Transducers in Kotlin

README.md

Transducers are composable algorithmic transformations. They are independent from the context of their input and output sources and specify only the essence of the transformation in terms of an individual element. Because transducers are decoupled from input or output sources, they can be used in many different processes - collections, streams, channels, observables, etc. Transducers compose directly, without awareness of input or creation of intermediate aggregates.

Original source code (from Oct 12, 2014):

• Transducers.kt: https://gist.github.com/Spasi/4052e4e8c8d88a7325fb
• TransducersTest.kt: https://gist.github.com/Spasi/2a9d7d420b20f37513d5

Change notes:

• Converted to Kotlin 1.0.0-beta-3595 and JUnit 4.12.
• Added T.assertEquals(T) and auto reformatted the source code.
• Some unit tests are failing with slight differences in the results.
• Updated copyright notice since Apache License states "You must cause any modified files to carry prominent notices stating that You changed the files".

Weblinks:

• http://clojure.org/transducers
• http://blog.cognitect.com/blog/2014/8/6/transducers-are-coming
• https://github.com/cognitect-labs/transducers-java

Transducers.kt

// Copyright 2014 Cognitect. All Rights Reserved.
// Copyright 2015 Benjamin Gudehus (updated code to Kotlin 1.0.0).
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS-IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

// This is a Kotlin port of https://github.com/cognitect-labs/transducers-java

package transducers

import java.util.ArrayList
import java.util.concurrent.ThreadLocalRandom
import java.util.concurrent.atomic.AtomicBoolean

/**
 * A reducing step function.
 * @param <R> Type of first argument and return value
 * @param <T> Type of input to reduce
 */
interface StepFunction<R, T> {
    /**
     * Applies the reducing function to the current result and
     * the new input, returning a new result.
     *
     * A reducing function can indicate that no more input
     * should be processed by setting the value of reduced to
     * true. This causes the reduction process to complete,
     * returning the most recent result.
     * @param result The current result value
     * @param input New input to process
     * @param reduced A boolean value which can be set to true
     *                to stop the reduction process
     * @return A new result value
     */
    fun apply(result: R,
              input: T,
              reduced: AtomicBoolean): R
}

/**
 * A complete reducing function. Extends a single reducing step
 * function and adds a zero-arity function for initializing a new
 * result and a single-arity function for processing the final
 * result after the reduction process has completed.
 * @param <R> Type of first argument and return value
 * @param <T> Type of input to reduce
 */
interface ReducingFunction<R, T> : StepFunction<R, T> {
    /**
     * Returns a newly initialized result.
     * @return a new result
     */
    fun apply(): R = throw UnsupportedOperationException()

    /**
     * Completes processing of a final result.
     * @param result the final reduction result
     * @return the completed result
     */
    fun apply(result: R): R = result
}

/**
 * Abstract base class for implementing a reducing function that chains to
 * another reducing function. Zero-arity and single-arity overloads of apply
 * delegate to the chained reducing function. Derived classes must implement
 * the three-arity overload of apply, and may implement either of the other
 * two overloads as required.
 * @param <R> Type of first argument and return value of the reducing functions
 * @param <A> Input type of reducing function being chained to
 * @param <B> Input type of this reducing function
 */
abstract class ReducingFunctionOn<R, A, B>(val rf: ReducingFunction<R, in A>) : ReducingFunction<R, B> {
    override fun apply() = rf.apply()
    override fun apply(result: R) = rf.apply(result)
}

/**
 * A Transducer transforms a reducing function of one type into a
 * reducing function of another (possibly the same) type, applying
 * mapping, filtering, flattening, etc. logic as desired.
 * @param <B> The type of data processed by an input process
 * @param <C> The type of data processed by the transduced process
 */
interface Transducer<B, C> {
    /**
     * Transforms a reducing function of B into a reducing function
     * of C.
     * @param rf The input reducing function
     * @param <R> The result type of both the input and the output
     *           reducing functions
     * @return The transformed reducing function
     */
    fun <R> apply(rf: ReducingFunction<R, in B>): ReducingFunction<R, C>

    /**
     * Composes a transducer with another transducer, yielding
     * a new transducer.
     * @param right the transducer to compose with this transducer
     * @param <A> the type of input processed by the reducing function
     *           the composed transducer returns when applied
     * @return A new composite transducer
     */
    fun <A> comp(right: Transducer<A, in B>): Transducer<A, C> = object : Transducer<A, C> {
        override fun <R> apply(rf: ReducingFunction<R, in A>) = [email protected](right.apply(rf))
    }
}

/**
 * Applies given reducing function to current result and each T in input, using
 * the result returned from each reduction step as input to the next step. Returns
 * final result.
 * @param f a reducing function
 * @param result an initial result value
 * @param input the input to process
 * @param reduced a boolean flag that can be set to indicate that the reducing process
 *                should stop, even though there is still input to process
 * @param <R> the type of the result
 * @param <T> the type of each item in input
 * @return the final reduced result
 */
fun <R, T> reduce(f: ReducingFunction<R, in T>,
                  result: R,
                  input: Iterable<T>,
                  reduced: AtomicBoolean = AtomicBoolean()): R {
    var ret = result
    for (t in input) {
        ret = f.apply(ret, t, reduced)
        if (reduced.get()) break
    }
    return f.apply(ret)
}

fun <R, T> completing(sf: StepFunction<R, in T>): ReducingFunction<R, in T> =
    if (sf is ReducingFunction) {
        sf
    }
    else {
        object : ReducingFunction<R, T> {
            override fun apply(result: R,
                               input: T,
                               reduced: AtomicBoolean) = sf.apply(result, input, reduced)
        }
    }

/**
 * Reduces input using transformed reducing function. Transforms reducing function by applying
 * transducer. Reducing function must implement zero-arity apply that returns initial result
 * to start reducing process.
 * @param xf a transducer (or composed transducers) that transforms the reducing function
 * @param rf a reducing function
 * @param input the input to reduce
 * @param <R> return type
 * @param <A> type of input expected by reducing function
 * @param <B> type of input and type accepted by reducing function returned by transducer
 * @return result of reducing transformed input
 */
fun <R, A, B> transduce(xf: Transducer<A, B>,
                        rf: ReducingFunction<R, in A>,
                        input: Iterable<B>): R = reduce(xf.apply(rf), rf.apply(), input)

/**
 * Reduces input using transformed reducing function. Transforms reducing function by applying
 * transducer. Step function is converted to reducing function if necessary. Accepts initial value
 * for reducing process as argument.
 * @param xf a transducer (or composed transducers) that transforms the reducing function
 * @param rf a reducing function
 * @param init an initial value to start reducing process
 * @param input the input to reduce
 * @param <R> return type
 * @param <A> type expected by reducing function
 * @param <B> type of input and type accepted by reducing function returned by transducer
 * @return result of reducing transformed input
 */
fun <R, A, B> transduce(xf: Transducer<A, B>,
                        rf: StepFunction<R, in A>,
                        init: R,
                        input: Iterable<B>): R = reduce(xf.apply(completing(rf)), init, input)

fun <R : MutableCollection<A>, A, B> into(xf: Transducer<A, B>,
                                          init: R,
                                          input: Iterable<B>): R =
    transduce(xf, object : ReducingFunction<R, A> {
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            result.add(input)
            return result
        }
    }, init, input)

/**
 * Composes a transducer with another transducer, yielding a new transducer that
 * @param left left hand transducer
 * @param right right hand transducer
 */
fun <A, B, C> compose(left: Transducer<B, C>,
                      right: Transducer<A, B>): Transducer<A, C> = left.comp(right)

/**
 * Creates a transducer that transforms a reducing function by applying a mapping
 * function to each input.
 * @param f a mapping function from one type to another (can be the same type)
 * @param <A> input type of input reducing function
 * @param <B> input type of output reducing function
 * @return a new transducer
 */
fun <A, B> map(f: (B) -> A): Transducer<A, B> = object : Transducer<A, B> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, B>(rf) {
        override fun apply(result: R,
                           input: B,
                           reduced: AtomicBoolean) = rf.apply(result, f(input), reduced)
    }
}

/**
 * Creates a transducer that transforms a reducing function by applying a
 * predicate to each input and processing only those inputs for which the
 * predicate is true.
 * @param p a predicate function
 * @param <A> input type of input and output reducing functions
 * @return a new transducer
 */
fun <A> filter(p: (A) -> Boolean): Transducer<A, A> = object : Transducer<A, A> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, A>(rf) {
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean) = if (p(input)) rf.apply(result, input, reduced) else result
    }
}

/**
 * Creates a transducer that transforms a reducing function by accepting
 * an iterable of the expected input type and reducing it
 * @param <A> input type of input reducing function
 * @param <B> input type of output reducing function
 * @return a new transducer
 */
fun <A, B : Iterable<A>> cat(): Transducer<A, B> = object : Transducer<A, B> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, B>(rf) {
        override fun apply(result: R,
                           input: B,
                           reduced: AtomicBoolean) = reduce(rf, result, input, reduced)
    }
}

/**
 * Creates a transducer that transforms a reducing function using
 * a composition of map and cat.
 * @param f a mapping function from one type to another (can be the same type)
 * @param <A> input type of input reducing function
 * @param <B> output type of output reducing function and iterable of input type
 *           of input reducing function
 * @param <C> input type of output reducing function
 * @return a new transducer
 */
fun<A, B : Iterable<A>, C> mapcat(f: (C) -> B): Transducer<A, C> =
    map(f).comp(cat())

/**
 * Creates a transducer that transforms a reducing function by applying a
 * predicate to each input and not processing those inputs for which the
 * predicate is true.
 * @param p a predicate function
 * @param <A> input type of input and output reducing functions
 * @return a new transducer
 */
fun <A> remove(p: (A) -> Boolean): Transducer<A, A> =
    filter { !p(it) }

/**
 * Creates a transducer that transforms a reducing function such that
 * it only processes n inputs, then the reducing process stops.
 * @param n the number of inputs to process
 * @param <A> input type of input and output reducing functions
 * @return a new transducer
 */
fun <A> take(n: Long): Transducer<A, A> = object : Transducer<A, A> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, A>(rf) {
        private var taken = 0L
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            var ret = result
            if (taken < n) {
                ret = rf.apply(result, input, reduced)
                taken++
            }
            else {
                reduced.set(true)
            }
            return ret
        }
    }
}

/**
 * Creates a transducer that transforms a reducing function such that
 * it processes inputs as long as the provided predicate returns true.
 * If the predicate returns false, the reducing process stops.
 * @param p a predicate used to test inputs
 * @param <A> input type of input and output reducing functions
 * @return a new transducer
 */
fun <A> takeWhile(p: (A) -> Boolean): Transducer<A, A> = object : Transducer<A, A> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, A>(rf) {
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            var ret = result
            if (p(input)) {
                ret = rf.apply(ret, input, reduced)
            }
            else {
                reduced.set(true)
            }
            return ret
        }
    }
}

/**
 * Creates a transducer that transforms a reducing function such that
 * it skips n inputs, then processes the rest of the inputs.
 * @param n the number of inputs to skip
 * @param <A> input type of input and output reducing functions
 * @return a new transducer
 */
fun <A> drop(n: Long): Transducer<A, A> = object : Transducer<A, A> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, A>(rf) {
        private var dropped = 0L
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            var ret = result
            if (dropped < n) {
                dropped++
            }
            else {
                ret = rf.apply(ret, input, reduced)
            }
            return ret
        }
    }
}

/**
 * Creates a transducer that transforms a reducing function such that
 * it skips inputs as long as the provided predicate returns true.
 * Once the predicate returns false, the rest of the inputs are
 * processed.
 * @param p a predicate used to test inputs
 * @param <A> input type of input and output reducing functions
 * @return a new transducer
 */
fun <A> dropWhile(p: (A) -> Boolean): Transducer<A, A> = object : Transducer<A, A> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, A>(rf) {
        private var drop = true
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            if (drop && p(input)) {
                return result
            }
            drop = false
            return rf.apply(result, input, reduced)
        }
    }
}

/**
 * Creates a transducer that transforms a reducing function such that
 * it processes every nth input.
 * @param n The frequence of inputs to process (e.g., 3 processes every third input).
 * @param <A> The input type of the input and output reducing functions
 * @return a new transducer
 */
fun <A> takeNth(n: Long): Transducer<A, A> = object : Transducer<A, A> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, A>(rf) {
        private var nth = 0L
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            return if ((nth++ % n) == 0L) rf.apply(result, input, reduced) else result
        }
    }
}

/**
 * Creates a transducer that transforms a reducing function such that
 * inputs that are keys in the provided map are replaced by the corresponding
 * value in the map.
 * @param smap a map of replacement values
 * @param <A> the input type of the input and output reducing functions
 * @return a new transducer
 */
fun <A> replace(smap: Map<A, A>): Transducer<A, A> =
    map { if (smap.containsKey(it)) smap[it]!! else it }

/**
 * Creates a transducer that transforms a reducing function by applying a
 * function to each input and processing the resulting value, ignoring values
 * that are null.
 * @param f a function for processing inputs
 * @param <A> the input type of the input and output reducing functions
 * @return a new transducer
 */
fun <A : Any> keep(f: (A) -> A?): Transducer<A, A> = object : Transducer<A, A> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, A>(rf) {
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            val _input = f(input)
            return if (_input != null) rf.apply(result, _input, reduced) else result
        }
    }
}

/**
 * Creates a transducer that transforms a reducing function by applying a
 * function to each input and processing the resulting value, ignoring values
 * that are null.
 * @param f a function for processing inputs
 * @param <A> the input type of the input and output reducing functions
 * @return a new transducer
 */
fun <A : Any> keepIndexed(f: (Long, A) -> A?): Transducer<A, A> = object : Transducer<A, A> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, A>(rf) {
        private var n = 0L
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            val _input = f(++n, input)
            return if (_input != null) rf.apply(result, _input, reduced) else result
        }
    }
}

/**
 * Creates a transducer that transforms a reducing function such that
 * consecutive identical input values are removed, only a single value
 * is processed.
 * @param <A> the input type of the input and output reducing functions
 * @return a new transducer
 */
fun <A : Any> dedupe(): Transducer<A, A> = object : Transducer<A, A> {
    override fun <R> apply(rf: ReducingFunction<R, in A>) = object : ReducingFunctionOn<R, A, A>(rf) {
        var prior: A? = null
        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            var ret = result
            if (prior != input) {
                prior = input
                ret = rf.apply(ret, input, reduced)
            }
            return ret
        }
    }
}

/**
 * Creates a transducer that transforms a reducing function such that
 * it has the specified probability of processing each input.
 * @param prob the probability between expressed as a value between 0 and 1.
 * @param <A> the input type of the input and output reducing functions
 * @return a new transducer
 */
fun <A : Any> randomSample(prob: Double): Transducer<A, A> =
    filter { ThreadLocalRandom.current().nextDouble() < prob }

/**
 * Creates a transducer that transforms a reducing function that processes
 * iterables of input into a reducing function that processes individual inputs
 * by gathering series of inputs for which the provided partitioning function returns
 * the same value, only forwarding them to the next reducing function when the value
 * the partitioning function returns for a given input is different from the value
 * returned for the previous input.
 * @param f the partitioning function
 * @param <A> the input type of the input and output reducing functions
 * @param <P> the type returned by the partitioning function
 * @return a new transducer
 */
fun <A, P> partitionBy(f: (A) -> P): Transducer<Iterable<A>, A> = object : Transducer<Iterable<A>, A> {
    override fun <R> apply(rf: ReducingFunction<R, in Iterable<A>>) = object : ReducingFunction<R, A> {
        val part = ArrayList<A>()
        val mark: Any = Unit
        var prior: Any? = mark

        override fun apply(): R = rf.apply()

        override fun apply(result: R): R {
            var ret = result
            if (part.isNotEmpty()) {
                ret = rf.apply(result, ArrayList(part), AtomicBoolean())
                part.clear()
            }
            return rf.apply(ret)
        }

        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            val p = f(input)
            if (prior === mark || prior == p) {
                prior = p
                part.add(input)
                return result
            }

            val copy = ArrayList(part)
            prior = p
            part.clear()
            val ret = rf.apply(result, copy, reduced)
            if (!reduced.get()) {
                part.add(input)
            }
            return ret
        }
    }
}

/**
 * Creates a transducer that transforms a reducing function that processes
 * iterables of input into a reducing function that processes individual inputs
 * by gathering series of inputs into partitions of a given size, only forwarding
 * them to the next reducing function when enough inputs have been accrued. Processes
 * any remaining buffered inputs when the reducing process completes.
 * @param n the size of each partition
 * @param <A> the input type of the input and output reducing functions
 * @return a new transducer
 */
fun <A> partitionAll(n: Int): Transducer<Iterable<A>, A> = object : Transducer<Iterable<A>, A> {
    override fun <R> apply(rf: ReducingFunction<R, in Iterable<A>>) = object : ReducingFunction<R, A> {
        val part = ArrayList<A>()

        override fun apply(): R = rf.apply()

        override fun apply(result: R): R {
            var ret = result
            if (part.isNotEmpty()) {
                ret = rf.apply(result, ArrayList(part), AtomicBoolean())
                part.clear()
            }
            return rf.apply(ret)
        }

        override fun apply(result: R,
                           input: A,
                           reduced: AtomicBoolean): R {
            part.add(input)
            return if (n == part.size) {
                try {
                    rf.apply(result, ArrayList(part), reduced)
                }
                finally {
                    part.clear()
                }
            }
            else {
                result
            }
        }
    }
}

TransducersTest.kt

// Copyright 2014 Cognitect. All Rights Reserved.
// Copyright 2015 Benjamin Gudehus (updated code to Kotlin 1.0.0).
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//      http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS-IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

// This is a Kotlin port of https://github.com/cognitect-labs/transducers-java

package transducers

import org.junit.Test
import java.util.ArrayList
import java.util.concurrent.atomic.AtomicBoolean
import kotlin.test.assertEquals

class TransducersTest {

    @Test
    fun testMap() {
        transduce(
            map { it.toString() },
            object : StepFunction<String, String> {
                override fun apply(result: String,
                                   input: String,
                                   reduced: AtomicBoolean): String = "$result$input "
            },
            "",
            ints(10)
        ) assertEquals "0 1 2 3 4 5 6 7 8 9 "

        transduce(
            map { it },
            object : StepFunction<MutableList<Int>, Int> {
                override fun apply(result: MutableList<Int>,
                                   input: Int,
                                   reduced: AtomicBoolean): MutableList<Int> {
                    result.add(input + 1)
                    return result
                }
            },
            arrayListOf(),
            ints(10)
        ) assertEquals arrayListOf(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)

        transduce(
            STRINGIFY,
            ADD_STRING,
            arrayListOf(),
            longs(10)
        ) assertEquals arrayListOf("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")
    }

    @Test
    fun testFilter() {
        transduce(
            filter { it % 2 != 0 },
            ADD_INT,
            arrayListOf(),
            ints(10)
        ) assertEquals arrayListOf(1, 3, 5, 7, 9)
    }

    @Test
    fun testCat() {
        val data = arrayListOf(
            ints(10),
            ints(20)
        )

        val vals = transduce(
            cat(),
            ADD_INT,
            arrayListOf(),
            data
        )
        vals.size assertEquals 30

        var nums = ints(10)
        var i = 0
        for (j in nums.indices) {
            nums[j] assertEquals vals[i++]
        }

        nums = ints(20)
        for (j in nums.indices) {
            nums[j] assertEquals vals[i++]
        }
    }

    @Test
    fun testMapcat() {
        transduce(
            mapcat { i: Int -> i.toString().toList() },
            object : StepFunction<MutableList<Char>, Char> {
                override fun apply(result: MutableList<Char>,
                                   input: Char,
                                   reduced: AtomicBoolean): MutableList<Char> {
                    result.add(input)
                    return result
                }
            },
            arrayListOf(),
            ints(10)
        ) assertEquals arrayListOf('0', '1', '2', '3', '4', '5', '6', '7', '8', '9')
    }

    @Test
    fun testComp() {
        transduce(
            filter<Int> { it % 2 != 0 }.comp(map { it.toString() }),
            ADD_STRING,
            arrayListOf(),
            ints(10)
        ) assertEquals arrayListOf("1", "3", "5", "7", "9")

        transduce(
            filter<Long> { it % 2L != 0L }.comp(STRINGIFY),
            ADD_STRING,
            arrayListOf(),
            longs(10)
        ) assertEquals arrayListOf("1", "3", "5", "7", "9")
    }

    @Test
    fun testTake() {
        transduce(
            take(5),
            ADD_INT,
            arrayListOf(),
            ints(20)
        ) assertEquals arrayListOf(0, 1, 2, 3, 4)
    }

    @Test
    fun testTakeWhile() {
        transduce(
            takeWhile { it < 10 },
            ADD_INT,
            arrayListOf(),
            ints(20)
        ) assertEquals arrayListOf(0, 1, 2, 3, 4, 5, 6, 7, 8, 9)
    }

    @Test
    fun testDrop() {
        transduce(
            drop(5),
            ADD_INT,
            arrayListOf(),
            ints(10)
        ) assertEquals arrayListOf(5, 6, 7, 8, 9)
    }

    @Test
    fun testDropWhile() {
        transduce(
            dropWhile { it < 10 },
            ADD_INT,
            arrayListOf(),
            ints(20)
        ) assertEquals arrayListOf(10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
    }

    @Test
    fun testTakeNth() {
        transduce(
            takeNth(2),
            ADD_INT,
            arrayListOf(),
            ints(10)
        ) assertEquals arrayListOf(0, 2, 4, 6, 8)
    }

    @Test
    fun testReplace() {
        transduce(
            replace(hashMapOf(
                3 to 42
            )),
            ADD_INT,
            arrayListOf(),
            ints(5)
        ) assertEquals arrayListOf(0, 1, 2, 42, 4)
    }

    @Test
    fun testKeep() {
        transduce(
            keep { if ( it % 2 == 0 ) null else it },
            ADD_INT,
            arrayListOf(),
            ints(10)
        ) assertEquals arrayListOf(1, 3, 5, 7, 9)
    }

    @Test
    fun testKeepIndexed() {
        transduce(
            keepIndexed { index, value -> if ( index == 1L || index == 4L ) value else null },
            ADD_INT,
            arrayListOf(),
            ints(10)
        ) assertEquals arrayListOf(0, 3)
    }

    @Test
    fun testDedupe() {
        transduce(
            dedupe(),
            ADD_INT,
            arrayListOf(),
            arrayListOf(1, 2, 2, 3, 4, 5, 5, 5, 5, 5, 5, 5, 0)
        ) assertEquals arrayListOf(1, 2, 3, 4, 5, 0)
    }

    @Test
    fun testPartitionBy() {
        transduce(
            partitionBy { i: Int -> i },
            object : StepFunction<MutableList<Iterable<Int>>, Iterable<Int>> {
                override fun apply(result: MutableList<Iterable<Int>>,
                                   input: Iterable<Int>,
                                   reduced: AtomicBoolean): MutableList<Iterable<Int>> {
                    result.add(input.toList())
                    return result
                }
            },
            arrayListOf(),
            arrayListOf(1, 1, 1, 2, 2, 3, 4, 5, 5)
        ) assertEquals arrayListOf(
            arrayListOf(1, 1, 1),
            arrayListOf(2, 2),
            arrayListOf(3),
            arrayListOf(4),
            arrayListOf(5, 5)
        )
    }

    @Test
    fun testPartitionAll() {
        transduce(
            partitionAll<Int>(3),
            object : StepFunction<MutableList<Iterable<Int>>, Iterable<Int>> {
                override fun apply(result: MutableList<Iterable<Int>>,
                                   input: Iterable<Int>,
                                   reduced: AtomicBoolean): MutableList<Iterable<Int>> {
                    result.add(input.toList())
                    return result
                }
            },
            arrayListOf(),
            ints(10)
        ) assertEquals arrayListOf(
            arrayListOf(0, 1, 2),
            arrayListOf(3, 4, 5),
            arrayListOf(6, 7, 8),
            arrayListOf(9)
        )
    }

    @Test
    fun testSimpleCovariance() {
        val m = map<Int, Int> { it * 2 }
        val input = ints(20)

        val ADD_NUMBER = object : StepFunction<MutableCollection<Number>, Number> {
            override fun apply(result: MutableCollection<Number>,
                               input: Number,
                               reduced: AtomicBoolean): MutableCollection<Number> {
                result.add(input)
                return result
            }
        }

        transduce(
            m,
            ADD_NUMBER,
            ArrayList<Number>(input.size),
            input
        ).size assertEquals 20

        transduce(
            m.comp(filter<Number> { it.toDouble() > 10.0 }),
            ADD_NUMBER,
            ArrayList<Number>(input.size),
            input
        ).size assertEquals 14
    }

    private companion object {
        val STRINGIFY = map { i: Long -> i.toString() }

        val ADD_STRING = object : StepFunction<MutableList<String>, String> {
            override fun apply(result: MutableList<String>,
                               input: String,
                               reduced: AtomicBoolean): MutableList<String> {
                result.add(input)
                return result
            }
        }

        val ADD_INT = object : StepFunction<MutableList<Int>, Int> {
            override fun apply(result: MutableList<Int>,
                               input: Int,
                               reduced: AtomicBoolean): MutableList<Int> {
                result.add(input)
                return result
            }
        }
    }

    private fun ints(n: Int): List<Int> = (0..n - 1).toArrayList()

    private fun longs(n: Int): List<Long> = (0L..n - 1).toArrayList()

    private infix fun <T> T.assertEquals(expected: T) = assertEquals(expected, this)

}