
const responseTimeHistogram = Metric.histogram("http_response_time", {
boundaries: Metric.linearBoundaries({ start: 0, width: 10, count: 10 })
})
const activeConnectionsGauge = Metric.gauge("active_connections")
const statusFrequency = Metric.frequency("http_status_codes")
// Update metrics
yield* Metric.update(requestCounter, 1)
yield* Metric.update(responseTimeHistogram, 45.2)
yield* Metric.update(activeConnectionsGauge, 12)
yield* Metric.update(statusFrequency, "200")
// Get metric values
const counterValue = yield* Metric.value(requestCounter)
const histogramValue = yield* Metric.value(responseTimeHistogram)
const gaugeValue = yield* Metric.value(activeConnectionsGauge)
const frequencyValue = yield* Metric.value(statusFrequency)
return {
counter: counterValue,
histogram: histogramValue,
gauge: gaugeValue,
frequency: frequencyValue
}
})
Metric<import DurationDuration.type Duration.Duration = /*unresolved*/ anyDuration, function (type parameter) State in <State, E>(metric: Metric.Metric<Duration.Duration, State>): <A, R>(self: Effect<A, E, R>) => Effect<A, E, R>State>
): <function (type parameter) A in <A, R>(self: Effect<A, E, R>): Effect<A, E, R>A, function (type parameter) R in <A, R>(self: Effect<A, E, R>): Effect<A, E, R>R>(self: Effect<A, E, R>(parameter) self: {
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, R>(self: Effect<A, E, R>): Effect<A, E, R>A, function (type parameter) E in <State, E>(metric: Metric.Metric<Duration.Duration, State>): <A, R>(self: Effect<A, E, R>) => Effect<A, E, R>E, function (type parameter) R in <A, R>(self: Effect<A, E, R>): Effect<A, E, R>R>) => interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, R>(self: Effect<A, E, R>): Effect<A, E, R>A, function (type parameter) E in <State, E>(metric: Metric.Metric<Duration.Duration, State>): <A, R>(self: Effect<A, E, R>) => Effect<A, E, R>E, function (type parameter) R in <A, R>(self: Effect<A, E, R>): Effect<A, E, R>R>
<function (type parameter) A in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>A, function (type parameter) E in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>E, function (type parameter) R in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>R, function (type parameter) Input in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>Input, function (type parameter) State in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>State>(
self: Effect<A, E, R>(parameter) self: {
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>A, function (type parameter) E in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>E, function (type parameter) R in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>R>,
metric: Metric.Metric<Input, State>(parameter) metric: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
import MetricMetric.interface Metric<in Input, out State>A Metric<Input, State> represents a concurrent metric which accepts update
values of type Input and are aggregated to a value of type State.
Details
For example, a counter metric would have type Metric<number, number>,
representing the fact that the metric can be updated with numbers (the amount
to increment or decrement the counter by), and the state of the counter is a
number.
There are five primitive metric types supported by Effect:
- Counters
- Frequencies
- Gauges
- Histograms
- Summaries
Example (Using multiple metric types)
import { Data, Effect, Metric } from "effect"
class MetricExample extends Data.TaggedError("MetricExample")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter: Metric.Counter<number> = Metric.counter("requests", {
description: "Total requests processed"
})
const memoryGauge: Metric.Gauge<number> = Metric.gauge("memory_usage", {
description: "Current memory usage in MB"
})
const statusFrequency: Metric.Frequency = Metric.frequency("status_codes", {
description: "HTTP status code frequency"
})
// All metrics share the same interface for updates and reads
yield* Metric.update(requestCounter, 1)
yield* Metric.update(memoryGauge, 128)
yield* Metric.update(statusFrequency, "200")
// All metrics can be read with Metric.value
const counterState = yield* Metric.value(requestCounter)
const gaugeState = yield* Metric.value(memoryGauge)
const frequencyState = yield* Metric.value(statusFrequency)
// Metrics have common properties accessible through the interface:
// - id: unique identifier
// - type: metric type ("Counter", "Gauge", "Frequency", etc.)
// - description: optional human-readable description
// - attributes: optional key-value attributes for tagging
return {
counter: {
id: requestCounter.id,
type: requestCounter.type,
state: counterState
},
gauge: { id: memoryGauge.id, type: memoryGauge.type, state: gaugeState },
frequency: {
id: statusFrequency.id,
type: statusFrequency.type,
state: frequencyState
}
}
})
The Metric namespace provides a comprehensive system for collecting, aggregating, and observing
application metrics in Effect applications.
Example (Collecting application metrics)
import { Data, Effect, Metric } from "effect"
class MetricsError extends Data.TaggedError("MetricsError")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter = Metric.counter("http_requests_total")
const responseTimeHistogram = Metric.histogram("http_response_time", {
boundaries: Metric.linearBoundaries({ start: 0, width: 10, count: 10 })
})
const activeConnectionsGauge = Metric.gauge("active_connections")
const statusFrequency = Metric.frequency("http_status_codes")
// Update metrics
yield* Metric.update(requestCounter, 1)
yield* Metric.update(responseTimeHistogram, 45.2)
yield* Metric.update(activeConnectionsGauge, 12)
yield* Metric.update(statusFrequency, "200")
// Get metric values
const counterValue = yield* Metric.value(requestCounter)
const histogramValue = yield* Metric.value(responseTimeHistogram)
const gaugeValue = yield* Metric.value(activeConnectionsGauge)
const frequencyValue = yield* Metric.value(statusFrequency)
return {
counter: counterValue,
histogram: histogramValue,
gauge: gaugeValue,
frequency: frequencyValue
}
})
Metric<function (type parameter) Input in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>Input, function (type parameter) State in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>State>,
f: (duration: Duration.Duration) => Inputf: (duration: Duration.Duration(parameter) duration: {
value: DurationValue;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
import DurationDuration.type Duration.Duration = /*unresolved*/ anyDuration) => function (type parameter) Input in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>Input
): interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>A, function (type parameter) E in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>E, function (type parameter) R in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: (duration: Duration.Duration) => Input): Effect<A, E, R>R>
<function (type parameter) A in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>A, function (type parameter) E in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>E, function (type parameter) R in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>R, function (type parameter) State in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>State>(
self: Effect<A, E, R>(parameter) self: {
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>A, function (type parameter) E in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>E, function (type parameter) R in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>R>,
metric: Metric.Metric<Duration.Duration, State>(parameter) metric: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
import MetricMetric.interface Metric<in Input, out State>A Metric<Input, State> represents a concurrent metric which accepts update
values of type Input and are aggregated to a value of type State.
Details
For example, a counter metric would have type Metric<number, number>,
representing the fact that the metric can be updated with numbers (the amount
to increment or decrement the counter by), and the state of the counter is a
number.
There are five primitive metric types supported by Effect:
- Counters
- Frequencies
- Gauges
- Histograms
- Summaries
Example (Using multiple metric types)
import { Data, Effect, Metric } from "effect"
class MetricExample extends Data.TaggedError("MetricExample")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter: Metric.Counter<number> = Metric.counter("requests", {
description: "Total requests processed"
})
const memoryGauge: Metric.Gauge<number> = Metric.gauge("memory_usage", {
description: "Current memory usage in MB"
})
const statusFrequency: Metric.Frequency = Metric.frequency("status_codes", {
description: "HTTP status code frequency"
})
// All metrics share the same interface for updates and reads
yield* Metric.update(requestCounter, 1)
yield* Metric.update(memoryGauge, 128)
yield* Metric.update(statusFrequency, "200")
// All metrics can be read with Metric.value
const counterState = yield* Metric.value(requestCounter)
const gaugeState = yield* Metric.value(memoryGauge)
const frequencyState = yield* Metric.value(statusFrequency)
// Metrics have common properties accessible through the interface:
// - id: unique identifier
// - type: metric type ("Counter", "Gauge", "Frequency", etc.)
// - description: optional human-readable description
// - attributes: optional key-value attributes for tagging
return {
counter: {
id: requestCounter.id,
type: requestCounter.type,
state: counterState
},
gauge: { id: memoryGauge.id, type: memoryGauge.type, state: gaugeState },
frequency: {
id: statusFrequency.id,
type: statusFrequency.type,
state: frequencyState
}
}
})
The Metric namespace provides a comprehensive system for collecting, aggregating, and observing
application metrics in Effect applications.
Example (Collecting application metrics)
import { Data, Effect, Metric } from "effect"
class MetricsError extends Data.TaggedError("MetricsError")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter = Metric.counter("http_requests_total")
const responseTimeHistogram = Metric.histogram("http_response_time", {
boundaries: Metric.linearBoundaries({ start: 0, width: 10, count: 10 })
})
const activeConnectionsGauge = Metric.gauge("active_connections")
const statusFrequency = Metric.frequency("http_status_codes")
// Update metrics
yield* Metric.update(requestCounter, 1)
yield* Metric.update(responseTimeHistogram, 45.2)
yield* Metric.update(activeConnectionsGauge, 12)
yield* Metric.update(statusFrequency, "200")
// Get metric values
const counterValue = yield* Metric.value(requestCounter)
const histogramValue = yield* Metric.value(responseTimeHistogram)
const gaugeValue = yield* Metric.value(activeConnectionsGauge)
const frequencyValue = yield* Metric.value(statusFrequency)
return {
counter: counterValue,
histogram: histogramValue,
gauge: gaugeValue,
frequency: frequencyValue
}
})
Metric<import DurationDuration.type Duration.Duration = /*unresolved*/ anyDuration, function (type parameter) State in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>State>
): interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>A, function (type parameter) E in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>E, function (type parameter) R in <A, E, R, State>(self: Effect<A, E, R>, metric: Metric.Metric<Duration.Duration, State>): Effect<A, E, R>R>
} = dual<(...args: Array<any>) => any, <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined) => Effect<A, E, R>>(isDataFirst: (args: IArguments) => boolean, body: <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined) => Effect<A, E, R>): ((...args: Array<any>) => any) & (<A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined) => Effect<A, E, R>) (+1 overload)Creates a function that can be called in data-first style or data-last
(pipe-friendly) style.
When to use
Use to expose one implementation through both direct and pipe-friendly
call styles.
Details
Pass either the arity of the uncurried function or a predicate that decides
whether the current call is data-first. Arity is the common case. Use a
predicate when optional arguments make arity ambiguous.
Example (Selecting data-first or data-last style by arity)
import { Function, pipe } from "effect"
const sum = Function.dual<
(that: number) => (self: number) => number,
(self: number, that: number) => number
>(2, (self, that) => self + that)
console.log(sum(2, 3)) // 5
console.log(pipe(2, sum(3))) // 5
Example (Defining overloads with call signatures)
import { Function, pipe } from "effect"
const sum: {
(that: number): (self: number) => number
(self: number, that: number): number
} = Function.dual(2, (self: number, that: number): number => self + that)
console.log(sum(2, 3)) // 5
console.log(pipe(2, sum(3))) // 5
Example (Selecting data-first or data-last style with a predicate)
import { Function, pipe } from "effect"
const sum = Function.dual<
(that: number) => (self: number) => number,
(self: number, that: number) => number
>(
(args) => args.length === 2,
(self, that) => self + that
)
console.log(sum(2, 3)) // 5
console.log(pipe(2, sum(3))) // 5
dual(
(args: IArgumentsargs) => const isEffect: (
u: unknown
) => u is Effect<any, any, any>
Checks whether a value is an Effect.
Example (Checking whether a value is an Effect)
import { Effect } from "effect"
console.log(Effect.isEffect(Effect.succeed(1))) // true
console.log(Effect.isEffect("hello")) // false
isEffect(args: IArgumentsargs[0]),
<function (type parameter) A in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>A, function (type parameter) E in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>E, function (type parameter) R in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>R, function (type parameter) Input in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>Input, function (type parameter) State in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>State>(
self: Effect<A, E, R>(parameter) self: {
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>A, function (type parameter) E in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>E, function (type parameter) R in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>R>,
metric: Metric.Metric<Input, State>(parameter) metric: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
import MetricMetric.interface Metric<in Input, out State>A Metric<Input, State> represents a concurrent metric which accepts update
values of type Input and are aggregated to a value of type State.
Details
For example, a counter metric would have type Metric<number, number>,
representing the fact that the metric can be updated with numbers (the amount
to increment or decrement the counter by), and the state of the counter is a
number.
There are five primitive metric types supported by Effect:
- Counters
- Frequencies
- Gauges
- Histograms
- Summaries
Example (Using multiple metric types)
import { Data, Effect, Metric } from "effect"
class MetricExample extends Data.TaggedError("MetricExample")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter: Metric.Counter<number> = Metric.counter("requests", {
description: "Total requests processed"
})
const memoryGauge: Metric.Gauge<number> = Metric.gauge("memory_usage", {
description: "Current memory usage in MB"
})
const statusFrequency: Metric.Frequency = Metric.frequency("status_codes", {
description: "HTTP status code frequency"
})
// All metrics share the same interface for updates and reads
yield* Metric.update(requestCounter, 1)
yield* Metric.update(memoryGauge, 128)
yield* Metric.update(statusFrequency, "200")
// All metrics can be read with Metric.value
const counterState = yield* Metric.value(requestCounter)
const gaugeState = yield* Metric.value(memoryGauge)
const frequencyState = yield* Metric.value(statusFrequency)
// Metrics have common properties accessible through the interface:
// - id: unique identifier
// - type: metric type ("Counter", "Gauge", "Frequency", etc.)
// - description: optional human-readable description
// - attributes: optional key-value attributes for tagging
return {
counter: {
id: requestCounter.id,
type: requestCounter.type,
state: counterState
},
gauge: { id: memoryGauge.id, type: memoryGauge.type, state: gaugeState },
frequency: {
id: statusFrequency.id,
type: statusFrequency.type,
state: frequencyState
}
}
})
The Metric namespace provides a comprehensive system for collecting, aggregating, and observing
application metrics in Effect applications.
Example (Collecting application metrics)
import { Data, Effect, Metric } from "effect"
class MetricsError extends Data.TaggedError("MetricsError")<{
readonly operation: string
}> {}
const program = Effect.gen(function*() {
// Create different types of metrics
const requestCounter = Metric.counter("http_requests_total")
const responseTimeHistogram = Metric.histogram("http_response_time", {
boundaries: Metric.linearBoundaries({ start: 0, width: 10, count: 10 })
})
const activeConnectionsGauge = Metric.gauge("active_connections")
const statusFrequency = Metric.frequency("http_status_codes")
// Update metrics
yield* Metric.update(requestCounter, 1)
yield* Metric.update(responseTimeHistogram, 45.2)
yield* Metric.update(activeConnectionsGauge, 12)
yield* Metric.update(statusFrequency, "200")
// Get metric values
const counterValue = yield* Metric.value(requestCounter)
const histogramValue = yield* Metric.value(responseTimeHistogram)
const gaugeValue = yield* Metric.value(activeConnectionsGauge)
const frequencyValue = yield* Metric.value(statusFrequency)
return {
counter: counterValue,
histogram: histogramValue,
gauge: gaugeValue,
frequency: frequencyValue
}
})
Metric<function (type parameter) Input in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>Input, function (type parameter) State in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>State>,
f: | ((duration: Duration.Duration) => Input)
| undefined
duration: Duration.Duration(parameter) duration: {
value: DurationValue;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
import DurationDuration.type Duration.Duration = /*unresolved*/ anyDuration) => function (type parameter) Input in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>Input) | undefined
): interface Effect<out A, out E = never, out R = never>The Effect interface defines a value that lazily describes a workflow or
job. The workflow requires some context R, and may fail with an error of
type E, or succeed with a value of type A.
When to use
Use when you need to represent a lazy, composable workflow that can require
services, fail with a typed error, or succeed with a typed value.
Details
Effect values model resourceful interaction with the outside world,
including synchronous, asynchronous, concurrent, and parallel interaction.
They use a fiber-based concurrency model, with built-in support for
scheduling, fine-grained interruption, structured concurrency, and high
scalability.
To run an Effect value, you need a Runtime, which is a type that is
capable of executing Effect values.
Effect<function (type parameter) A in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>A, function (type parameter) E in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>E, function (type parameter) R in <A, E, R, Input, State>(self: Effect<A, E, R>, metric: Metric.Metric<Input, State>, f: ((duration: Duration.Duration) => Input) | undefined): Effect<A, E, R>R> =>
const clockWith: <A, E, R>(
f: (clock: Clock) => Effect<A, E, R>
) => Effect<A, E, R>
Retrieves the Clock service from the context and provides it to the
specified effectful function.
Example (Accessing the Clock service)
import { Console, Effect } from "effect"
const program = Effect.clockWith((clock) =>
clock.currentTimeMillis.pipe(
Effect.map((currentTime) => `Current time is: ${currentTime}`),
Effect.tap(Console.log)
)
)
Effect.runFork(program)
// Example Output:
// Current time is: 1735484929744
clockWith((clock: Clock(parameter) clock: {
currentTimeMillisUnsafe: () => number;
currentTimeMillis: Effect<number>;
currentTimeNanosUnsafe: () => bigint;
currentTimeNanos: Effect<bigint>;
sleep: (duration: Duration.Duration) => Effect<void>;
}
const startTime: anystartTime = clock: Clock(parameter) clock: {
currentTimeMillisUnsafe: () => number;
currentTimeMillis: Effect<number>;
currentTimeNanosUnsafe: () => bigint;
currentTimeNanos: Effect<bigint>;
sleep: (duration: Duration.Duration) => Effect<void>;
}
const onExit: {
<A, E, XE = never, XR = never>(
f: (
exit: Exit.Exit<A, E>
) => Effect<void, XE, XR>
): <R>(
self: Effect<A, E, R>
) => Effect<A, E | XE, R | XR>
<A, E, R, XE = never, XR = never>(
self: Effect<A, E, R>,
f: (
exit: Exit.Exit<A, E>
) => Effect<void, XE, XR>
): Effect<A, E | XE, R | XR>
}
self: Effect<A, E, R>(parameter) self: {
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
const endTime: anyendTime = clock: Clock(parameter) clock: {
currentTimeMillisUnsafe: () => number;
currentTimeMillis: Effect<number>;
currentTimeNanosUnsafe: () => bigint;
currentTimeNanos: Effect<bigint>;
sleep: (duration: Duration.Duration) => Effect<void>;
}
const duration: Duration.Durationconst duration: {
value: DurationValue;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
import DurationDuration.subtract(
import DurationDuration.fromInputUnsafe(const endTime: anyendTime),
import DurationDuration.fromInputUnsafe(const startTime: anystartTime)
)
const const input: anyinput = f: | ((duration: Duration.Duration) => Input)
| undefined
var undefinedundefined ? const duration: Duration.Durationconst duration: {
value: DurationValue;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
internalCall<Input>(body: () => Input): InputinternalCall(() => f: | ((duration: Duration.Duration) => Input)
| undefined
const duration: Duration.Durationconst duration: {
value: DurationValue;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
toString: () => string;
toJSON: () => unknown;
}
import MetricMetric.const update: {
<Input>(input: Input): <State>(
self: Metric<Input, State>
) => Effect<void>
<Input, State>(
self: Metric<Input, State>,
input: Input
): Effect<void>
}
metric: Metric.Metric<Input, State>(parameter) metric: {
Input: Contravariant<Input>;
State: Covariant<State>;
id: string;
type: Metric.Type;
description: string | undefined;
attributes: Metric.AttributeSet | undefined;
valueUnsafe: (context: Context.Context<never>) => State;
updateUnsafe: (input: Input, context: Context.Context<never>) => void;
modifyUnsafe: (input: Input, context: Context.Context<never>) => void;
pipe: { <A>(this: A): A; <A, B = never>(this: A, ab: (_: A) => B): B; <A, B = never, C = never>(this: A, ab: (_: A) => B, bc: (_: B) => C): C; <A, B = never, C = never, D = never>(this: A, ab: (_: A) => B, bc: (_: B) => C, cd: (_: C) => D): D; <…;
}
const input: anyinput as any)
})
})
)