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The module for FunctionalJ Core.
// ============================================================================
// Copyright (c) 2017-2021 Nawapunth Manusitthipol (NawaMan - http://nawaman.net).
// ----------------------------------------------------------------------------
// MIT License
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in all
// copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
// ============================================================================
package functionalj.stream.intstream;
import java.util.function.Function;
import java.util.function.IntPredicate;
import functionalj.list.intlist.IntFuncList;
import functionalj.map.FuncMap;
import functionalj.tuple.Tuple2;
public interface IntStreamPlusWithSplit
extends IntStreamPlusWithMapToTuple {
// The most important thing here is to only evaluate the value once.
// Everything else that contradict that must give. That because we can use regular filter if evaluating once is not important.
//== split ==
// TODO - Try to make it lazy
// It is not easy as it seems as there has to be buffer for one branch when go through with another branch.
// We may need a dynamic collection of all branch as we goes along.
/**
* Split the stream using the predicate.
* The result is a tuple of streams where the first stream is for those element that the predicate returns true.
*
* The elements in this stream is guaranteed to be in one of the result stream.
*/
public default Tuple2 split(
IntPredicate predicate) {
Function toStreamPlus = IntFuncList::intStreamPlus;
return IntFuncList.from(()->intStreamPlus())
.split(predicate)
.map(toStreamPlus, toStreamPlus);
}
/**
* Split the stream using the predicate and return as part of a map.
*
* The predicate will be checked one by one and when match the element will be used as part of the value with that associated key.
*/
public default FuncMap split(
KEY key1, IntPredicate predicate,
KEY key2) {
Function toStreamPlus = IntFuncList::intStreamPlus;
return IntFuncList.from(()->intStreamPlus())
.split(key1, predicate, key2)
.mapValue(toStreamPlus);
}
/**
* Split the stream using the predicate and return as part of a map.
*
* The predicate will be checked one by one and when match the element will be used as part of the value with that associated key.
*/
public default FuncMap split(
KEY key1, IntPredicate predicate1,
KEY key2, IntPredicate predicate2,
KEY key3) {
Function toStreamPlus = IntFuncList::intStreamPlus;
return IntFuncList.from(()->intStreamPlus())
.split(key1, predicate1, key2, predicate2, key3)
.mapValue(toStreamPlus);
}
/**
* Split the stream using the predicate and return as part of a map.
*
* The predicate will be checked one by one and when match the element will be used as part of the value with that associated key.
*/
public default FuncMap split(
KEY key1, IntPredicate predicate1,
KEY key2, IntPredicate predicate2,
KEY key3, IntPredicate predicate3,
KEY key4) {
Function toStreamPlus = IntFuncList::intStreamPlus;
return IntFuncList.from(()->intStreamPlus())
.split(key1, predicate1, key2, predicate2, key3, predicate3, key4)
.mapValue(toStreamPlus);
}
/**
* Split the stream using the predicate and return as part of a map.
*
* The predicate will be checked one by one and when match the element will be used as part of the value with that associated key.
*/
public default FuncMap split(
KEY key1, IntPredicate predicate1,
KEY key2, IntPredicate predicate2,
KEY key3, IntPredicate predicate3,
KEY key4, IntPredicate predicate4,
KEY key5) {
Function toStreamPlus = IntFuncList::intStreamPlus;
return IntFuncList.from(()->intStreamPlus())
.split(key1, predicate1, key2, predicate2, key3, predicate3, key4, predicate4, key5)
.mapValue(toStreamPlus);
}
/**
* Split the stream using the predicate and return as part of a map.
*
* The predicate will be checked one by one and when match the element will be used as part of the value with that associated key.
*/
public default FuncMap split(
KEY key1, IntPredicate predicate1,
KEY key2, IntPredicate predicate2,
KEY key3, IntPredicate predicate3,
KEY key4, IntPredicate predicate4,
KEY key5, IntPredicate predicate5,
KEY key6) {
Function toStreamPlus = IntFuncList::intStreamPlus;
return IntFuncList.from(()->intStreamPlus())
.split(key1, predicate1, key2, predicate2, key3, predicate3, key4, predicate4, key5, predicate5, key6)
.mapValue(toStreamPlus);
}
}