<A, E>(value: A): (self: TxEnqueue<A, E>) => Effect.Effect<boolean>
<A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>Offers an item to the queue and returns whether it was accepted.
Details
Open unbounded queues always accept; open bounded queues retry while full; dropping queues return false when full; sliding queues evict the oldest item when full. Closing or done queues return false. This function mutates the original TxQueue by adding the item according to the queue's strategy. It does not return a new TxQueue reference.
Example (Offering a value)
import { Effect, TxQueue } from "effect"
const program = Effect.gen(function*() {
const queue = yield* TxQueue.bounded<number>(10)
// Offer an item - returns true if accepted
const accepted = yield* TxQueue.offer(queue, 42)
console.log(accepted) // true
})export const const offer: {
<A, E>(value: A): (
self: TxEnqueue<A, E>
) => Effect.Effect<boolean>
<A, E>(
self: TxEnqueue<A, E>,
value: A
): Effect.Effect<boolean>
}
Offers an item to the queue and returns whether it was accepted.
Details
Open unbounded queues always accept; open bounded queues retry while full; dropping queues return false when full; sliding queues evict the oldest item when full. Closing or done queues return false. This function mutates the original TxQueue by adding the item according to the queue's strategy. It does not return a new TxQueue reference.
Example (Offering a value)
import { Effect, TxQueue } from "effect"
const program = Effect.gen(function*() {
const queue = yield* TxQueue.bounded<number>(10)
// Offer an item - returns true if accepted
const accepted = yield* TxQueue.offer(queue, 42)
console.log(accepted) // true
})
offer: {
<function (type parameter) A in <A, E>(value: A): (self: TxEnqueue<A, E>) => Effect.Effect<boolean>A, function (type parameter) E in <A, E>(value: A): (self: TxEnqueue<A, E>) => Effect.Effect<boolean>E>(value: Avalue: function (type parameter) A in <A, E>(value: A): (self: TxEnqueue<A, E>) => Effect.Effect<boolean>A): (self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
interface TxEnqueue<in A, in E = never>Namespace containing type definitions for TxEnqueue variance annotations.
A TxEnqueue represents the write-only interface of a transactional queue, providing
operations for adding elements (enqueue operations) and inspecting queue state.
Example (Offering values through enqueue handles)
import { Effect, TxQueue } from "effect"
import type { Cause } from "effect"
const program = Effect.gen(function*() {
// Queue without error channel
const queue = yield* TxQueue.bounded<number>(10)
const accepted = yield* TxQueue.offer(queue, 42)
// Queue with error channel for completion signaling
const faultTolerantQueue = yield* TxQueue.bounded<number, string>(10)
yield* TxQueue.offerAll(faultTolerantQueue, [1, 2, 3])
yield* TxQueue.fail(faultTolerantQueue, "processing complete")
// Works with Done for clean completion
const completableQueue = yield* TxQueue.bounded<
string,
Cause.Done
>(5)
yield* TxQueue.offer(completableQueue, "task")
yield* TxQueue.end(completableQueue)
})
TxEnqueue<function (type parameter) A in <A, E>(value: A): (self: TxEnqueue<A, E>) => Effect.Effect<boolean>A, function (type parameter) E in <A, E>(value: A): (self: TxEnqueue<A, E>) => Effect.Effect<boolean>E>) => import EffectEffect.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<boolean>
<function (type parameter) A in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>A, function (type parameter) E in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>E>(self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
interface TxEnqueue<in A, in E = never>Namespace containing type definitions for TxEnqueue variance annotations.
A TxEnqueue represents the write-only interface of a transactional queue, providing
operations for adding elements (enqueue operations) and inspecting queue state.
Example (Offering values through enqueue handles)
import { Effect, TxQueue } from "effect"
import type { Cause } from "effect"
const program = Effect.gen(function*() {
// Queue without error channel
const queue = yield* TxQueue.bounded<number>(10)
const accepted = yield* TxQueue.offer(queue, 42)
// Queue with error channel for completion signaling
const faultTolerantQueue = yield* TxQueue.bounded<number, string>(10)
yield* TxQueue.offerAll(faultTolerantQueue, [1, 2, 3])
yield* TxQueue.fail(faultTolerantQueue, "processing complete")
// Works with Done for clean completion
const completableQueue = yield* TxQueue.bounded<
string,
Cause.Done
>(5)
yield* TxQueue.offer(completableQueue, "task")
yield* TxQueue.end(completableQueue)
})
TxEnqueue<function (type parameter) A in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>A, function (type parameter) E in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>E>, value: Avalue: function (type parameter) A in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>A): import EffectEffect.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<boolean>
} = dual<(...args: Array<any>) => any, <A, E>(self: TxEnqueue<A, E>, value: A) => Effect.Effect<boolean>>(arity: 2, body: <A, E>(self: TxEnqueue<A, E>, value: A) => Effect.Effect<boolean>): ((...args: Array<any>) => any) & (<A, E>(self: TxEnqueue<A, E>, value: A) => Effect.Effect<boolean>) (+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(
2,
<function (type parameter) A in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>A, function (type parameter) E in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>E>(self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
interface TxEnqueue<in A, in E = never>Namespace containing type definitions for TxEnqueue variance annotations.
A TxEnqueue represents the write-only interface of a transactional queue, providing
operations for adding elements (enqueue operations) and inspecting queue state.
Example (Offering values through enqueue handles)
import { Effect, TxQueue } from "effect"
import type { Cause } from "effect"
const program = Effect.gen(function*() {
// Queue without error channel
const queue = yield* TxQueue.bounded<number>(10)
const accepted = yield* TxQueue.offer(queue, 42)
// Queue with error channel for completion signaling
const faultTolerantQueue = yield* TxQueue.bounded<number, string>(10)
yield* TxQueue.offerAll(faultTolerantQueue, [1, 2, 3])
yield* TxQueue.fail(faultTolerantQueue, "processing complete")
// Works with Done for clean completion
const completableQueue = yield* TxQueue.bounded<
string,
Cause.Done
>(5)
yield* TxQueue.offer(completableQueue, "task")
yield* TxQueue.end(completableQueue)
})
TxEnqueue<function (type parameter) A in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>A, function (type parameter) E in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>E>, value: Avalue: function (type parameter) A in <A, E>(self: TxEnqueue<A, E>, value: A): Effect.Effect<boolean>A): import EffectEffect.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<boolean> =>
import EffectEffect.const gen: {
<Eff extends Effect<any, any, any>, AEff>(
f: () => Generator<Eff, AEff, never>
): Effect<
AEff,
[Eff] extends [never]
? never
: [Eff] extends [
Effect<infer _A, infer E, infer _R>
]
? E
: never,
[Eff] extends [never]
? never
: [Eff] extends [
Effect<infer _A, infer _E, infer R>
]
? R
: never
>
<Self, Eff extends Effect<any, any, any>, AEff>(
options: { readonly self: Self },
f: (this: Self) => Generator<Eff, AEff, never>
): Effect<
AEff,
[Eff] extends [never]
? never
: [Eff] extends [
Effect<infer _A, infer E, infer _R>
]
? E
: never,
[Eff] extends [never]
? never
: [Eff] extends [
Effect<infer _A, infer _E, infer R>
]
? R
: never
>
}
const state: State<any, any>state = yield* import TxRefTxRef.const get: <A>(
self: TxRef<A>
) => Effect.Effect<A>
Reads the current value of the TxRef.
When to use
Use to read the current value of a TxRef.
Example (Reading transactional references)
import { Effect, TxRef } from "effect"
const program = Effect.gen(function*() {
const counter = yield* TxRef.make(42)
// Read the value within a transaction
const value = yield* Effect.tx(
TxRef.get(counter)
)
console.log(value) // 42
})
get(self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
TxQueueState.stateRef: TxRef.TxRef<State<any, any>>(property) TxQueueState.stateRef: {
version: number;
pending: Map<unknown, () => void>;
value: A;
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 state: State<any, any>state._tag: "Open" | "Closing" | "Done"_tag === "Done" || const state:
| {
readonly _tag: "Open"
}
| {
readonly _tag: "Closing"
readonly cause: Cause.Cause<any>
}
_tag: "Open" | "Closing"_tag === "Closing") {
return false
}
const const currentSize: numbercurrentSize = yield* const size: (
self: TxQueueState
) => Effect.Effect<number>
Gets the current size of the queue.
Example (Reading queue size)
import { Effect, TxQueue } from "effect"
const program = Effect.gen(function*() {
const queue = yield* TxQueue.bounded<number>(10)
yield* TxQueue.offerAll(queue, [1, 2, 3])
const size = yield* TxQueue.size(queue)
console.log(size) // 3
})
size(self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
TxQueueState.strategy: "bounded" | "unbounded" | "dropping" | "sliding"strategy === "unbounded") {
yield* import TxChunkTxChunk.const append: {
<A>(element: A): (
self: TxChunk<A>
) => Effect.Effect<void>
<A>(
self: TxChunk<A>,
element: A
): Effect.Effect<void>
}
self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
TxQueueState.items: TxChunk.TxChunk<any>(property) TxQueueState.items: {
ref: TxRef.TxRef<Chunk.Chunk<A>>;
toString: () => string;
toJSON: () => unknown;
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; <…;
}
value: Avalue)
return true
}
// For bounded queues, check capacity
if (const currentSize: numbercurrentSize < self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
TxQueueState.capacity: numbercapacity) {
yield* import TxChunkTxChunk.const append: {
<A>(element: A): (
self: TxChunk<A>
) => Effect.Effect<void>
<A>(
self: TxChunk<A>,
element: A
): Effect.Effect<void>
}
self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
TxQueueState.items: TxChunk.TxChunk<any>(property) TxQueueState.items: {
ref: TxRef.TxRef<Chunk.Chunk<A>>;
toString: () => string;
toJSON: () => unknown;
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; <…;
}
value: Avalue)
return true
}
// Queue is at capacity, strategy-specific behavior
if (self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
TxQueueState.strategy: "bounded" | "dropping" | "sliding"strategy === "dropping") {
return false // Drop the new item
}
if (self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
TxQueueState.strategy: "bounded" | "sliding"strategy === "sliding") {
yield* import TxChunkTxChunk.const drop: {
(n: number): <A>(
self: TxChunk<A>
) => Effect.Effect<void>
<A>(
self: TxChunk<A>,
n: number
): Effect.Effect<void>
}
self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
TxQueueState.items: TxChunk.TxChunk<any>(property) TxQueueState.items: {
ref: TxRef.TxRef<Chunk.Chunk<A>>;
toString: () => string;
toJSON: () => unknown;
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 TxChunkTxChunk.const append: {
<A>(element: A): (
self: TxChunk<A>
) => Effect.Effect<void>
<A>(
self: TxChunk<A>,
element: A
): Effect.Effect<void>
}
self: TxEnqueue<A, E>(parameter) self: {
strategy: "bounded" | "unbounded" | "dropping" | "sliding";
capacity: number;
items: TxChunk.TxChunk<any>;
stateRef: TxRef.TxRef<State<any, any>>;
toString: () => string;
toJSON: () => unknown;
}
TxQueueState.items: TxChunk.TxChunk<any>(property) TxQueueState.items: {
ref: TxRef.TxRef<Chunk.Chunk<A>>;
toString: () => string;
toJSON: () => unknown;
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; <…;
}
value: Avalue) // Add new item
return true
}
// bounded strategy - block until space is available
return yield* import EffectEffect.const txRetry: Effect<
never,
never,
Transaction
>
const txRetry: {
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;
}
Retries the current transaction by signaling that it must be retried.
Details
NOTE: the transaction retries on any change to transactional values (i.e. TxRef) accessed in its body.
Example (Retrying transactions)
import { Effect, TxRef } from "effect"
const program = Effect.gen(function*() {
// create a transactional reference
const ref = yield* TxRef.make(0)
// forks a fiber that increases the value of `ref` every 100 millis
yield* Effect.forkChild(Effect.forever(
// update to transactional value
Effect.tx(TxRef.update(ref, (n) => n + 1)).pipe(Effect.delay("100 millis"))
))
// the following will retry 10 times until the `ref` value is 10
yield* Effect.tx(Effect.gen(function*() {
const value = yield* TxRef.get(ref)
if (value < 10) {
yield* Effect.log(`retry due to value: ${value}`)
return yield* Effect.txRetry
}
yield* Effect.log(`transaction done with value: ${value}`)
}))
})
Effect.runPromise(program).catch(console.error)
txRetry
}).Pipeable.pipe<Effect.Effect<boolean, never, Effect.Transaction>, Effect.Effect<boolean, never, never>>(this: Effect.Effect<boolean, never, Effect.Transaction>, ab: (_: Effect.Effect<boolean, never, Effect.Transaction>) => Effect.Effect<boolean, never, never>): Effect.Effect<boolean, never, never> (+21 overloads)pipe(import EffectEffect.const tx: <A, E, R>(
effect: Effect<A, E, R>
) => Effect<A, E, Exclude<R, Transaction>>
Defines a transaction boundary. Transactions are "all or nothing" with respect to changes
made to transactional values (i.e. TxRef) that occur within the transaction body.
Details
If called inside an active transaction, tx composes with the current transaction and reuses
its journal and retry state instead of creating a nested boundary.
Effect transactions are optimistic with retry. A transaction is retried when
its body explicitly calls Effect.txRetry and any accessed transactional
value changes, or when any accessed transactional value changes because a
different transaction commits before the current one.
The outermost tx call creates the transaction boundary and commits or rolls back the full
composed transaction.
Example (Running a transaction)
import { Effect, TxRef } from "effect"
const program = Effect.gen(function*() {
const ref1 = yield* TxRef.make(0)
const ref2 = yield* TxRef.make(0)
// Nested tx calls compose into the same transaction
yield* Effect.tx(Effect.gen(function*() {
yield* TxRef.set(ref1, 10)
yield* Effect.tx(TxRef.set(ref2, 20))
const sum = (yield* TxRef.get(ref1)) + (yield* TxRef.get(ref2))
console.log(`Transaction sum: ${sum}`)
}))
console.log(`Final ref1: ${yield* TxRef.get(ref1)}`) // 10
console.log(`Final ref2: ${yield* TxRef.get(ref2)}`) // 20
})
tx)
)