<A>(other: TxChunk<A>): (self: TxChunk<A>) => Effect.Effect<void>
<A>(self: TxChunk<A>, other: TxChunk<A>): Effect.Effect<void>Concatenates another TxChunk to the end of this TxChunk.
Details
This function mutates the original TxChunk by appending all elements from the other TxChunk. It does not return a new TxChunk reference.
Example (Concatenating TxChunks)
import { Chunk, Effect, TxChunk } from "effect"
const program = Effect.gen(function*() {
const txChunk1 = yield* TxChunk.fromIterable([1, 2, 3])
const txChunk2 = yield* TxChunk.fromIterable([4, 5, 6])
// Concatenate atomically within a transaction
yield* TxChunk.concat(txChunk1, txChunk2)
const result = yield* TxChunk.get(txChunk1)
console.log(Chunk.toReadonlyArray(result)) // [1, 2, 3, 4, 5, 6]
// Original txChunk2 is unchanged
const original = yield* TxChunk.get(txChunk2)
console.log(Chunk.toReadonlyArray(original)) // [4, 5, 6]
})export const const concat: {
<A>(other: TxChunk<A>): (
self: TxChunk<A>
) => Effect.Effect<void>
<A>(
self: TxChunk<A>,
other: TxChunk<A>
): Effect.Effect<void>
}
Concatenates another TxChunk to the end of this TxChunk.
Details
This function mutates the original TxChunk by appending all elements from the other TxChunk. It
does not return a new TxChunk reference.
Example (Concatenating TxChunks)
import { Chunk, Effect, TxChunk } from "effect"
const program = Effect.gen(function*() {
const txChunk1 = yield* TxChunk.fromIterable([1, 2, 3])
const txChunk2 = yield* TxChunk.fromIterable([4, 5, 6])
// Concatenate atomically within a transaction
yield* TxChunk.concat(txChunk1, txChunk2)
const result = yield* TxChunk.get(txChunk1)
console.log(Chunk.toReadonlyArray(result)) // [1, 2, 3, 4, 5, 6]
// Original txChunk2 is unchanged
const original = yield* TxChunk.get(txChunk2)
console.log(Chunk.toReadonlyArray(original)) // [4, 5, 6]
})
concat: {
<function (type parameter) A in <A>(other: TxChunk<A>): (self: TxChunk<A>) => Effect.Effect<void>A>(other: TxChunk<A>(parameter) other: {
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; <…;
}
interface TxChunk<in out A>TxChunk is a transactional chunk data structure that provides Software Transactional Memory (STM)
semantics for chunk operations.
Details
Accessed values are tracked by the transaction in order to detect conflicts and to track changes.
A transaction will retry whenever a conflict is detected or whenever the transaction explicitly
calls Effect.txRetry and any of the accessed TxChunk values change.
Example (Using a transactional chunk)
import { Chunk, Effect, TxChunk } from "effect"
const program = Effect.gen(function*() {
// Create a transactional chunk
const txChunk: TxChunk.TxChunk<number> = yield* TxChunk.fromIterable([
1,
2,
3
])
// Single operations - no explicit transaction needed
yield* TxChunk.append(txChunk, 4)
const result = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(result)) // [1, 2, 3, 4]
// Multi-step atomic operation - use explicit transaction
yield* Effect.tx(
Effect.gen(function*() {
yield* TxChunk.prepend(txChunk, 0)
yield* TxChunk.append(txChunk, 5)
})
)
const finalResult = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(finalResult)) // [0, 1, 2, 3, 4, 5]
})
TxChunk<function (type parameter) A in <A>(other: TxChunk<A>): (self: TxChunk<A>) => Effect.Effect<void>A>): (self: TxChunk<A>(parameter) self: {
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; <…;
}
interface TxChunk<in out A>TxChunk is a transactional chunk data structure that provides Software Transactional Memory (STM)
semantics for chunk operations.
Details
Accessed values are tracked by the transaction in order to detect conflicts and to track changes.
A transaction will retry whenever a conflict is detected or whenever the transaction explicitly
calls Effect.txRetry and any of the accessed TxChunk values change.
Example (Using a transactional chunk)
import { Chunk, Effect, TxChunk } from "effect"
const program = Effect.gen(function*() {
// Create a transactional chunk
const txChunk: TxChunk.TxChunk<number> = yield* TxChunk.fromIterable([
1,
2,
3
])
// Single operations - no explicit transaction needed
yield* TxChunk.append(txChunk, 4)
const result = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(result)) // [1, 2, 3, 4]
// Multi-step atomic operation - use explicit transaction
yield* Effect.tx(
Effect.gen(function*() {
yield* TxChunk.prepend(txChunk, 0)
yield* TxChunk.append(txChunk, 5)
})
)
const finalResult = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(finalResult)) // [0, 1, 2, 3, 4, 5]
})
TxChunk<function (type parameter) A in <A>(other: TxChunk<A>): (self: TxChunk<A>) => Effect.Effect<void>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<void>
<function (type parameter) A in <A>(self: TxChunk<A>, other: TxChunk<A>): Effect.Effect<void>A>(self: TxChunk<A>(parameter) self: {
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; <…;
}
interface TxChunk<in out A>TxChunk is a transactional chunk data structure that provides Software Transactional Memory (STM)
semantics for chunk operations.
Details
Accessed values are tracked by the transaction in order to detect conflicts and to track changes.
A transaction will retry whenever a conflict is detected or whenever the transaction explicitly
calls Effect.txRetry and any of the accessed TxChunk values change.
Example (Using a transactional chunk)
import { Chunk, Effect, TxChunk } from "effect"
const program = Effect.gen(function*() {
// Create a transactional chunk
const txChunk: TxChunk.TxChunk<number> = yield* TxChunk.fromIterable([
1,
2,
3
])
// Single operations - no explicit transaction needed
yield* TxChunk.append(txChunk, 4)
const result = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(result)) // [1, 2, 3, 4]
// Multi-step atomic operation - use explicit transaction
yield* Effect.tx(
Effect.gen(function*() {
yield* TxChunk.prepend(txChunk, 0)
yield* TxChunk.append(txChunk, 5)
})
)
const finalResult = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(finalResult)) // [0, 1, 2, 3, 4, 5]
})
TxChunk<function (type parameter) A in <A>(self: TxChunk<A>, other: TxChunk<A>): Effect.Effect<void>A>, other: TxChunk<A>(parameter) other: {
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; <…;
}
interface TxChunk<in out A>TxChunk is a transactional chunk data structure that provides Software Transactional Memory (STM)
semantics for chunk operations.
Details
Accessed values are tracked by the transaction in order to detect conflicts and to track changes.
A transaction will retry whenever a conflict is detected or whenever the transaction explicitly
calls Effect.txRetry and any of the accessed TxChunk values change.
Example (Using a transactional chunk)
import { Chunk, Effect, TxChunk } from "effect"
const program = Effect.gen(function*() {
// Create a transactional chunk
const txChunk: TxChunk.TxChunk<number> = yield* TxChunk.fromIterable([
1,
2,
3
])
// Single operations - no explicit transaction needed
yield* TxChunk.append(txChunk, 4)
const result = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(result)) // [1, 2, 3, 4]
// Multi-step atomic operation - use explicit transaction
yield* Effect.tx(
Effect.gen(function*() {
yield* TxChunk.prepend(txChunk, 0)
yield* TxChunk.append(txChunk, 5)
})
)
const finalResult = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(finalResult)) // [0, 1, 2, 3, 4, 5]
})
TxChunk<function (type parameter) A in <A>(self: TxChunk<A>, other: TxChunk<A>): Effect.Effect<void>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<void>
} = dual<(...args: Array<any>) => any, <A>(self: TxChunk<A>, other: TxChunk<A>) => Effect.Effect<void>>(arity: 2, body: <A>(self: TxChunk<A>, other: TxChunk<A>) => Effect.Effect<void>): ((...args: Array<any>) => any) & (<A>(self: TxChunk<A>, other: TxChunk<A>) => Effect.Effect<void>) (+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>(self: TxChunk<A>, other: TxChunk<A>): Effect.Effect<void>A>(self: TxChunk<A>(parameter) self: {
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; <…;
}
interface TxChunk<in out A>TxChunk is a transactional chunk data structure that provides Software Transactional Memory (STM)
semantics for chunk operations.
Details
Accessed values are tracked by the transaction in order to detect conflicts and to track changes.
A transaction will retry whenever a conflict is detected or whenever the transaction explicitly
calls Effect.txRetry and any of the accessed TxChunk values change.
Example (Using a transactional chunk)
import { Chunk, Effect, TxChunk } from "effect"
const program = Effect.gen(function*() {
// Create a transactional chunk
const txChunk: TxChunk.TxChunk<number> = yield* TxChunk.fromIterable([
1,
2,
3
])
// Single operations - no explicit transaction needed
yield* TxChunk.append(txChunk, 4)
const result = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(result)) // [1, 2, 3, 4]
// Multi-step atomic operation - use explicit transaction
yield* Effect.tx(
Effect.gen(function*() {
yield* TxChunk.prepend(txChunk, 0)
yield* TxChunk.append(txChunk, 5)
})
)
const finalResult = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(finalResult)) // [0, 1, 2, 3, 4, 5]
})
TxChunk<function (type parameter) A in <A>(self: TxChunk<A>, other: TxChunk<A>): Effect.Effect<void>A>, other: TxChunk<A>(parameter) other: {
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; <…;
}
interface TxChunk<in out A>TxChunk is a transactional chunk data structure that provides Software Transactional Memory (STM)
semantics for chunk operations.
Details
Accessed values are tracked by the transaction in order to detect conflicts and to track changes.
A transaction will retry whenever a conflict is detected or whenever the transaction explicitly
calls Effect.txRetry and any of the accessed TxChunk values change.
Example (Using a transactional chunk)
import { Chunk, Effect, TxChunk } from "effect"
const program = Effect.gen(function*() {
// Create a transactional chunk
const txChunk: TxChunk.TxChunk<number> = yield* TxChunk.fromIterable([
1,
2,
3
])
// Single operations - no explicit transaction needed
yield* TxChunk.append(txChunk, 4)
const result = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(result)) // [1, 2, 3, 4]
// Multi-step atomic operation - use explicit transaction
yield* Effect.tx(
Effect.gen(function*() {
yield* TxChunk.prepend(txChunk, 0)
yield* TxChunk.append(txChunk, 5)
})
)
const finalResult = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(finalResult)) // [0, 1, 2, 3, 4, 5]
})
TxChunk<function (type parameter) A in <A>(self: TxChunk<A>, other: TxChunk<A>): Effect.Effect<void>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<void> =>
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 otherChunk: Chunk.Chunk<A>const otherChunk: {
length: number;
right: Chunk<A>;
left: Chunk<A>;
backing: Backing<A>;
depth: number;
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 get: <A>(
self: TxChunk<A>
) => Effect.Effect<Chunk.Chunk<A>>
Reads the current chunk from the TxChunk.
Example (Reading the current chunk)
import { Chunk, Effect, TxChunk } from "effect"
const program = Effect.gen(function*() {
const txChunk = yield* TxChunk.fromIterable([1, 2, 3])
// Read the current value within a transaction
const chunk = yield* TxChunk.get(txChunk)
console.log(Chunk.toReadonlyArray(chunk)) // [1, 2, 3]
// The value is tracked for conflict detection
const size = Chunk.size(chunk)
console.log(size) // 3
})
get(other: TxChunk<A>(parameter) other: {
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; <…;
}
const appendAll: {
<A>(other: Chunk.Chunk<A>): (
self: TxChunk<A>
) => Effect.Effect<void>
<A>(
self: TxChunk<A>,
other: Chunk.Chunk<A>
): Effect.Effect<void>
}
self: TxChunk<A>(parameter) self: {
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; <…;
}
const otherChunk: Chunk.Chunk<A>const otherChunk: {
length: number;
right: Chunk<A>;
left: Chunk<A>;
backing: Backing<A>;
depth: number;
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;
}
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 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)
)