dataforge-data/space.kscience.dataforge.data

Package-level declarations

Types

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class CoroutineMonitor : CoroutineContext.Element

A monitor of goal state that could be accessed only form inside the goal

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@DfId(id = "data")
interface Data<out T> : Goal<T> , MetaRepr

A data element characterized by its meta

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interface DataSet<out T : Any>
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interface DataSetBuilder<in T : Any>
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interface DataSource<out T : Any> : DataSet<T> , CoroutineScope

A DataSet with propagated updates.

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@DfId(id = "dataTree")
interface DataTree<out T : Any> : DataSet<T>

A tree-like DataSet grouped into the node. All data inside the node must inherit its type

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class DataTreeBuilder<T : Any>(val dataType: KType, coroutineContext: CoroutineContext) : DataTree<T> , DataSourceBuilder<T>

A mutable DataTree that propagates updates

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sealed class DataTreeItem<out T : Any>
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interface Goal<out T>

Lazy computation result with its dependencies to allowing to stat computing dependencies ahead of time

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class GoalExecutionRestriction(val policy: GoalExecutionRestrictionPolicy = GoalExecutionRestrictionPolicy.ERROR) : CoroutineContext.Element

A special coroutine context key that allows or disallows goal execution during configuration time (eager execution).

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interface GoalLogger : CoroutineContext.Element

Coroutine context element that provides logging capabilities

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interface GroupRule
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open class LazyGoal<T>(coroutineContext: CoroutineContext = EmptyCoroutineContext, val dependencies: Collection<Goal<*>> = emptyList(), val block: suspend () -> T) : Goal<T>
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interface NamedData<out T : Any> : Named, Data<T>
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data class NamedValueWithMeta<T>(val name: Name, val meta: Meta, val value: T)
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class StaticData<T : Any>(val type: KType, value: T, val meta: Meta = Meta.EMPTY) : StaticGoal<T> , Data<T>
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open class StaticGoal<T>(val value: T) : Goal<T>
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data class ValueWithMeta<T>(val meta: Meta, val value: T)

Properties

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val <T : Any> DataTreeItem<T>?.data: Data<T>?
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val Job.dependencies: Collection<Job>
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val Job.progress: Double
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val Job.status: String
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val Job.totalWork: Double
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val <T : Any> DataTreeItem<T>?.tree: DataTree<T>?
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val <T : Any> DataSet<T>.updates: Flow<Name>
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val <T : Any> DataSet<T>.updatesWithData: Flow<NamedData<T>>
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val Job.workDone: Double

Functions

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suspend fun <T> Goal<T>.await(): T
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suspend fun <T : Any> Data<T>.awaitWithMeta(): ValueWithMeta<T>
suspend fun <T : Any> NamedData<T>.awaitWithMeta(): NamedValueWithMeta<T>
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fun <T : Any> DataSet<T>.branch(branchName: String): DataSet<T>
fun <T : Any> DataTree<T>.branch(branchName: String): DataTree<T>

fun <T : Any> DataSet<T>.branch(branchName: Name): DataSet<T>

Get a subset of data starting with a given branchName

fun <T : Any> DataTree<T>.branch(branchName: Name): DataTree<T>

Get a branch of this DataTree with a given branchName. The difference from similar method for DataSet is that internal logic is more simple and the return value is a DataTree

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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

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operator fun NamedData<*>.component1(): Name
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operator fun <T : Any> NamedData<T>.component2(): Data<T>
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suspend fun <T : Any> DataSet<T>.computeAndJoinAll()
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inline fun <T : Any> Data(value: T, meta: Meta = Meta.EMPTY): StaticData<T>
inline fun <T : Any> Data(meta: Meta = Meta.EMPTY, context: CoroutineContext = EmptyCoroutineContext, dependencies: Collection<Goal<*>> = emptyList(), noinline block: suspend () -> T): Data<T>
fun <T : Any> Data(type: KType, meta: Meta = Meta.EMPTY, context: CoroutineContext = EmptyCoroutineContext, dependencies: Collection<Goal<*>> = emptyList(), block: suspend () -> T): Data<T>
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fun <T : Any> DataSetBuilder<T>.data(name: String, value: Data<T>)
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inline suspend fun <T : Any> DataSource(crossinline block: DataSourceBuilder<T>.() -> Unit = {}): DataTreeBuilder<T>
inline fun <T : Any> DataSource(parent: CoroutineScope, crossinline block: DataSourceBuilder<T>.() -> Unit): DataTreeBuilder<T>

fun <T : Any> DataSource(type: KType, parent: CoroutineScope, block: DataSourceBuilder<T>.() -> Unit): DataTreeBuilder<T>

Create a dynamic DataSource. Initial data is placed synchronously.

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inline fun <T : Any> DataTree(noinline block: DataSetBuilder<T>.() -> Unit): DataTree<T>
inline fun <T : Any> DataTree(dataType: KType, block: DataSetBuilder<T>.() -> Unit): DataTree<T>
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inline fun <T : Any> DataSourceBuilder<T>.emit(name: String, parent: CoroutineScope, noinline block: DataSourceBuilder<T>.() -> Unit)
inline fun <T : Any> DataSourceBuilder<T>.emit(name: Name, parent: CoroutineScope, noinline block: DataSourceBuilder<T>.() -> Unit)
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fun <T : Any> DataSet<T>.filter(predicate: (Name, Meta) -> Boolean): DataSource<T>

A stateless filtered DataSet

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inline fun <R : Any> DataSet<*>.filterByType(noinline predicate: (name: Name, meta: Meta) -> Boolean = { _, _ -> true }): DataSet<R>

Select a single datum of the appropriate type

fun <R : Any> DataSet<*>.filterByType(type: KType, predicate: (name: Name, meta: Meta) -> Boolean = { _, _ -> true }): DataSource<R>

Select all data matching given type and filters. Does not modify paths

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inline fun <T : Any, R : Any> Iterable<NamedData<T>>.foldNamedToData(initial: R, coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline block: suspend (result: R, data: NamedValueWithMeta<T>) -> R): Data<R>

Fold a Iterable of named data into a single Data

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inline fun <T : Any, R : Any> Iterable<Data<T>>.foldToData(initial: R, coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline block: suspend (result: R, data: ValueWithMeta<T>) -> R): Data<R>
inline fun <T : Any, R : Any> DataSet<T>.foldToData(initial: R, coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline block: suspend (result: R, data: NamedValueWithMeta<T>) -> R): Data<R>
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inline fun <T : Any> DataSet<T>.forEach(block: (NamedData<T>) -> Unit)
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operator fun <T : Any> DataSet<T>.get(name: String): Data<T>?
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inline fun <R : Any> DataSet<*>.getByType(name: String): NamedData<R>?
inline fun <R : Any> DataSet<*>.getByType(name: Name): NamedData<R>?

fun <R : Any> DataSet<*>.getByType(type: KType, name: Name): NamedData<R>?

Select a single datum if it is present and of given type

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tailrec fun <T : Any> DataTree<T>.getItem(name: Name): DataTreeItem<T>?

Get a DataTreeItem with given name or null if the item does not exist

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fun Goal<*>.launch(coroutineScope: CoroutineScope): Job
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fun <T : Any> DataTree<T>.listChildren(prefix: Name): List<Name>
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inline suspend fun <T : Any, R : Any> DataSet<T>.map(coroutineContext: CoroutineContext = EmptyCoroutineContext, noinline metaTransform: MutableMeta.() -> Unit = {}, noinline block: suspend (NamedValueWithMeta<T>) -> R): DataTree<R>
suspend fun <T : Any, R : Any> DataSet<T>.map(outputType: KType, coroutineContext: CoroutineContext = EmptyCoroutineContext, metaTransform: MutableMeta.() -> Unit = {}, block: suspend (NamedValueWithMeta<T>) -> R): DataTree<R>

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).

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fun <T : Any> DataSetBuilder<T>.meta(mutableMeta: MutableMeta.() -> Unit)
fun <T : Any> DataSetBuilder<T>.meta(value: Meta)

Define meta in this DataSet

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fun <T : Any> Data<T>.named(name: Name): NamedData<T>
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inline fun <T : Any> DataSetBuilder<T>.node(name: String, crossinline block: DataSetBuilder<T>.() -> Unit)
fun <T : Any> DataSetBuilder<T>.node(name: String, set: DataSet<T>)
inline fun <T : Any> DataSetBuilder<T>.node(name: Name, crossinline block: DataSetBuilder<T>.() -> Unit)
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fun <T : Any> DataSetBuilder<T>.populateFrom(sequence: Sequence<NamedData<T>>)

fun <T : Any> DataSetBuilder<T>.populateFrom(tree: DataSet<T>)

Update data with given node data and meta with node meta.

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inline fun <T : Any> DataSetBuilder<T>.produce(name: String, meta: Meta = Meta.EMPTY, noinline producer: suspend () -> T)

Produce lazy Data and emit it into the DataSetBuilder

inline fun <T : Any> DataSetBuilder<T>.produce(name: Name, meta: Meta = Meta.EMPTY, noinline producer: suspend () -> T)
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infix fun <T : Any> String.put(block: DataSetBuilder<T>.() -> Unit)

Build and append node

infix fun <T : Any> String.put(dataSet: DataSet<T>)

Append node

infix fun <T : Any> String.put(data: Data<T>)

Append data to node

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inline fun <T : Any, R : Any> Iterable<NamedData<T>>.reduceNamedToData(coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline transformation: suspend (Collection<NamedValueWithMeta<T>>) -> R): Data<R>

inline fun <T : Any, R : Any> Iterable<NamedData<T>>.reduceNamedToData(outputType: KType, coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline transformation: suspend (Collection<NamedValueWithMeta<T>>) -> R): Data<R>

Transform an Iterable of NamedData to a single Data.

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inline fun <T : Any, R : Any> Collection<Data<T>>.reduceToData(coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline block: suspend (List<ValueWithMeta<T>>) -> R): Data<R>

Lazily reduce a collection of Data to a single data.

inline fun <T : Any, R : Any> Iterable<Data<T>>.reduceToData(coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline transformation: suspend (Collection<ValueWithMeta<T>>) -> R): Data<R>
inline fun <T : Any, R : Any> DataSet<T>.reduceToData(coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline transformation: suspend (Iterable<NamedValueWithMeta<T>>) -> R): Data<R>
inline fun <T : Any, R : Any> Iterable<Data<T>>.reduceToData(outputType: KType, coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline transformation: suspend (Collection<ValueWithMeta<T>>) -> R): Data<R>
fun <K, T : Any, R : Any> Map<K, Data<T>>.reduceToData(outputType: KType, coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, block: suspend (Map<K, ValueWithMeta<T>>) -> R): Data<R>

inline fun <K, T : Any, R : Any> Map<K, Data<T>>.reduceToData(coroutineContext: CoroutineContext = EmptyCoroutineContext, meta: Meta = Meta.EMPTY, crossinline block: suspend (Map<K, ValueWithMeta<T>>) -> R): Data<R>

Lazily reduce a Map of Data with any static key.

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suspend fun <T : Any> DataSet<T>.rootData(): Data<T>?
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fun <T : Any> DataSet<T>.seal(): DataTree<T>
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fun <T : Any> DataSetBuilder<T>.set(value: NamedData<T>)
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fun <T : Any> CoroutineScope.setAndWatch(name: Name, dataSet: DataSet<T>): Job

Copy given data set and mirror its changes to this DataTreeBuilder in this@setAndObserve. Returns an update Job

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fun <T : Any> DataSet<T>.single(): NamedData<T>

Return a single Data in this DataSet. Throw error if it is not single.

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fun <T : Any> DataSet<T>.startAll(coroutineScope: CoroutineScope): Job

Start computation for all goals in data node and return a job for the whole node

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inline fun <T : Any> DataSetBuilder<T>.static(name: String, data: T, mutableMeta: MutableMeta.() -> Unit)
inline fun <T : Any> DataSetBuilder<T>.static(name: Name, data: T, meta: Meta = Meta.EMPTY)

inline fun <T : Any> DataSetBuilder<T>.static(name: String, data: T, meta: Meta = Meta.EMPTY)

Emit a static data with the fixed value

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fun DataSet<*>.toMeta(): Meta
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fun <T : Any> DataTree<T>.traverseItems(): Sequence<Pair<Name, DataTreeItem<T>>>

A Sequence of all children including nodes

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fun <T : Any> DataSet<T>.withNamePrefix(prefix: Name): DataSet<T>

Generate a wrapper data set with a given name prefix appended to all names