Documentation / dataflow-async / com.femastudios.dataflow.async.extensions / chunked
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chunked
fun <T, R> Attribute<Iterable<T>>.chunked(size: Attribute<Int>, transform: (List<T>) -> R): Attribute<List<R>>
fun <T, R> Attribute<Iterable<T>>.chunked(size: Int, transform: (List<T>) -> R): Attribute<List<R>>
fun <T> Attribute<Iterable<T>>.chunked(size: Attribute<Int>): Attribute<List<List<T>>>
fun <T> Attribute<Iterable<T>>.chunked(size: Int): Attribute<List<List<T>>>
Same as chunked, but accepts Attribute and returns a new Attribute.
Calling this function is equivalent to use transform and calling chunked in the transformation function.
This is simply a convenience function.
See Also
fun <T, R> Attribute<Sequence<T>>.chunked(size: Attribute<Int>, transform: (List<T>) -> R): Attribute<Sequence<R>>
fun <T, R> Attribute<Sequence<T>>.chunked(size: Int, transform: (List<T>) -> R): Attribute<Sequence<R>>
fun <T> Attribute<Sequence<T>>.chunked(size: Attribute<Int>): Attribute<Sequence<List<T>>>
fun <T> Attribute<Sequence<T>>.chunked(size: Int): Attribute<Sequence<List<T>>>
Same as chunked, but accepts Attribute and returns a new Attribute.
Calling this function is equivalent to use transform and calling chunked in the transformation function.
This is simply a convenience function.
See Also
fun <R> Attribute<String>.chunked(size: Attribute<Int>, transform: (CharSequence) -> R): Attribute<List<R>>
fun <R> Attribute<String>.chunked(size: Int, transform: (CharSequence) -> R): Attribute<List<R>>
fun Attribute<String>.chunked(size: Attribute<Int>): Attribute<List<String>>
fun Attribute<String>.chunked(size: Int): Attribute<List<String>>
Same as chunked, but accepts Attribute and returns a new Attribute.
Calling this function is equivalent to use transform and calling chunked in the transformation function.
This is simply a convenience function.
See Also