dataforge-data/space.kscience.dataforge.data/StaticData

StaticData

class StaticData<T : Any>(val type: KType, value: T, val meta: Meta = Meta.EMPTY) : StaticGoal<T> , Data<T>

Constructors

constructor(type: KType, value: T, meta: Meta = Meta.EMPTY)

Properties

abstract val deferred: Deferred<T>?

Returns current running coroutine if the goal is started. Null if the computation is not started.

abstract val dependencies: Collection<Goal<*>>

val Goal<*>.isComplete: Boolean

open override val meta: Meta

Meta for the data

open override val type: KType

Type marker for the data. The type is known before the calculation takes place so it could be checked.

val value: T

Functions

abstract fun async(coroutineScope: CoroutineScope): Deferred<T>

Get ongoing computation or start a new one. Does not guarantee thread safety. In case of multi-thread access, could create orphan computations.

suspend fun <T> Goal<T>.await(): T

suspend fun <T : Any> Data<T>.awaitWithMeta(): ValueWithMeta<T>

inline fun <T1 : Any, T2 : Any, R : Any> Data<T1>.combine(other: Data<T2>, coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = this.meta, crossinline block: suspend (left: T1, right: T2) -> R): Data<R>

Combine this data with the other data using block. See Data::map for other details

fun Goal<*>.launch(coroutineScope: CoroutineScope): Job

inline fun <T : Any, R : Any> Data<T>.map(coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = this.meta, crossinline block: suspend (T) -> R): Data<R>

Lazily transform this data to another data. By convention block should not use external data (be pure).

fun <T : Any> Data<T>.named(name: Name): NamedData<T>

abstract fun reset()

Reset the computation

open override fun toMeta(): Meta