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Add enriched and enrichedOutput DSL functions
Signed-off-by: Matheus Cruz <matheuscruz.dev@gmail.com>
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‎experimental/fluent/func/src/main/java/io/serverlessworkflow/fluent/func/dsl/EnrichWithModelBiFunction.java‎

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/*
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* Copyright 2020-Present The Serverless Workflow Specification Authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package io.serverlessworkflow.fluent.func.dsl;
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import io.serverlessworkflow.impl.WorkflowModel;
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/**
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* A function that enriches the current state by combining it with the root workflow input.
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*
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* <p>This is useful when you need to merge the last task output with the original workflow input,
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* where the last state is typed and the root input is a WorkflowModel.
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*
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* @param <T> The type of the last state
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* @param <R> The type of the enriched result
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*/
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@FunctionalInterface
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public interface EnrichWithModelBiFunction<T, R> {
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/**
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* Applies this function to enrich the last state with the root workflow input.
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*
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* @param lastState the output from the previous task with its actual type
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* @param rootInput the original workflow input as WorkflowModel
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* @return the enriched result combining both inputs
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*/
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R apply(T lastState, WorkflowModel rootInput);
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}

‎experimental/fluent/func/src/main/java/io/serverlessworkflow/fluent/func/dsl/FuncDSL.java‎

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import io.serverlessworkflow.fluent.spec.configurers.AuthenticationConfigurer;
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import io.serverlessworkflow.impl.TaskContextData;
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import io.serverlessworkflow.impl.WorkflowContextData;
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import io.serverlessworkflow.impl.WorkflowModel;
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import java.net.URI;
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import java.util.Collection;
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import java.util.List;
@@ -279,6 +280,117 @@ public static FuncPredicateEventConfigurer event(String type) {
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return OPS.event(type);
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}
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/**
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* Create an input transformation that enriches the typed last state with the root workflow input
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* as WorkflowModel.
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*
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* <p>This is useful when you want to combine the last task output (with its actual type) with the
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* original workflow input as WorkflowModel.
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*
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* <p>Example usage:
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*
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* <pre>{@code
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* function("processData", (Long input) -> input + 5, Long.class),
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* function("combineData", (Long enrichedValue) -> enrichedValue, Long.class)
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* .enrichInputWith((lastState, rootInputModel) -> {
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* Long rootInput = rootInputModel.as(Long.class).orElse(0L);
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* return lastState + rootInput;
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* }, Long.class)
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* }</pre>
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*
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* @param fn the enrichment function that receives typed lastState and WorkflowModel rootInput
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* @param lastStateClass the class of the last state type
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* @param <T> the type of the last state
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* @param <R> the type of the enriched result
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* @return a JavaContextFunction that can be used with inputFrom
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*/
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public static <T, R> JavaContextFunction<T, R> enriched(
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EnrichWithModelBiFunction<T, R> fn, Class<T> lastStateClass) {
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return (lastState, workflowContext) -> {
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final WorkflowModel rootInput = workflowContext.instanceData().input();
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return fn.apply(lastState, rootInput);
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};
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}
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/**
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* Create an input transformation that uses only the root workflow input as WorkflowModel.
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*
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* <p>This is useful when you want to transform the task input based solely on the original
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* workflow input, ignoring the last state.
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*
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* <p>Example usage:
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*
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* <pre>{@code
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* function("processData", (Long input) -> input * 2, Long.class)
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* .enrichWithInput(rootInput -> rootInput.asNumber().orElseThrow())
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* }</pre>
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*
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* @param fn the function that receives the root workflow input and returns the enriched result
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* @param <R> the type of the enriched result
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* @return a JavaContextFunction that can be used with inputFrom
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*/
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public static <R> JavaContextFunction<Object, R> enriched(Function<WorkflowModel, R> fn) {
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return (lastState, workflowContext) -> {
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final WorkflowModel rootInput = workflowContext.instanceData().input();
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return fn.apply(rootInput);
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};
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}
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/**
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* Create an output transformation that enriches the typed task output with the root workflow
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* input as WorkflowModel.
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*
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* <p>This is useful when you want to combine the task output (with its actual type) with the
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* original workflow input as WorkflowModel.
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*
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* <p>Example usage:
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*
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* <pre>{@code
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* function("processData", (Long input) -> input + 5, Long.class)
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* .outputAs(FuncDSL.enrichWithModel((taskOutput, rootInputModel) -> {
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* Long rootInput = rootInputModel.as(Long.class).orElse(0L);
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* return taskOutput + rootInput;
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* }, Long.class))
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* }</pre>
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*
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* @param fn the enrichment function that receives typed taskOutput and WorkflowModel rootInput
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* @param taskOutputClass the class of the task output type
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* @param <T> the type of the task output
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* @param <R> the type of the enriched result
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* @return a JavaContextFunction that can be used with outputAs
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*/
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public static <T, R> JavaContextFunction<T, R> enrichedOutput(
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EnrichWithModelBiFunction<T, R> fn, Class<T> taskOutputClass) {
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return (taskOutput, workflowContext) -> {
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final WorkflowModel rootInput = workflowContext.instanceData().input();
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return fn.apply(taskOutput, rootInput);
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};
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}
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/**
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* Create an output transformation that uses only the root workflow input as WorkflowModel.
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*
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* <p>This is useful when you want to transform the task output based solely on the original
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* workflow input, ignoring the actual task output.
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*
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* <p>Example usage:
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*
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* <pre>{@code
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* function("processData", (Long input) -> input * 2, Long.class)
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* .outputAs(FuncDSL.enrichWithInput(rootInput -> rootInput.asNumber().orElseThrow()))
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* }</pre>
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*
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* @param fn the function that receives the root workflow input and returns the enriched result
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* @param <R> the type of the enriched result
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* @return a JavaContextFunction that can be used with outputAs
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*/
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public static <R> JavaContextFunction<Object, R> enrichedOutput(Function<WorkflowModel, R> fn) {
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return (taskOutput, workflowContext) -> {
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final WorkflowModel rootInput = workflowContext.instanceData().input();
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return fn.apply(rootInput);
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};
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}
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/**
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* Create a {@link FuncCallStep} that calls a simple Java {@link Function} with explicit input
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* type.

‎experimental/fluent/func/src/main/java/io/serverlessworkflow/fluent/func/dsl/Step.java‎

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import io.serverlessworkflow.fluent.func.spi.ConditionalTaskBuilder;
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import io.serverlessworkflow.fluent.func.spi.FuncTaskTransformations;
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import io.serverlessworkflow.fluent.spec.TaskBaseBuilder;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.function.Consumer;
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private void applyPost(B builder) {
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for (Consumer<B> c : postConfigurers) c.accept(builder);
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}
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}

‎impl/test/pom.xml‎

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<artifactId>grpc-netty</artifactId>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>io.serverlessworkflow</groupId>
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<artifactId>serverlessworkflow-experimental-fluent-func</artifactId>
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<scope>test</scope>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>io.serverlessworkflow</groupId>
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<artifactId>serverlessworkflow-experimental-lambda</artifactId>
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<scope>test</scope>
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<version>${project.version}</version>
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</dependency>
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</dependencies>
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<build>
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<resources>

‎impl/test/src/test/java/io/serverlessworkflow/impl/test/FuncDSLEnrichWithTest.java‎

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/*
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* Copyright 2020-Present The Serverless Workflow Specification Authors
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package io.serverlessworkflow.impl.test;
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import static io.serverlessworkflow.fluent.func.dsl.FuncDSL.enriched;
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import static io.serverlessworkflow.fluent.func.dsl.FuncDSL.enrichedOutput;
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import static io.serverlessworkflow.fluent.func.dsl.FuncDSL.function;
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import io.serverlessworkflow.api.types.Workflow;
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import io.serverlessworkflow.fluent.func.FuncWorkflowBuilder;
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import io.serverlessworkflow.impl.WorkflowApplication;
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import io.serverlessworkflow.impl.WorkflowDefinition;
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import io.serverlessworkflow.impl.WorkflowModel;
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import org.assertj.core.api.SoftAssertions;
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import org.junit.jupiter.api.Test;
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class FuncDSLEnrichWithTest {
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@Test
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void test_enrich_with_model_in_workflow() {
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SoftAssertions softly = new SoftAssertions();
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Workflow workflow =
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FuncWorkflowBuilder.workflow("reviewSubmissionWithModel")
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.tasks(
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function(
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"add5",
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(Long input) -> {
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softly.assertThat(input).isEqualTo(10L);
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return input + 5;
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},
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Long.class),
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function("returnEnriched", (Long enrichedValue) -> enrichedValue, Long.class)
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.inputFrom(
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enriched(
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(lastState, rootInputModel) -> {
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softly.assertThat(lastState).isEqualTo(15L);
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Long originalInput = rootInputModel.as(Long.class).orElse(0L);
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softly.assertThat(originalInput).isEqualTo(10L);
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return lastState + originalInput;
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},
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Long.class)))
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.build();
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WorkflowApplication app = WorkflowApplication.builder().build();
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WorkflowDefinition def = app.workflowDefinition(workflow);
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WorkflowModel model = def.instance(10L).start().join();
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Number number = model.asNumber().orElseThrow();
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softly.assertThat(number.longValue()).isEqualTo(25L);
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softly.assertAll();
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}
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@Test
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void test_enrich_with_input_workflow() {
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SoftAssertions softly = new SoftAssertions();
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Workflow workflow =
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FuncWorkflowBuilder.workflow("enrichWithInputTest")
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.tasks(
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function(
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"add5",
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(Long input) -> {
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softly.assertThat(input).isEqualTo(10L);
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return input + 5;
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},
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Long.class),
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function(
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"returnEnriched",
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(Long enrichedValue) -> {
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softly.assertThat(enrichedValue).isEqualTo(10L);
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return enrichedValue;
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},
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Long.class)
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.inputFrom(
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enriched(rootInput -> rootInput.asNumber().orElseThrow().longValue())))
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.build();
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WorkflowApplication app = WorkflowApplication.builder().build();
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WorkflowDefinition def = app.workflowDefinition(workflow);
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WorkflowModel model = def.instance(10L).start().join();
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Number number = model.asNumber().orElseThrow();
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softly.assertThat(number).isEqualTo(10L);
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}
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@Test
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void test_enrich_output_with_model_in_workflow() {
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SoftAssertions softly = new SoftAssertions();
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Workflow workflow =
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FuncWorkflowBuilder.workflow("enrichOutputWithModelTest")
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.tasks(
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function(
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"add5",
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(Long input) -> {
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softly.assertThat(input).isEqualTo(10L);
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return input + 5;
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},
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Long.class)
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.outputAs(
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enrichedOutput(
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(taskOutput, rootInputModel) -> {
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// taskOutput is typed as Long (result from add5) = 15
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softly.assertThat(taskOutput).isEqualTo(15L);
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// rootInput is WorkflowModel (original input) = 10
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Long originalInput = rootInputModel.as(Long.class).orElse(0L);
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softly.assertThat(originalInput).isEqualTo(10L);
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// Return the sum: 15 + 10
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return taskOutput + originalInput;
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},
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Long.class)))
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.build();
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WorkflowApplication app = WorkflowApplication.builder().build();
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WorkflowDefinition def = app.workflowDefinition(workflow);
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WorkflowModel model = def.instance(10L).start().join();
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Number number = model.asNumber().orElseThrow();
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softly.assertThat(number.longValue()).isEqualTo(25L);
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softly.assertAll();
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}
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@Test
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void test_enrich_output_with_input_in_workflow() {
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SoftAssertions softly = new SoftAssertions();
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Workflow workflow =
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FuncWorkflowBuilder.workflow("enrichOutputWithInputTest")
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.tasks(
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function(
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"add5",
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(Long input) -> {
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softly.assertThat(input).isEqualTo(10L);
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return input + 5;
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},
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Long.class)
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.outputAs(
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enrichedOutput(
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rootInput -> {
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Long value = rootInput.asNumber().orElseThrow().longValue();
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softly.assertThat(value).isEqualTo(10L);
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return value;
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})))
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.build();
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WorkflowApplication app = WorkflowApplication.builder().build();
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WorkflowDefinition def = app.workflowDefinition(workflow);
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WorkflowModel model = def.instance(10L).start().join();
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Number number = model.asNumber().orElseThrow();
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softly.assertThat(number.longValue()).isEqualTo(10L);
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softly.assertAll();
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}
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}

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