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.
Also see the introductory blog post and this video.
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- Latest release: 0.4.67
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Maven dependency information:
<dependency>
<groupId>com.cognitect</groupId>
<artifactId>transducers-java</artifactId>
<version>0.4.67</version>
</dependency>The Fns class in the com.cognitect.transducers package provide the available transducing functionality. To use this library, simple import the package as such:
import static com.cognitect.transducers.Fns.*;All of the methods on the Fns class are static.
A Transducer transforms a reducing function of one type into a reducing function of another (possibly the same) type. For the sake of illustration, you can define an com.cognitect.transducers.ITransducer mapping instance that encapsulates an operation that takes Longs and converts them into Strings:
ITransducer<String, Long> stringify = map(new Function<Long, String>() {
@Override
public String apply(Long i) {
return i.toString();
}
});Because Transducers are agnostic to both the source of their inputs and the target of their intermediate sub-processes, you need a way to independently supply these elements for the purpose of executing an operation. The specification of the intermediate stages is given by creating an instance of an com.cognitect.transducers.IStepFunction, shown below:
IStepFunction<List<String>, String> addString = new IStepFunction<List<String>, String>() {
@Override
public List<String> apply(List<String> result, String input, AtomicBoolean reduced) {
result.add(input);
return result;
}
};The addString function supplies the knowledge of how to accumulate the result of an operation. In this case, addString accepts a list and a String instance and adds it to the end of the list. One of the most common ways to apply transducers is with the com.cognitect.transducers.Fns#transduce method, which is analogous to a standard reduce or foldl function found in many functional programming languages. Given the Transducer stringify and the step function addString, you can initiate the mapping process by simply providing an ArrayList<String> instance serving as the output target for the step function and a list of Longs serving as the source of data for the whole operation:
transduce(stringify, addString, new ArrayList<String>(), longs(10));
//=> ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"]The longs method is a convenience (not shown here) that returns a list of Long instances.
Transducers are composable, allowing you to define aggregate processes from parts. To show this, you can define a Transducer named filterOdds that is meant to identify odd numbered Longs via the results of a com.cognitect.transducers.Predicate instance:
ITransducer<Long, Long> filterOdds = filter(new Predicate<Long>() {
@Override
public boolean test(Long num) {
return num.longValue() % 2 != 0;
}
}); Transducers are composed using the com.cognitect.transducers.Fns#compose method:
ITransducer<String, Long> stringifyOdds = filterOdds.comp(stringify);The transducer stringifyOdds is a transformation stack that will be applied by a process to a series of input elements:
transduce(stringifyOdds, addString, new ArrayList<String>(), longs(10));
//=> ["1", "3", "5", "7", "9"]For more examples of using Transducers, you can view the transducers-java JavaDocs and the com.cognitect.transducers.Fns test suite.
This library is open source, developed internally by Cognitect. Issues can be filed using GitHub Issues.
This project is provided without support or guarantee of continued development. Because transducers-java may be incorporated into products or client projects, we prefer to do development internally and do not accept pull requests or patches.
Copyright © 2014 Cognitect
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.
