# Spring Statemachine - Reference Documentation ## Preface The concept of a state machine is most likely older than any reader of this reference documentation and definitely older than the Java language itself. Description of finite automata dates back to 1943 when gentlemen Warren McCulloch and Walter Pitts wrote a paper about it. Later George H. Mealy presented a state machine concept (known as a “Mealy Machine”) in 1955. A year later, in 1956, Edward F. Moore presented another paper, in which he described what is known as a “Moore Machine”. If you have ever read anything about state machines, the names, Mealy and Moore, should have popped up at some point. This reference documentation contains the following parts: [Introduction](#introduction) contains introduction to this reference documentation. [Using Spring Statemachine](#statemachine) describes the usage of Spring Statemachine(SSM). [State Machine Examples](#statemachine-examples) contains more detailed state machine examples. [FAQ](#statemachine-faq) contains frequently asked questions. [Appendices](#appendices) contains generic information about used material and state machines. # Introduction Spring Statemachine (SSM) is a framework that lets application developers use traditional state machine concepts with Spring applications. SSM provides the following features: * Easy-to-use flat (one-level) state machine for simple use cases. * Hierarchical state machine structure to ease complex state configuration. * State machine regions to provide even more complex state configurations. * Usage of triggers, transitions, guards, and actions. * Type-safe configuration adapter. * State machine event listeners. * Spring IoC integration to associate beans with a state machine. Before you continue, we recommend going through the appendices [Glossary](#glossary)and [A State Machine Crash Course](#crashcourse) to get a generic idea of what state machines are. The rest of the documentation expects you to be familiar with state machine concepts. ## Background State machines are powerful because their behavior is always guaranteed to be consistent and relatively easily debugged due to how operational rules are written in stone when a machine is started. The idea is that your application is now in and may exist in a finite number of states. Then something happens that takes your application from one state to the next. A state machine is driven by triggers, which are based on either events or timers. It is much easier to design high-level logic outside of your application and then interact with a state machine in various different ways. You can interact with a state machine by sending events, listening to what a state machine does, or requesting the current state. Traditionally, state machines are added to an existing project when developers realize that the code base is starting to look like a plate full of spaghetti. Spaghetti code looks like a never ending, hierarchical structure of IF, ELSE, and BREAK clauses, and compilers should probably ask developers to go home when things are starting to look too complex. ## Usage Scenarios A project is a good candidate to use a state machine when: * You can represent the application or part of its structure as states. * You want to split complex logic into smaller manageable tasks. * The application is already suffering concurrency issues with (for example) something happening asynchronously. You are already trying to implement a state machine when you: * Use boolean flags or enums to model situations. * Have variables that have meaning only for some part of your application lifecycle. * Loop through an if-else structure (or, worse, multiple such structures), check whether a particular flag or enum is set, and then make further exceptions about what to do when certain combinations of your flags and enums exist or do not exist. # Getting started If you are just getting started with Spring Statemachine, this is the section for you! Here, we answer the basic “`what?`”, “`how?`” and “`why?`” questions. We start with a gentle introduction to Spring Statemachine. We then build our first Spring Statemachine application and discuss some core principles as we go. ## System Requirement Spring Statemachine 3.0.1 is built and tested with JDK 8 (all artifacts have JDK 7 compatibility) and Spring Framework 5.3.8. It does not require any other dependencies outside of Spring Framework within its core system. Other optional parts (such as [Using Distributed States](#sm-distributed)) have dependencies on Zookeeper, while [State Machine Examples](#statemachine-examples) has dependencies on `spring-shell` and `spring-boot`, which pull other dependencies beyond the framework itself. Also, the optional security and data access features have dependencies to on Spring Security and Spring Data modules. ## Modules The following table describes the modules that are available for Spring Statemachine. | Module | Description | |------------------------------------|----------------------------------------------------------------------------------------------------------------------| | `spring-statemachine-core` | The core system of Spring Statemachine. | |`spring-statemachine-recipes-common`| Common recipes that do not require dependencies outside of the core
framework. | | `spring-statemachine-kryo` | `Kryo` serializers for Spring Statemachine. | | `spring-statemachine-data-common` | Common support module for `Spring Data`. | | `spring-statemachine-data-jpa` | Support module for `Spring Data JPA`. | | `spring-statemachine-data-redis` | Support module for `Spring Data Redis`. | | `spring-statemachine-data-mongodb` | Support module for `Spring Data MongoDB`. | | `spring-statemachine-zookeeper` | Zookeeper integration for a distributed state machine. | | `spring-statemachine-test` | Support module for state machine testing. | | `spring-statemachine-cluster` |Support module for Spring Cloud Cluster.
Note that Spring Cloud Cluster has been superseded by Spring Integration.| | `spring-statemachine-uml` | Support module for UI UML modeling with Eclipse Papyrus. | |`spring-statemachine-autoconfigure` | Support module for Spring Boot. | | `spring-statemachine-bom` | Bill of Materials pom. | | `spring-statemachine-starter` | Spring Boot starter. | ## Using Gradle The following listing shows a typical `build.gradle` file created by choosing various settings at [https://start.spring.io](https://start.spring.io): ``` buildscript { ext { springBootVersion = '2.4.8' } repositories { mavenCentral() maven { url "https://repo.spring.io/snapshot" } maven { url "https://repo.spring.io/milestone" } } dependencies { classpath("org.springframework.boot:spring-boot-gradle-plugin:${springBootVersion}") } } apply plugin: 'java' apply plugin: 'eclipse' apply plugin: 'org.springframework.boot' apply plugin: 'io.spring.dependency-management' group = 'com.example' version = '0.0.1-SNAPSHOT' sourceCompatibility = 1.8 repositories { mavenCentral() maven { url "https://repo.spring.io/snapshot" } maven { url "https://repo.spring.io/milestone" } } ext { springStatemachineVersion = '3.0.1' } dependencies { compile('org.springframework.statemachine:spring-statemachine-starter') testCompile('org.springframework.boot:spring-boot-starter-test') } dependencyManagement { imports { mavenBom "org.springframework.statemachine:spring-statemachine-bom:${springStatemachineVersion}" } } ``` | |Replace `0.0.1-SNAPSHOT` with a version you want to use.| |---|--------------------------------------------------------| With a normal project structure, you can build this project with the following command: ``` # ./gradlew clean build ``` The expected Spring Boot-packaged fat jar would be `build/libs/demo-0.0.1-SNAPSHOT.jar`. | |You do not need the`libs-milestone` and `libs-snapshot` repositories for
production development.| |---|----------------------------------------------------------------------------------------------------| ## Using Maven The following example shows a typical `pom.xml` file, which was created by choosing various options at [https://start.spring.io](https://start.spring.io): ``` 4.0.0 com.example demo 0.0.1-SNAPSHOT jar gs-statemachine Demo project for Spring Statemachine org.springframework.boot spring-boot-starter-parent 2.4.8 UTF-8 UTF-8 1.8 3.0.1 org.springframework.statemachine spring-statemachine-starter org.springframework.boot spring-boot-starter-test test org.springframework.statemachine spring-statemachine-bom ${spring-statemachine.version} pom import org.springframework.boot spring-boot-maven-plugin spring-snapshots Spring Snapshots https://repo.spring.io/snapshot true spring-milestones Spring Milestones https://repo.spring.io/milestone false spring-snapshots Spring Snapshots https://repo.spring.io/snapshot true spring-milestones Spring Milestones https://repo.spring.io/milestone false ``` | |Replace `0.0.1-SNAPSHOT` with a version you want to use.| |---|--------------------------------------------------------| With a normal project structure, you can build this project with the following command: ``` # mvn clean package ``` The expected Spring Boot-packaged fat-jar would be `target/demo-0.0.1-SNAPSHOT.jar`. | |You do not need the `libs-milestone` and `libs-snapshot` repositories for
production development.| |---|-----------------------------------------------------------------------------------------------------| ## Developing Your First Spring Statemachine Application You can start by creating a simple Spring Boot `Application` class that implements `CommandLineRunner`. The following example shows how to do so: ``` @SpringBootApplication public class Application implements CommandLineRunner { public static void main(String[] args) { SpringApplication.run(Application.class, args); } } ``` Then you need to add states and events, as the following example shows: ``` public enum States { SI, S1, S2 } public enum Events { E1, E2 } ``` Then you need to add state machine configuration, as the following example shows: ``` @Configuration @EnableStateMachine public class StateMachineConfig extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withConfiguration() .autoStartup(true) .listener(listener()); } @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.SI) .states(EnumSet.allOf(States.class)); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.SI).target(States.S1).event(Events.E1) .and() .withExternal() .source(States.S1).target(States.S2).event(Events.E2); } @Bean public StateMachineListener listener() { return new StateMachineListenerAdapter() { @Override public void stateChanged(State from, State to) { System.out.println("State change to " + to.getId()); } }; } } ``` Then you need to implement `CommandLineRunner` and autowire `StateMachine`. The following example shows how to do so: ``` @Autowired private StateMachine stateMachine; @Override public void run(String... args) throws Exception { stateMachine.sendEvent(Events.E1); stateMachine.sendEvent(Events.E2); } ``` Depending on whether you build your application with `Gradle` or `Maven`, you can run it by using `java -jar build/libs/gs-statemachine-0.1.0.jar` or`java -jar target/gs-statemachine-0.1.0.jar`, respectively. The result of this command should be normal Spring Boot output. However, you should also find the following lines: ``` State change to SI State change to S1 State change to S2 ``` These lines indicate that the machine you constructed is moving from one state to another, as it should. # What’s New ## In 1.1 Spring Statemachine 1.1 focuses on security and better interoperability with web applications. It includes the following: * Comprehensive support for Spring Security has been added. See [State Machine Security](#sm-security). * Context integration with `@WithStateMachine' has been greatly enhanced. See [Context Integration](#sm-context). * `StateContext` is now a first class citizen, letting you interact with a State Machine. See [Using `StateContext`](#sm-statecontext). * Features around persistence have been enhanced with built-in support for redis. See [Using Redis](#sm-persist-redis). * A new feature helps with persist operations. See[Using `StateMachinePersister`](#sm-persist-statemachinepersister). * Configuration model classes are now in a public API. * New features in timer-based events. * New `Junction` pseudostate. See [Junction State](#statemachine-config-states-junction). * New Exit Point and Entry Point pseudostates. See [Exit and Entry Point States](#statemachine-config-states-exitentry). * Configuration model verifier. * New samples. See [Security](#statemachine-examples-security) and [Event Service](#statemachine-examples-eventservice). * UI modeling support using Eclipse Papyrus. See [Eclipse Modeling Support](#sm-papyrus). ## In 1.2 Spring Statemachine 1.2 focuses on generic enhancements, better UML support, and integrations with external config repositories. It includes the following: * Support for UML sub-machines. See [Using a Sub-Machine Reference](#sm-papyrus-submachineref). * A new repository abstraction that keeps machine configuration in an external repository. See [Repository Support](#sm-repository). * New support for state actions. See [State Actions](#state-actions). * New transition error action concepts. See [Transition Action Error Handling](#statemachine-config-transition-actions-errorhandling). * New action error concepts. See [State Action Error Handling](#statemachine-config-state-actions-errorhandling). * Initial work for Spring Boot support. See [Spring Boot Support](#sm-boot). * Support for tracing and monitoring. See [Monitoring a State Machine](#sm-monitoring). ### In 1.2.8 Spring Statemachine 1.2.8 contains a bit more functionality than normally not seen in a point release, but these changes did not merit a fork of Spring Statemachine 1.3. It includes the following: * JPA entity classes have changed table names. See [JPA](#sm-repository-config-jpa). * A new sample. See [Data Persist](#statemachine-examples-datapersist). * New entity classes for persistence. See [Repository Persistence](#sm-repository-persistence). * Transition conflict policy. See[Configuring Common Settings](#statemachine-config-commonsettings) ## In 2.0 Spring Statemachine 2.0 focuses on Spring Boot 2.x support. ### In 2.0.0 Spring Statemachine 2.0.0 includes the following: * The format of monitoring and tracing has been changed. See [Monitoring and Tracing](#sm-boot-monitoring). * The `spring-statemachine-boot` module has been renamed to `spring-statemachine-autoconfigure`. ## In 3.0 Spring Statemachine 3.0.0 focuses on adding a Reactive support. Moving from `2.x` to `3.x` is introducing some breaking changes which are detailed in [Reactor Migration Guide](#appendix-reactormigrationguide). With `3.0.x` we have deprecated all blocking methods which will get removed at some point in a future releases. | |Please read an appendix [Reactor Migration Guide](#appendix-reactormigrationguide) carefully as it will steer you
through a process of migrating into `3.x` for cases we’re not handling internallyl.| |---|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| At this point most of a documentation has been changed to showcase reactive interfaces while we still keep some notes around to users still using old blocking methods. # Using Spring Statemachine This part of the reference documentation explains the core functionality that Spring Statemachine provides to any Spring based application. It includes the following topics: * [Statemachine Configuration](#sm-config) describes the generic configuration support. * [State Machine ID](#sm-machineid) describes the use of machine id. * [State Machine Factories](#sm-factories) describes the generic state machine factory support. * [Using Deferred Events](#sm-deferevents) describes the deferred event support. * [Using Scopes](#sm-scopes) describes the scope support. * [Using Actions](#sm-actions) describes the actions support. * [Using Guards](#sm-guards) describes the guard support. * [Using Extended State](#sm-extendedstate) describes the extended state support. * [Using `StateContext`](#sm-statecontext) describes the state context support. * [Triggering Transitions](#sm-triggers) describes the use of triggers. * [Listening to State Machine Events](#sm-listeners) describes the use of state machine listeners. * [Context Integration](#sm-context) describes the generic Spring application context support. * [Using `StateMachineAccessor`](#sm-accessor) describes the state machine internal accessor support. * [Using `StateMachineInterceptor`](#sm-interceptor) describes the state machine error handling support. * [State Machine Security](#sm-security) describes the state machine security support. * [State Machine Error Handling](#sm-error-handling) describes the state machine interceptor support. * [State Machine Services](#sm-service) describes the state machine service support. * [Persisting a State Machine](#sm-persist) describes the state machine persisting support. * [Spring Boot Support](#sm-boot) describes the Spring Boot support. * [Monitoring a State Machine](#sm-monitoring) describes the monitoring and trancing support. * [Using Distributed States](#sm-distributed) describes the distributed state machine support. * [Testing Support](#sm-test) describes the state machine testing support. * [Eclipse Modeling Support](#sm-papyrus) describes the state machine UML modeling support. * [Repository Support](#sm-repository) describes the state machine repository config support. ## Statemachine Configuration One of the common tasks when using a state machine is to design its runtime configuration. This chapter focuses on how Spring Statemachine is configured and how it leverages Spring’s lightweight IoC containers to simplify the application internals to make it more manageable. | |Configuration examples in this section are not feature complete. That is,
you always need to have definitions of both states and transitions.
Otherwise, state machine configuration would be ill-formed. We have
simply made code snippets less verbose by leaving other needed parts
out.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ### Using `enable` Annotations We use two familiar Spring *enabler* annotations to ease configuration:`@EnableStateMachine` and `@EnableStateMachineFactory`. These annotations, when placed in a `@Configuration` class, enable some basic functionality needed by a state machine. You can use `@EnableStateMachine` when you need a configuration to create an instance of `StateMachine`. Usually, a `@Configuration` class extends adapters (`EnumStateMachineConfigurerAdapter` or `StateMachineConfigurerAdapter`), which lets you override configuration callback methods. We automatically detect whether you use these adapter classes and modify the runtime configuration logic accordingly. You can use `@EnableStateMachineFactory` when you need a configuration to create an instance of a `StateMachineFactory`. | |Usage examples of these are shown in below sections.| |---|----------------------------------------------------| ### Configuring States We get into more complex configuration examples a bit later in this guide, but we first start with something simple. For most simple state machine, you can use `EnumStateMachineConfigurerAdapter` and define possible states and choose the initial and optional end states. ``` @Configuration @EnableStateMachine public class Config1Enums extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.S1) .end(States.SF) .states(EnumSet.allOf(States.class)); } } ``` You can also use strings instead of enumerations as states and events by using `StateMachineConfigurerAdapter`, as shown in the next example. Most of the configuration examples ues enumerations, but, generally speaking, you can interchange strings and enumerations. ``` @Configuration @EnableStateMachine public class Config1Strings extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S1") .end("SF") .states(new HashSet(Arrays.asList("S1","S2","S3","S4"))); } } ``` | |Using enumerations brings a safer set of states and event types but
limits possible combinations to compile time. Strings do not have this
limitation and let you use more dynamic ways to build state
machine configurations but do not allow same level of safety.| |---|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ### Configuring Hierarchical States You can define hierarchical states can by using multiple `withStates()`calls, where you can use `parent()` to indicate that these particular states are sub-states of some other state. The following example shows how to do so: ``` @Configuration @EnableStateMachine public class Config2 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.S1) .state(States.S1) .and() .withStates() .parent(States.S1) .initial(States.S2) .state(States.S2); } } ``` ### Configuring Regions There are no special configuration methods to mark a collection of states to be part of an orthogonal state. To put it simply, orthogonal state is created when the same hierarchical state machine has multiple sets of states, each of which has an initial state. Because an individual state machine can only have one initial state, multiple initial states must mean that a specific state must have multiple independent regions. The following example shows how to define regions: ``` @Configuration @EnableStateMachine public class Config10 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States2.S1) .state(States2.S2) .and() .withStates() .parent(States2.S2) .initial(States2.S2I) .state(States2.S21) .end(States2.S2F) .and() .withStates() .parent(States2.S2) .initial(States2.S3I) .state(States2.S31) .end(States2.S3F); } } ``` When persisting machines with regions or generally relying on any functionalities to reset a machine, you may need to have a dedicated ID for a region. By default, this ID is a generated UUID. As the following example shows, `StateConfigurer` has a method called `region(String id)` that lets you set the ID for a region: ``` @Configuration @EnableStateMachine public class Config10RegionId extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States2.S1) .state(States2.S2) .and() .withStates() .parent(States2.S2) .region("R1") .initial(States2.S2I) .state(States2.S21) .end(States2.S2F) .and() .withStates() .parent(States2.S2) .region("R2") .initial(States2.S3I) .state(States2.S31) .end(States2.S3F); } } ``` ### Configuring Transitions We support three different types of transitions: `external`,`internal`, and `local`. Transitions are triggered either by a signal (which is an event sent into a state machine) or by a timer. The following example shows how to define all three kinds of transitions: ``` @Configuration @EnableStateMachine public class Config3 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.S1) .states(EnumSet.allOf(States.class)); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.S1).target(States.S2) .event(Events.E1) .and() .withInternal() .source(States.S2) .event(Events.E2) .and() .withLocal() .source(States.S2).target(States.S3) .event(Events.E3); } } ``` ### Configuring Guards You can use guards to protect state transitions. You can use the `Guard` interface to do an evaluation where a method has access to a `StateContext`. The following example shows how to do so: ``` @Configuration @EnableStateMachine public class Config4 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.S1).target(States.S2) .event(Events.E1) .guard(guard()) .and() .withExternal() .source(States.S2).target(States.S3) .event(Events.E2) .guardExpression("true"); } @Bean public Guard guard() { return new Guard() { @Override public boolean evaluate(StateContext context) { return true; } }; } } ``` In the preceding example, we used two different types of guard configurations. First, we created a simple `Guard` as a bean and attached it to the transition between states `S1` and `S2`. Second, we used a SPeL expression as a guard to dicate that the expression must return a `BOOLEAN` value. Behind the scenes, this expression-based guard is a `SpelExpressionGuard`. We attached it to the transition between states `S2` and `S3`. Both guards always evaluate to `true`. ### Configuring Actions You can define actions to be executed with transitions and states. An action is always run as a result of a transition that originates from a trigger. The following example shows how to define an action: ``` @Configuration @EnableStateMachine public class Config51 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.S1) .target(States.S2) .event(Events.E1) .action(action()); } @Bean public Action action() { return new Action() { @Override public void execute(StateContext context) { // do something } }; } } ``` In the preceding example, a single `Action` is defined as a bean named `action` and associated with a transition from `S1` to `S2`. The following example shows how to use an action multiple times: ``` @Configuration @EnableStateMachine public class Config52 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.S1, action()) .state(States.S1, action(), null) .state(States.S2, null, action()) .state(States.S2, action()) .state(States.S3, action(), action()); } @Bean public Action action() { return new Action() { @Override public void execute(StateContext context) { // do something } }; } } ``` | |Usually, you would not define the same `Action` instance for different
stages, but we did it here to not make too much noise in a code
snippet.| |---|-------------------------------------------------------------------------------------------------------------------------------------------------------| In the preceding example, a single `Action` is defined by the bean named `action` and associated with states `S1`, `S2`, and `S3`. We need to clarify what is going on here: * We defined an action for the initial state, `S1`. * We defined an entry action for state `S1` and left the exit action empty. * We defined an exit action for state `S2` and left the entry action empty. * We defined a single state action for state `S2`. * We defined both entry and exit actions for state `S3`. * Note that state `S1` is used twice with `initial()` and `state()`functions. You need to do this only if you want to define entry or exit actions with initial state. | |Defining action with `initial()` function only runs a particular
action when a state machine or sub state is started. This action
is an initializing action that is run only once. An action defined
with `state()` is then run if the state machine transitions back
and forward between initial and non-initial states.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| #### State Actions State actions are run differently compared to entry and exit actions, because execution happens after state has been entered and can be cancelled if state exit happens before a particular action has been completed. State actions are executed using normal reactive flow by subscribing with a Reactor’s default parallel scheduler. This means that, whatever you do in your action, you need to be able to catch `InterruptedException` or, more generally, periodically check whether `Thread` is interrupted. The following example shows typical configuration that uses default the `IMMEDIATE_CANCEL`, which would immediately cancel a running task when its state is complete: ``` @Configuration @EnableStateMachine static class Config1 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withConfiguration() .stateDoActionPolicy(StateDoActionPolicy.IMMEDIATE_CANCEL); } @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S1") .state("S2", context -> {}) .state("S3"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S1") .target("S2") .event("E1") .and() .withExternal() .source("S2") .target("S3") .event("E2"); } } ``` You can set a policy to `TIMEOUT_CANCEL` together with a global timeout for each machine. This changes state behavior to await action completion before cancelation is requested. The following example shows how to do so: ``` @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withConfiguration() .stateDoActionPolicy(StateDoActionPolicy.TIMEOUT_CANCEL) .stateDoActionPolicyTimeout(10, TimeUnit.SECONDS); } ``` If `Event` directly takes a machine into a state so that event headers are available to a particular action, you can also use a dedicated event header to set a specific timeout (defined in `millis`). You can use the reserved header value `StateMachineMessageHeaders.HEADER_DO_ACTION_TIMEOUT`for this purpose. The following example shows how to do so: ``` @Autowired StateMachine stateMachine; void sendEventUsingTimeout() { stateMachine .sendEvent(Mono.just(MessageBuilder .withPayload("E1") .setHeader(StateMachineMessageHeaders.HEADER_DO_ACTION_TIMEOUT, 5000) .build())) .subscribe(); } ``` #### Transition Action Error Handling You can always catch exceptions manually. However, with actions defined for transitions, you can define an error action that is called if an exception is raised. The exception is then available from a `StateContext`passed to that action. The following example shows how to create a state that handles an exception: ``` @Configuration @EnableStateMachine public class Config53 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.S1) .target(States.S2) .event(Events.E1) .action(action(), errorAction()); } @Bean public Action action() { return new Action() { @Override public void execute(StateContext context) { throw new RuntimeException("MyError"); } }; } @Bean public Action errorAction() { return new Action() { @Override public void execute(StateContext context) { // RuntimeException("MyError") added to context Exception exception = context.getException(); exception.getMessage(); } }; } } ``` If need be, you can manually create similar logic for every action. The following example shows how to do so: ``` @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.S1) .target(States.S2) .event(Events.E1) .action(Actions.errorCallingAction(action(), errorAction())); } ``` #### State Action Error Handling Logic similar to the logic that handles errors in state transitions is also available for entry to a state and exit from a state. For these situations, `StateConfigurer` has methods called `stateEntry`, `stateDo`, and`stateExit`. These methods define an `error` action together with a normal (non-error) `action`. The following example shows how to use all three methods: ``` @Configuration @EnableStateMachine public class Config55 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.S1) .stateEntry(States.S2, action(), errorAction()) .stateDo(States.S2, action(), errorAction()) .stateExit(States.S2, action(), errorAction()) .state(States.S3); } @Bean public Action action() { return new Action() { @Override public void execute(StateContext context) { throw new RuntimeException("MyError"); } }; } @Bean public Action errorAction() { return new Action() { @Override public void execute(StateContext context) { // RuntimeException("MyError") added to context Exception exception = context.getException(); exception.getMessage(); } }; } } ``` ### Configuring Pseudo States *Pseudo state* configuration is usually done by configuring states and transitions. Pseudo states are automatically added to state machine as states. #### Initial State You can mark a particular state as initial state by using the `initial()`method. This initial action is good, for example, to initialize extended state variables. The following example shows how to use the `initial()` method: ``` @Configuration @EnableStateMachine public class Config11 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.S1, initialAction()) .end(States.SF) .states(EnumSet.allOf(States.class)); } @Bean public Action initialAction() { return new Action() { @Override public void execute(StateContext context) { // do something initially } }; } } ``` #### Terminate State You can mark a particular state as being an end state by using the `end()` method. You can do so at most once for each individual sub-machine or region. The following example shows how to use the `end()` method: ``` @Configuration @EnableStateMachine public class Config1Enums extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.S1) .end(States.SF) .states(EnumSet.allOf(States.class)); } } ``` #### State History You can define state history once for each individual state machine. You need to choose its state identifier and set either `History.SHALLOW` or`History.DEEP`. The following example uses `History.SHALLOW`: ``` @Configuration @EnableStateMachine public class Config12 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States3.S1) .state(States3.S2) .and() .withStates() .parent(States3.S2) .initial(States3.S2I) .state(States3.S21) .state(States3.S22) .history(States3.SH, History.SHALLOW); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withHistory() .source(States3.SH) .target(States3.S22); } } ``` Also, as the preceding example shows, you can optionally define a default transition from a history state into a state vertex in a same machine. This transition takes place as a default if, for example, the machine has never been entered — thus, no history would be available. If a default state transition is not defined, then normal entry into a region is done. This default transition is also used if a machine’s history is a final state. #### Choice State Choice needs to be defined in both states and transitions to work properly. You can mark a particular state as being a choice state by using the `choice()`method. This state needs to match source state when a transition is configured for this choice. You can configure a transition by using `withChoice()`, where you define source state and a `first/then/last` structure, which is equivalent to a normal`if/elseif/else`. With `first` and `then`, you can specify a guard just as you would use a condition with `if/elseif` clauses. A transition needs to be able to exist, so you must make sure to use `last`. Otherwise, the configuration is ill-formed. The following example shows how to define a choice state: ``` @Configuration @EnableStateMachine public class Config13 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.SI) .choice(States.S1) .end(States.SF) .states(EnumSet.allOf(States.class)); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withChoice() .source(States.S1) .first(States.S2, s2Guard()) .then(States.S3, s3Guard()) .last(States.S4); } @Bean public Guard s2Guard() { return new Guard() { @Override public boolean evaluate(StateContext context) { return false; } }; } @Bean public Guard s3Guard() { return new Guard() { @Override public boolean evaluate(StateContext context) { return true; } }; } } ``` Actions can be run with both incoming and outgoing transitions of a choice pseudostate. As the following example shows, one dummy lambda action is defined that leads into a choice state and one similar dummy lambda action is defined for one outgoing transition (where it also defines an error action): ``` @Configuration @EnableStateMachine public class Config23 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.SI) .choice(States.S1) .end(States.SF) .states(EnumSet.allOf(States.class)); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.SI) .action(c -> { // action with SI-S1 }) .target(States.S1) .and() .withChoice() .source(States.S1) .first(States.S2, c -> { return true; }) .last(States.S3, c -> { // action with S1-S3 }, c -> { // error callback for action S1-S3 }); } } ``` | |Junction have same api format meaning actions can be defined
similarly.| |---|---------------------------------------------------------------------------| #### Junction State You need to define a junction in both states and transitions for it to work properly. You can mark a particular state as being a choice state by using the `junction()`method. This state needs to match the source state when a transition is configured for this choice. You can configure the transition by using `withJunction()` where you define source state and a `first/then/last` structure (which is equivalent to a normal`if/elseif/else`). With `first` and `then`, you can specify a guard as you would use a condition with `if/elseif` clauses. A transition needs to be able to exist, so you must make sure to use `last`. Otherwise, the configuration is ill-formed. The following example uses a junction: ``` @Configuration @EnableStateMachine public class Config20 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.SI) .junction(States.S1) .end(States.SF) .states(EnumSet.allOf(States.class)); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withJunction() .source(States.S1) .first(States.S2, s2Guard()) .then(States.S3, s3Guard()) .last(States.S4); } @Bean public Guard s2Guard() { return new Guard() { @Override public boolean evaluate(StateContext context) { return false; } }; } @Bean public Guard s3Guard() { return new Guard() { @Override public boolean evaluate(StateContext context) { return true; } }; } } ``` | |The difference between choice and junction is purely academic, as both are
implemented with `first/then/last` structures . However, in theory, based
on UML modeling, `choice` allows only one incoming transition while`junction` allows multiple incoming transitions. At a code level, the
functionality is pretty much identical.| |---|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| #### Fork State You must define a fork in both states and transitions for it to work properly. You can mark a particular state as being a choice state by using the `fork()`method. This state needs to match source state when a transition is configured for this fork. The target state needs to be a super state or an immediate state in a regions. Using a super state as a target takes all regions into initial states. Targeting individual state gives more controlled entry into regions. The following example uses a fork: ``` @Configuration @EnableStateMachine public class Config14 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States2.S1) .fork(States2.S2) .state(States2.S3) .and() .withStates() .parent(States2.S3) .initial(States2.S2I) .state(States2.S21) .state(States2.S22) .end(States2.S2F) .and() .withStates() .parent(States2.S3) .initial(States2.S3I) .state(States2.S31) .state(States2.S32) .end(States2.S3F); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withFork() .source(States2.S2) .target(States2.S22) .target(States2.S32); } } ``` #### Join State You must define a join in both states and transitions for it to work properly. You can mark aparticular state as being a choice state by using the `join()`method. This state does not need to match either source states or a target state in a transition configuration. You can select a target state where a transition goes when all source states have been joined. If you use state hosting regions as the source, the end states of a region are used as joins. Otherwise, you can pick any states from a region. The following exmaple uses a join: ``` @Configuration @EnableStateMachine public class Config15 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States2.S1) .state(States2.S3) .join(States2.S4) .state(States2.S5) .and() .withStates() .parent(States2.S3) .initial(States2.S2I) .state(States2.S21) .state(States2.S22) .end(States2.S2F) .and() .withStates() .parent(States2.S3) .initial(States2.S3I) .state(States2.S31) .state(States2.S32) .end(States2.S3F); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withJoin() .source(States2.S2F) .source(States2.S3F) .target(States2.S4) .and() .withExternal() .source(States2.S4) .target(States2.S5); } } ``` You can also have multiple transitions originate from a join state. It this case, we advise you to use guards and define your guards such that only one guard evaluates to `TRUE` at any given time. Otherwise, transition behavior is not predictable. This is shown in the following example, where the guard checks whether the extended state has variables: ``` @Configuration @EnableStateMachine public class Config22 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States2.S1) .state(States2.S3) .join(States2.S4) .state(States2.S5) .end(States2.SF) .and() .withStates() .parent(States2.S3) .initial(States2.S2I) .state(States2.S21) .state(States2.S22) .end(States2.S2F) .and() .withStates() .parent(States2.S3) .initial(States2.S3I) .state(States2.S31) .state(States2.S32) .end(States2.S3F); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withJoin() .source(States2.S2F) .source(States2.S3F) .target(States2.S4) .and() .withExternal() .source(States2.S4) .target(States2.S5) .guardExpression("!extendedState.variables.isEmpty()") .and() .withExternal() .source(States2.S4) .target(States2.SF) .guardExpression("extendedState.variables.isEmpty()"); } } ``` #### Exit and Entry Point States You can use exit and entry points to do more controlled exit and entry from and into a submachine. The following example uses the `withEntry` and `withExit` methods to define entry points: ``` @Configuration @EnableStateMachine static class Config21 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S1") .state("S2") .state("S3") .and() .withStates() .parent("S2") .initial("S21") .entry("S2ENTRY") .exit("S2EXIT") .state("S22"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S1").target("S2") .event("E1") .and() .withExternal() .source("S1").target("S2ENTRY") .event("ENTRY") .and() .withExternal() .source("S22").target("S2EXIT") .event("EXIT") .and() .withEntry() .source("S2ENTRY").target("S22") .and() .withExit() .source("S2EXIT").target("S3"); } } ``` As shown in the preceding, you need to mark particular states as being `exit` and`entry` states. Then you create a normal transitions into those states and also specify `withExit()` and `withEntry()`, where those states exit and entry respectively. ### Configuring Common Settings You can set part of a common state machine configuration by using`ConfigurationConfigurer`. With it you can set `BeanFactory` and an autostart flag for a state machine. It also lets you register `StateMachineListener` instances, configure transition conflict policy and region execution policy. The following example shows how to use `ConfigurationConfigurer`: ``` @Configuration @EnableStateMachine public class Config17 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withConfiguration() .autoStartup(true) .machineId("myMachineId") .beanFactory(new StaticListableBeanFactory()) .listener(new StateMachineListenerAdapter()) .transitionConflictPolicy(TransitionConflictPolicy.CHILD) .regionExecutionPolicy(RegionExecutionPolicy.PARALLEL); } } ``` By default, the state machine `autoStartup` flag is disabled, because all instances that handle sub-states are controlled by the state machine itself and cannot be automatically started. Also, it is much safer to leave whether a machine should be started automatically or not to the user. This flag controls only the autostart of a top-level state machine. Setting `machineId` within a configuration class is simply a convenience for those times when you want or need to do it there. Registering `StateMachineListener` instances is also partly for convenience but is required if you want to catch a callback during a state machine lifecycle, such as getting notified of a state machine’s start and stop events. Note that you cannot listen a state machine’s start events if `autoStartup` is enabled, unless you register a listener during a configuration phase. You can use `transitionConflictPolicy` when multiple transition paths could be selected. One usual use case for this is when a machine contains anonymous transitions that lead out from a sub-state and a parent state and you want to define a policy in which one is selected. This is a global setting within a machine instance and defaults to `CHILD`. You can use `withDistributed()` to configure `DistributedStateMachine`. It lets you set a `StateMachineEnsemble`, which (if it exists) automatically wraps any created `StateMachine` with `DistributedStateMachine` and enables distributed mode. The following example shows how to use it: ``` @Configuration @EnableStateMachine public class Config18 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withDistributed() .ensemble(stateMachineEnsemble()); } @Bean public StateMachineEnsemble stateMachineEnsemble() throws Exception { // naturally not null but should return ensemble instance return null; } } ``` For more about distributed states, see [Using Distributed States](#sm-distributed). The `StateMachineModelVerifier` interface is used internally to do some sanity checks for a state machine’s structure. Its purpose is to fail fast early instead of letting common configuration errors into a state machine. By default, a verifier is automatically enabled and the`DefaultStateMachineModelVerifier` implementation is used. With `withVerifier()`, you can disable verifier or set a custom one if needed. The following example shows how to do so: ``` @Configuration @EnableStateMachine public class Config19 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withVerifier() .enabled(true) .verifier(verifier()); } @Bean public StateMachineModelVerifier verifier() { return new StateMachineModelVerifier() { @Override public void verify(StateMachineModel model) { // throw exception indicating malformed model } }; } } ``` For more about config model, see [StateMachine Config Model](#devdocs-configmodel). | |The `withSecurity`, `withMonitoring` and `withPersistence` configuration methods
are documented in [State Machine Security](#sm-security), [Monitoring a State Machine](#sm-monitoring), and[Using `StateMachineRuntimePersister`](#sm-persist-statemachineruntimepersister), respectively.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ### Configuring Model `StateMachineModelFactory` is a hook that lets you configure a statemachine model without using a manual configuration. Essentially, it is a third-party integration to integrate into a configuration model. You can hook `StateMachineModelFactory` into a configuration model by using a `StateMachineModelConfigurer`. The following example shows how to do so: ``` @Configuration @EnableStateMachine public static class Config1 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineModelConfigurer model) throws Exception { model .withModel() .factory(modelFactory()); } @Bean public StateMachineModelFactory modelFactory() { return new CustomStateMachineModelFactory(); } } ``` The follwoing example uses `CustomStateMachineModelFactory` to define two states (`S1` and `S2`) and an event (`E1`) between those states: ``` public static class CustomStateMachineModelFactory implements StateMachineModelFactory { @Override public StateMachineModel build() { ConfigurationData configurationData = new ConfigurationData<>(); Collection> stateData = new ArrayList<>(); stateData.add(new StateData("S1", true)); stateData.add(new StateData("S2")); StatesData statesData = new StatesData<>(stateData); Collection> transitionData = new ArrayList<>(); transitionData.add(new TransitionData("S1", "S2", "E1")); TransitionsData transitionsData = new TransitionsData<>(transitionData); StateMachineModel stateMachineModel = new DefaultStateMachineModel(configurationData, statesData, transitionsData); return stateMachineModel; } @Override public StateMachineModel build(String machineId) { return build(); } } ``` | |Defining a custom model is usually not what people are looking for,
although it is possible. However, it is a central concept of allowing
external access to this configuration model.| |---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| You can find an example of using this model factory integration in[Eclipse Modeling Support](#sm-papyrus). You can find more generic info about custom model integration in [Developer Documentation](#devdocs). ### Things to Remember When defining actions, guards, or any other references from a configuration, it pays to remember how Spring Framework works with beans. In the next example, we have defined a normal configuration with states `S1` and `S2` and four transitions between those. All transitions are guarded by either `guard1` or `guard2`. You must ensure that`guard1` is created as a real bean because it is annotated with`@Bean`, while `guard2` is not. This means that event `E3` would get the `guard2` condition as`TRUE`, and `E4` would get the `guard2` condition as `FALSE`, because those are coming from plain method calls to those functions. However, because `guard1` is defined as a `@Bean`, it is proxied by the Spring Framework. Thus, additional calls to its method result in only one instantiation of that instance. Event `E1` would first get the proxied instance with condition `TRUE`, while event `E2` would get the same instance with `TRUE` condition when the method call was defined with`FALSE`. This is not a Spring State Machine-specific behavior. Rather, it is how Spring Framework works with beans. The following example shows how this arrangement works: ``` @Configuration @EnableStateMachine public class Config1 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S1") .state("S2"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S1").target("S2").event("E1").guard(guard1(true)) .and() .withExternal() .source("S1").target("S2").event("E2").guard(guard1(false)) .and() .withExternal() .source("S1").target("S2").event("E3").guard(guard2(true)) .and() .withExternal() .source("S1").target("S2").event("E4").guard(guard2(false)); } @Bean public Guard guard1(final boolean value) { return new Guard() { @Override public boolean evaluate(StateContext context) { return value; } }; } public Guard guard2(final boolean value) { return new Guard() { @Override public boolean evaluate(StateContext context) { return value; } }; } } ``` ## State Machine ID Various classes and interfaces use `machineId` either as a variable or as a parameter in methods. This section takes a closer look at how`machineId` relates to normal machine operation and instantiation. During runtime, a `machineId` really does not have any big operational role except to distinguish machines from each other — for example, when following logs or doing deeper debugging. Having a lot of different machine instances quickly gets developers lost in translation if there is no easy way to identify these instances. As a result, we added the option to set the`machineId`. ### Using `@EnableStateMachine` Setting `machineId` in Java configuration as `mymachine` then exposes that value for logs. This same `machineId` is also available from the`StateMachine.getId()` method. The following example uses the `machineId` method: ``` @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withConfiguration() .machineId("mymachine"); } ``` The following example of log output shows the `mymachine` ID: ``` 11:23:54,509 INFO main support.LifecycleObjectSupport [main] - started S2 S1 / S1 / uuid=8fe53d34-8c85-49fd-a6ba-773da15fcaf1 / id=mymachine ``` | |The manual builder (see [State Machine through a Builder](#state-machine-via-builder)) uses the same configuration
interface, meaning that the behavior is equivalent.| |---|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ### Using `@EnableStateMachineFactory` You can see the same `machineId` getting configured if you use a`StateMachineFactory` and request a new machine by using that ID, as the following example shows: ``` StateMachineFactory factory = context.getBean(StateMachineFactory.class); StateMachine machine = factory.getStateMachine("mymachine"); ``` ### Using `StateMachineModelFactory` Behind the scenes, all machine configurations are first translated into a`StateMachineModel` so that `StateMachineFactory` need not know from where the configuration originated, as a machine can be built from Java configuration, UML, or a repository. If you want to go crazy, you can also use a custom`StateMachineModel`, which is the lowest possible level at which to define configuration. What do all of these have to do with a `machineId`?`StateMachineModelFactory` also has a method with the following signature:`StateMachineModel build(String machineId)` which a `StateMachineModelFactory`implementation may choose to use. `RepositoryStateMachineModelFactory` (see [Repository Support](#sm-repository)) uses`machineId` to support different configurations in a persistent store through Spring Data Repository interfaces. For example, both`StateRepository` and `TransitionRepository` have a method (`List findByMachineId(String machineId)`), to build different states and transitions by a `machineId`. With`RepositoryStateMachineModelFactory`, if `machineId` is used as empty or NULL, it defaults to repository configuration (in a backing-persistent model) without a known machine id. | |Currently, `UmlStateMachineModelFactory` does not distinguish between
different machine IDs, as UML source is always coming from the same
file. This may change in future releases.| |---|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ## State Machine Factories There are use cases when a state machine needs to be created dynamically instead of by defining static configuration at compile time. For example, if there are custom components that use their own state machines and these components are created dynamically, it is impossible to have a static state machine that is built during the application start. Internally, state machines are always built through factory interfaces. This then gives you an option to use this feature programmatically. Configuration for a state machine factory is exactly the same as shown in various examples in this document where state machine configuration is hard coded. ### Factory through an Adapter Actually creating a state machine by using `@EnableStateMachine`works through a factory, so `@EnableStateMachineFactory` merely exposes that factory through its interface. The following example uses`@EnableStateMachineFactory`: ``` @Configuration @EnableStateMachineFactory public class Config6 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.S1) .end(States.SF) .states(EnumSet.allOf(States.class)); } } ``` Now that you have used `@EnableStateMachineFactory` to create a factory instead of a state machine bean, you can inject it and use it (as is) to request new state machines. The following example shows how to do so: ``` public class Bean3 { @Autowired StateMachineFactory factory; void method() { StateMachine stateMachine = factory.getStateMachine(); stateMachine.startReactively().subscribe(); } } ``` #### Adapter Factory Limitations The current limitation of factory is that all the actions and guard with which it associates a state machine share the same instance. This means that, from your actions and guard, you need to specifically handle the case in which the same bean is called by different state machines. This limitation is something that will be resolved in future releases. ### State Machine through a Builder Using adapters (as shown above) has a limitation imposed by its requirement to work through Spring `@Configuration` classes and the application context. While this is a very clear model to configure a state machine, it limits configuration at compile time, which is not always what a user wants to do. If there is a requirement to build more dynamic state machines, you can use a simple builder pattern to construct similar instances. By using strings as states and events, you can use this builder pattern to build fully dynamic state machines outside of a Spring application context. The following example shows how to do so: ``` StateMachine buildMachine1() throws Exception { Builder builder = StateMachineBuilder.builder(); builder.configureStates() .withStates() .initial("S1") .end("SF") .states(new HashSet(Arrays.asList("S1","S2","S3","S4"))); return builder.build(); } ``` The builder uses the same configuration interfaces behind the scenes that the `@Configuration` model uses for adapter classes. The same model goes to configuring transitions, states, and common configuration through a builder’s methods. This means that whatever you can use with a normal`EnumStateMachineConfigurerAdapter` or `StateMachineConfigurerAdapter`you can use dynamically through a builder. | |Currently, the `builder.configureStates()`, `builder.configureTransitions()`,
and `builder.configureConfiguration()` interface methods cannot be
chained together, meaning that builder methods need to be called individually.| |---|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| The following example sets a number of options with a builder: ``` StateMachine buildMachine2() throws Exception { Builder builder = StateMachineBuilder.builder(); builder.configureConfiguration() .withConfiguration() .autoStartup(false) .beanFactory(null) .listener(null); return builder.build(); } ``` You need to understand when common configuration needs to be used with machines instantiated from a builder. You can use a configurer returned from a `withConfiguration()` to setup `autoStart` and `BeanFactory`. You can also use one to register a `StateMachineListener`. If a `StateMachine`instance returned from a builder is registered as a bean by using `@Bean`, `BeanFactory`is attached automatically. If you use instances outside of a spring application context, you must use these methods to set up the needed facilities. ## Using Deferred Events When an event is sent, it may fire an `EventTrigger`, which may then cause a transition to happen, if a state machine is in a state where a trigger is evaluated successfully. Normally, this may lead to a situation where an event is not accepted and is dropped. However, you may wish postpone this event until a state machine enters another state. In that case, you can accept that event. In other words, an event arrives at an inconvenient time. Spring Statemachine provides a mechanism for deferring events for later processing. Every state can have a list of deferred events. If an event in the current state’s deferred event list occurs, the event is saved (deferred) for future processing until a state is entered that does not list the event in its deferred event list. When such a state is entered, the state machine automatically recalls any saved events that are no longer deferred and then either consumes or discards these events. It is possible for a superstate to have a transition defined on an event that is deferred by a substate. Following same hierarchical state machines concepts, the substate takes precedence over the superstate, the event is deferred, and the transition for the superstate is not run. With orthogonal regions, where one orthogonal region defers an event and another accepts the event, the accept takes precedence and the event is consumed and not deferred. The most obvious use case for event deferring is when an event causes a transition into a particular state and the state machine is then returned back to its original state where a second event should cause the same transition. The following example shows this situation: ``` @Configuration @EnableStateMachine static class Config5 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("READY") .state("DEPLOYPREPARE", "DEPLOY") .state("DEPLOYEXECUTE", "DEPLOY"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("READY").target("DEPLOYPREPARE") .event("DEPLOY") .and() .withExternal() .source("DEPLOYPREPARE").target("DEPLOYEXECUTE") .and() .withExternal() .source("DEPLOYEXECUTE").target("READY"); } } ``` In the preceding example, the state machine has a state of `READY`, which indicates that the machine is ready to process events that would take it into a `DEPLOY` state, where the actual deployment would happen. After a deploy action has been run, the machine is returned back to the `READY` state. Sending multiple events in a`READY` state does not cause any trouble if the machine is using synchronous executors, because event sending would block between event calls. However, if the executor uses threads, other events may get lost, because the machine is no longer in a state where events can be processed. Thus, deferring some of these events lets the machine preserve them. The following example shows how to configure such an arrangement: ``` @Configuration @EnableStateMachine static class Config6 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("READY") .state("DEPLOY", "DEPLOY") .state("DONE") .and() .withStates() .parent("DEPLOY") .initial("DEPLOYPREPARE") .state("DEPLOYPREPARE", "DONE") .state("DEPLOYEXECUTE"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("READY").target("DEPLOY") .event("DEPLOY") .and() .withExternal() .source("DEPLOYPREPARE").target("DEPLOYEXECUTE") .and() .withExternal() .source("DEPLOYEXECUTE").target("READY") .and() .withExternal() .source("READY").target("DONE") .event("DONE") .and() .withExternal() .source("DEPLOY").target("DONE") .event("DONE"); } } ``` In the preceding example, the state machine uses nested states instead of a flat state model, so the `DEPLOY` event can be deferred directly in a substate. It also shows the concept of deferring the `DONE` event in a sub-state that would then override the anonymous transition between the `DEPLOY` and `DONE` states if the state machine happens to be in a`DEPLOYPREPARE` state when the `DONE` event is dispatched. In the`DEPLOYEXECUTE` state when the `DONE` event is not deferred, this event would be handled in a super state. ## Using Scopes Support for scopes in a state machine is very limited, but you can enable `session` scope by using a normal Spring `@Scope` annotation in one of two ways: * If the state machine is built manually by using a builder and returned into the context as a `@Bean`. * Through a configuration adapter. Both of these need `@Scope` to be present, with `scopeName` set to`session` and `proxyMode` set to `ScopedProxyMode.TARGET_CLASS`. The following examples show both use cases: ``` @Configuration public class Config3 { @Bean @Scope(scopeName="session", proxyMode=ScopedProxyMode.TARGET_CLASS) StateMachine stateMachine() throws Exception { Builder builder = StateMachineBuilder.builder(); builder.configureConfiguration() .withConfiguration() .autoStartup(true); builder.configureStates() .withStates() .initial("S1") .state("S2"); builder.configureTransitions() .withExternal() .source("S1") .target("S2") .event("E1"); StateMachine stateMachine = builder.build(); return stateMachine; } } ``` ``` @Configuration @EnableStateMachine @Scope(scopeName="session", proxyMode=ScopedProxyMode.TARGET_CLASS) public static class Config4 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withConfiguration() .autoStartup(true); } @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S1") .state("S2"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S1") .target("S2") .event("E1"); } } ``` TIP:See [Scope](#statemachine-examples-scope) for how to use session scoping. Once you have scoped a state machine into `session`, autowiring it into a `@Controller` gives a new state machine instance per session. Each state machine is then destroyed when `HttpSession` is invalidated. The following example shows how to use a state machine in a controller: ``` @Controller public class StateMachineController { @Autowired StateMachine stateMachine; @RequestMapping(path="/state", method=RequestMethod.POST) public HttpEntity setState(@RequestParam("event") String event) { stateMachine .sendEvent(Mono.just(MessageBuilder .withPayload(event).build())) .subscribe(); return new ResponseEntity(HttpStatus.ACCEPTED); } @RequestMapping(path="/state", method=RequestMethod.GET) @ResponseBody public String getState() { return stateMachine.getState().getId(); } } ``` | |Using state machines in a `session` scopes needs careful planning,
mostly because it is a relatively heavy component.| |---|-------------------------------------------------------------------------------------------------------------------------| | |Spring Statemachine poms have no dependencies to Spring MVC
classes, which you will need to work with session scope. However, if you are
working with a web application, you have already pulled those dependencies
directly from Spring MVC or Spring Boot.| |---|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ## Using Actions Actions are one of the most useful components that you can use to interact and collaborate with a state machine. You can run actions in various places in a state machine and its states lifecycle — for example, entering or exiting states or during transitions. The following example shows how to use actions in a state machine: ``` @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.SI) .state(States.S1, action1(), action2()) .state(States.S2, action1(), action2()) .state(States.S3, action1(), action3()); } ``` In the preceding example, the `action1` and `action2` beans are attached to the `entry` and`exit` states, respectively. The following example defines those actions (and `action3`): ``` @Bean public Action action1() { return new Action() { @Override public void execute(StateContext context) { } }; } @Bean public BaseAction action2() { return new BaseAction(); } @Bean public SpelAction action3() { ExpressionParser parser = new SpelExpressionParser(); return new SpelAction( parser.parseExpression( "stateMachine.sendEvent(T(org.springframework.statemachine.docs.Events).E1)")); } public class BaseAction implements Action { @Override public void execute(StateContext context) { } } public class SpelAction extends SpelExpressionAction { public SpelAction(Expression expression) { super(expression); } } ``` You can directly implement `Action` as an anonymous function or create your own implementation and define the appropriate implementation as a bean. In the preceding example, `action3` uses a SpEL expression to send the `Events.E1` event into a state machine. | |`StateContext` is described in [Using `StateContext`](#sm-statecontext).| |---|------------------------------------------------------------------------| ### SpEL Expressions with Actions You can also use a SpEL expression as a replacement for a full `Action` implementation. ### Reactive Actions Normal `Action` interface is a simple functional method taking `StateContext`and returning *void*. There’s nothing blocking here until you block in a method itself and this is a bit of a problem as framework cannot know what’s exactly happening inside of it. ``` public interface Action { void execute(StateContext context); } ``` To overcome this issue we’ve internally changed `Action` handling to process a plain java’s `Function` taking `StateContext` and returning`Mono`. This way we can call action and fully in a reactive way to execute action only when it’s subscribed and in a non-blocking way to wait completion. ``` public interface ReactiveAction extends Function, Mono> { } ``` | |Internally old `Action` interface is wrapped with a Reactor Mono Runnable as it
shares same return type. We have no control what you do in that method!| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------| ## Using Guards As shown in [Things to Remember](#statemachine-config-thingstoremember), the `guard1` and `guard2` beans are attached to the entry and exit states, respectively. The following example also uses guards on events: ``` @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.SI).target(States.S1) .event(Events.E1) .guard(guard1()) .and() .withExternal() .source(States.S1).target(States.S2) .event(Events.E1) .guard(guard2()) .and() .withExternal() .source(States.S2).target(States.S3) .event(Events.E2) .guardExpression("extendedState.variables.get('myvar')"); } ``` You can directly implement `Guard` as an anonymous function or create your own implementation and define the appropriate implementation as a bean. In the preceding example, `guardExpression` checkS whether the extended state variable named `myvar` evaluates to `TRUE`. The following example implements some sample guards: ``` @Bean public Guard guard1() { return new Guard() { @Override public boolean evaluate(StateContext context) { return true; } }; } @Bean public BaseGuard guard2() { return new BaseGuard(); } public class BaseGuard implements Guard { @Override public boolean evaluate(StateContext context) { return false; } } ``` | |`StateContext` is described in section [Using `StateContext`](#sm-statecontext).| |---|--------------------------------------------------------------------------------| ### SpEL Expressions with Guards You can also use a SpEL expression as a replacement for a full Guard implementation. The only requirement is that the expression needs to return a `Boolean` value to satisfy the `Guard` implementation. This can be demonstrated with a `guardExpression()` function that takes an expression as an argument. ### Reactive Guards Normal `Guard` interface is a simple functional method taking `StateContext`and returning *boolean*. There’s nothing blocking here until you block in a method itself and this is a bit of a problem as framework cannot know what’s exactly happening inside of it. ``` public interface Guard { boolean evaluate(StateContext context); } ``` To overcome this issue we’ve internally changed `Guard` handling to process a plain java’s `Function` taking `StateContext` and returning`Mono`. This way we can call guard and fully in a reactive way to evaluate it only when it’s subscribed and in a non-blocking way to wait completion with a return value. ``` public interface ReactiveGuard extends Function, Mono> { } ``` | |Internally old `Guard` interface is wrapped with a Reactor Mono Function. We have no
control what you do in that method!| |---|----------------------------------------------------------------------------------------------------------------------------| ## Using Extended State Assume that you need to create a state machine that tracks how many times a user is pressing a key on a keyboard and then terminates when keys are pressed 1000 times. A possible but really naive solution would be to create a new state for each 1000 key presses. You might suddenly have an astronomical number of states, which, naturally, is not very practical. This is where extended state variables come to the rescue by not needing to add more states to drive state machine changes. Instead, you can do a simple variable change during a transition. `StateMachine` has a method called `getExtendedState()`. It returns an interface called `ExtendedState`, which gives access to extended state variables. You can access these variables directly through a state machine or through`StateContext` during a callback from actions or transitions. The following example shows how to do so: ``` public Action myVariableAction() { return new Action() { @Override public void execute(StateContext context) { context.getExtendedState() .getVariables().put("mykey", "myvalue"); } }; } ``` If you need to get notified for extended state variable changes, you have two options: either use `StateMachineListener` or listen for `extendedStateChanged(key, value)` callbacks. The following example uses the `extendedStateChanged` method: ``` public class ExtendedStateVariableListener extends StateMachineListenerAdapter { @Override public void extendedStateChanged(Object key, Object value) { // do something with changed variable } } ``` Alternatively, you can implement a Spring Application context listener for`OnExtendedStateChanged`. As mentioned in [Listening to State Machine Events](#sm-listeners), you can also listen all `StateMachineEvent` events. The following example uses `onApplicationEvent` to listen for state changes: ``` public class ExtendedStateVariableEventListener implements ApplicationListener { @Override public void onApplicationEvent(OnExtendedStateChanged event) { // do something with changed variable } } ``` ## Using `StateContext` [`StateContext`](https://docs.spring.io/spring-statemachine/docs/3.0.1/api/org/springframework/statemachine/StateContext.html) is one of the most important objects when working with a state machine, as it is passed into various methods and callbacks to give the current state of a state machine and where it is possibly going. You can think of it as a snapshot of the current state machine stage when is when `StateContext` is retreived. | |In Spring Statemachine 1.0.x, `StateContext` usage was relatively naive
in terms of how it was used to pass stuff around as a simple “POJO”.
Starting from Spring Statemachine 1.1.x, its role has been greatly
improved by making it a first class citizen in a state machine.| |---|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| You can use `StateContext` to get access to the following: * The current `Message` or `Event` (or their `MessageHeaders`, if known). * The state machine’s `Extended State`. * The `StateMachine` itself. * To possible state machine errors. * To the current `Transition`, if applicable. * The source state of the state machine. * The target state of the state machine. * The current `Stage`, as described in [Stages](#sm-statecontext-stage). `StateContext` is passed into various components, such as`Action` and `Guard`. ### Stages [`Stage`](https://docs.spring.io/spring-statemachine/docs/3.0.1/api/org/springframework/statemachine/StateContext.Stage.html) is arepresentation of a `stage` on which a state machine is currently interacting with a user. The currently available stages are `EVENT_NOT_ACCEPTED`, `EXTENDED_STATE_CHANGED`,`STATE_CHANGED`, `STATE_ENTRY`, `STATE_EXIT`, `STATEMACHINE_ERROR`,`STATEMACHINE_START`, `STATEMACHINE_STOP`, `TRANSITION`,`TRANSITION_START`, and `TRANSITION_END`. These states may look familiar, as they match how you can interact with listeners (as described in[Listening to State Machine Events](#sm-listeners)). ## Triggering Transitions Driving a state machine is done by using transitions, which are triggered by triggers. The currently supported triggers are `EventTrigger` and`TimerTrigger`. ### Using `EventTrigger` `EventTrigger` is the most useful trigger, because it lets you directly interact with a state machine by sending events to it. These events are also called signals. You can add a trigger to a transition by associating a state with it during configuration. The following example shows how to do so: ``` @Autowired StateMachine stateMachine; void signalMachine() { stateMachine .sendEvent(Mono.just(MessageBuilder .withPayload("E1").build())) .subscribe(); Message message = MessageBuilder .withPayload("E2") .setHeader("foo", "bar") .build(); stateMachine.sendEvent(Mono.just(message)).subscribe(); } ``` Whether you send one event or multiple events, result is always a sequence of results. This is so because in a presence multiple reqions, results will come back from multiple machines in those regions. This is shown with method `sendEventCollect` which gives a list of results. Method itself is a just a syntactic sugar collecting `Flux` as list. If there is just one region, this list contains one result. ``` Message message1 = MessageBuilder .withPayload("E1") .build(); Mono>> results = stateMachine.sendEventCollect(Mono.just(message1)); results.subscribe(); ``` | |Nothing happens until returned flux is subscribed. See more about it from[StateMachineEventResult](#sm-triggers-statemachineeventresult).| |---|-----------------------------------------------------------------------------------------------------------------------------------------| The preceding example sends an events by constructing a `Mono` wrapping a `Message` and subscribing into returned `Flux` of results. `Message` lets us add arbitrary extra information to an event, which is then visible to `StateContext` when (for example) you implement actions. | |Message headers are generally passed on until machine runs to
completion for a specific event. For example if an event is causing
transition into a state `A` which have an anonymous transition into a
state `B`, original event is available for actions or guards in state`B`.| |---|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| It is also possible to send a `Flux` of messages instead of sending just one with a `Mono`. ``` Message message1 = MessageBuilder .withPayload("E1") .build(); Message message2 = MessageBuilder .withPayload("E2") .build(); Flux> results = stateMachine.sendEvents(Flux.just(message1, message2)); results.subscribe(); ``` #### StateMachineEventResult `StateMachineEventResult` contains more detailed information about a result of a event sending. From this you can get a `Region` which handled an event,`Message` itself and what was an actual `ResultType`. From `ResultType` you can see if message was accepted, denied or deferred. Generally speaking when subscribtion completes, events are passed into a machine. ### Using `TimerTrigger` `TimerTrigger` is useful when something needs to be triggered automatically without any user interaction. `Trigger` is added to a transition by associating a timer with it during a configuration. Currently, there are two types of supported timers, one that fires continuously and one that fires once a source state is entered. The following example shows how to use the triggers: ``` @Configuration @EnableStateMachine public class Config2 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S1") .state("S2") .state("S3"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S1").target("S2").event("E1") .and() .withExternal() .source("S1").target("S3").event("E2") .and() .withInternal() .source("S2") .action(timerAction()) .timer(1000) .and() .withInternal() .source("S3") .action(timerAction()) .timerOnce(1000); } @Bean public TimerAction timerAction() { return new TimerAction(); } } public class TimerAction implements Action { @Override public void execute(StateContext context) { // do something in every 1 sec } } ``` The preceding example has three states: `S1`, `S2`, and `S3`. We have a normal external transition from `S1` to `S2` and from `S1` to `S3` with events `E1` and `E2`, respectively. The interesting parts for working with `TimerTrigger` are when we define internal transitions for source states `S2` and `S3`. For both transitions, we invoke the `Action` bean (`timerAction`), where source state `S2` uses `timer` and `S3` uses `timerOnce`. Values given are in milliseconds (`1000` milliseconds, or one second, in both cases). Once a state machine receives event `E1`, it does a transition from `S1` to `S2` and the timer kicks in. When the state is `S2`,`TimerTrigger` runs and causes a transition associated with that state — in this case, the internal transition that has the`timerAction` defined. Once a state machine receives the `E2`, event it does a transition from `S1` to `S3` and the timer kicks in. This timer is executed only once after the state is entered (after a delay defined in a timer). | |Behind the scenes, timers are simple triggers that may cause a
transition to happen. Defining a transition with a `timer()` keeps
firing triggers and causes transition only if the source state is active.
Transition with `timerOnce()` is a little different, as it
triggers only after a delay when a source state is actually entered.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | |Use `timerOnce()` if you want something to happen after a delay
exactly once when state is entered.| |---|-------------------------------------------------------------------------------------------------------| ## Listening to State Machine Events There are use cases where you want to know what is happening with a state machine, react to something, or get logging details for debugging purposes. Spring Statemachine provides interfaces for adding listeners. These listeners then give an option to get callbacks when various state changes, actions, and so on happen. You basically have two options: listen to Spring application context events or directly attach a listener to a state machine. Both of these basically provide the same information. One produces events as event classes, and the other produces callbacks via a listener interface. Both of these have pros and cons, which we discuss later. ### Application Context Events Application context events classes are `OnTransitionStartEvent`,`OnTransitionEvent`, `OnTransitionEndEvent`, `OnStateExitEvent`,`OnStateEntryEvent`, `OnStateChangedEvent`, `OnStateMachineStart`,`OnStateMachineStop`, and others that extend the base event class,`StateMachineEvent`. These can be used as is with a Spring`ApplicationListener`. `StateMachine` sends context events through `StateMachineEventPublisher`. The default implementation is automatically created if a `@Configuration`class is annotated with `@EnableStateMachine`. The following example gets a `StateMachineApplicationEventListener`from a bean defined in a `@Configuration` class: ``` public class StateMachineApplicationEventListener implements ApplicationListener { @Override public void onApplicationEvent(StateMachineEvent event) { } } @Configuration public class ListenerConfig { @Bean public StateMachineApplicationEventListener contextListener() { return new StateMachineApplicationEventListener(); } } ``` Context events are also automatically enabled by using `@EnableStateMachine`, with `StateMachine` used to build a machine and registered as a bean, as the following example shows: ``` @Configuration @EnableStateMachine public class ManualBuilderConfig { @Bean public StateMachine stateMachine() throws Exception { Builder builder = StateMachineBuilder.builder(); builder.configureStates() .withStates() .initial("S1") .state("S2"); builder.configureTransitions() .withExternal() .source("S1") .target("S2") .event("E1"); return builder.build(); } } ``` ### Using `StateMachineListener` By using `StateMachineListener`, you can either extend it and implement all callback methods or use the `StateMachineListenerAdapter`class, which contains stub method implementations and choose which ones to override. The following example uses the latter approach: ``` public class StateMachineEventListener extends StateMachineListenerAdapter { @Override public void stateChanged(State from, State to) { } @Override public void stateEntered(State state) { } @Override public void stateExited(State state) { } @Override public void transition(Transition transition) { } @Override public void transitionStarted(Transition transition) { } @Override public void transitionEnded(Transition transition) { } @Override public void stateMachineStarted(StateMachine stateMachine) { } @Override public void stateMachineStopped(StateMachine stateMachine) { } @Override public void eventNotAccepted(Message event) { } @Override public void extendedStateChanged(Object key, Object value) { } @Override public void stateMachineError(StateMachine stateMachine, Exception exception) { } @Override public void stateContext(StateContext stateContext) { } } ``` In the preceding example, we created our own listener class (`StateMachineEventListener`) that extends`StateMachineListenerAdapter`. The `stateContext` listener method gives access to various`StateContext` changes on a different stages. You can find more about about it in[Using `StateContext`](#sm-statecontext). Once you have defined your own listener, you can registered it in a state machine by using the `addStateListener` method. It is a matter of flavor whether to hook it up within a spring configuration or do it manually at any time during the application life-cycle. The following example shows how to attach a listener: ``` public class Config7 { @Autowired StateMachine stateMachine; @Bean public StateMachineEventListener stateMachineEventListener() { StateMachineEventListener listener = new StateMachineEventListener(); stateMachine.addStateListener(listener); return listener; } } ``` ### Limitations and Problems Spring application context is not the fastest event bus out there, so we advise giving some thought to the rate of events the state machine sends. For better performance, it may be better to use the`StateMachineListener` interface. For this specific reason, you can use the `contextEvents` flag with `@EnableStateMachine` and`@EnableStateMachineFactory` to disable Spring application context events, as shown in the preceding section. The following example shows how to disable Spring application context events: ``` @Configuration @EnableStateMachine(contextEvents = false) public class Config8 extends EnumStateMachineConfigurerAdapter { } @Configuration @EnableStateMachineFactory(contextEvents = false) public class Config9 extends EnumStateMachineConfigurerAdapter { } ``` ## Context Integration It is a little limited to do interaction with a state machine by either listening to its events or using actions with states and transitions. From time to time, this approach is going be too limited and verbose to create interaction with the application with which a state machine works. For this specific use case, we have made a Spring-style context integration that easily inserts state machine functionality into your beans. The available annotations has been harmonized to enable access to the same state machine execution points that are available from[Listening to State Machine Events](#sm-listeners). You can use the `@WithStateMachine` annotation to associate a state machine with an existing bean. Then you can start adding supported annotations to the methods of that bean. The following example shows how to do so: ``` @WithStateMachine public class Bean1 { @OnTransition public void anyTransition() { } } ``` You can also attach any other state machine from an application context by using the annotation `name` field. The following example shows how to do so: ``` @WithStateMachine(name = "myMachineBeanName") public class Bean2 { @OnTransition public void anyTransition() { } } ``` Sometimes, it is more convenient to use `machine id`, which is something you can set to better identify multiple instances. This ID maps to the `getId()` method in the `StateMachine` interface. The following example shows how to use it: ``` @WithStateMachine(id = "myMachineId") public class Bean16 { @OnTransition public void anyTransition() { } } ``` You can also use `@WithStateMachine` as a meta-annotation, as shown in the preceding example. In this case, you could annotate your bean with `WithMyBean`. The following example shows how to do so: ``` @Target(ElementType.TYPE) @Retention(RetentionPolicy.RUNTIME) @WithStateMachine(name = "myMachineBeanName") public @interface WithMyBean { } ``` | |The return type of these methods does not matter and is effectively
discarded.| |---|----------------------------------------------------------------------------------| ### Enabling Integration You can enable all the features of `@WithStateMachine` by using the `@EnableWithStateMachine` annotation, which imports the needed configuration into the Spring Application Context. Both`@EnableStateMachine` and `@EnableStateMachineFactory` are already annotated with this annotation, so there is no need to add it again. However, if a machine is built and configured without configuration adapters, you must use `@EnableWithStateMachine`to use these features with `@WithStateMachine`. The following example shows how to do so: ``` public static StateMachine buildMachine(BeanFactory beanFactory) throws Exception { Builder builder = StateMachineBuilder.builder(); builder.configureConfiguration() .withConfiguration() .machineId("myMachineId") .beanFactory(beanFactory); builder.configureStates() .withStates() .initial("S1") .state("S2"); builder.configureTransitions() .withExternal() .source("S1") .target("S2") .event("E1"); return builder.build(); } @WithStateMachine(id = "myMachineId") static class Bean17 { @OnStateChanged public void onStateChanged() { } } ``` | |If a machine is not created as a bean, you need to set`BeanFactory` for a machine, as shown in the prededing example. Otherwise, tge machine is
unaware of handlers that call your `@WithStateMachine` methods.| |---|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ### Method Parameters Every annotation support exactly the same set of possible method parameters, but runtime behavior differs, depending on the annotation itself and the stage in which the annotated method is called. To better understand how context works, see[Using `StateContext`](#sm-statecontext). | |For differences between method parameters, see the sections that desdribe the
individual annotation, later in this document.| |---|--------------------------------------------------------------------------------------------------------------------------------| Effectively, all annotated methods are called by using Spring SPel expressions, which are built dynamically during the process. To make this work, these expressions needs to have a root object (against which they evaluate). This root object is a `StateContext`. We have also made some tweaks internally so that it is possible to access `StateContext` methods directly without going through the context handle. The simplest method parameter is a `StateContext` itself. The following example shows how to use it: ``` @WithStateMachine public class Bean3 { @OnTransition public void anyTransition(StateContext stateContext) { } } ``` You can access the rest of the `StateContext` content. The number and order of the parameters does not matter. The following example shows how to access the various parts of the `StateContext` content: ``` @WithStateMachine public class Bean4 { @OnTransition public void anyTransition( @EventHeaders Map headers, @EventHeader("myheader1") Object myheader1, @EventHeader(name = "myheader2", required = false) String myheader2, ExtendedState extendedState, StateMachine stateMachine, Message message, Exception e) { } } ``` | |Instead of getting all event headers with `@EventHeaders`, you can use`@EventHeader`, which can bound to a single header.| |---|-------------------------------------------------------------------------------------------------------------------------| ### Transition Annotations The annotations for transitions are `@OnTransition`, `@OnTransitionStart`, and `@OnTransitionEnd`. These annotations behave exactly the same. To show how they work, we show how `@OnTransition` is used. Within this annotation, a property’s you can use `source` and `target` to qualify a transition. If`source` and `target` are left empty, any transition is matched. The following example shows how to use the `@OnTransition` annotation (remember that `@OnTransitionStart` and `@OnTransitionEnd` work the same way): ``` @WithStateMachine public class Bean5 { @OnTransition(source = "S1", target = "S2") public void fromS1ToS2() { } @OnTransition public void anyTransition() { } } ``` By default, you cannot use the `@OnTransition` annotation with a state and event enumerations that you have created, due to Java language limitations. For this reason, you need to use string representations. Additionally, you can access `Event Headers` and`ExtendedState` by adding the needed arguments to a method. The method is then called automatically with these arguments. The following example shows how to do so: ``` @WithStateMachine public class Bean6 { @StatesOnTransition(source = States.S1, target = States.S2) public void fromS1ToS2(@EventHeaders Map headers, ExtendedState extendedState) { } } ``` However, if you want to have a type-safe annotation, you can create a new annotation and use `@OnTransition` as a meta-annotation. This user-level annotation can make references to actual states and events enumerations, and the framework tries to match these in the same way. The following example shows how to do so: ``` @Target(ElementType.METHOD) @Retention(RetentionPolicy.RUNTIME) @OnTransition public @interface StatesOnTransition { States[] source() default {}; States[] target() default {}; } ``` In the preceding example, we created a `@StatesOnTransition` annotation that defines`source` and `target` in a type-safe manner. The following example uses that annotation in a bean: ``` @WithStateMachine public class Bean7 { @StatesOnTransition(source = States.S1, target = States.S2) public void fromS1ToS2() { } } ``` ### State Annotations The following annotations for states are available: `@OnStateChanged`, `@OnStateEntry`, and`@OnStateExit`. The following example shows how to use `OnStateChanged` annotation (the other two work the same way): ``` @WithStateMachine public class Bean8 { @OnStateChanged public void anyStateChange() { } } ``` As you can with [Transition Annotations](#state-machine-transition-annotations), you can define target and source states. The following example shows how to do so: ``` @WithStateMachine public class Bean9 { @OnStateChanged(source = "S1", target = "S2") public void stateChangeFromS1toS2() { } } ``` For type safety, new annotations need to be created for enumerations by using`@OnStateChanged` as a meta-annotation. The following examples show how to do so: ``` @Target(ElementType.METHOD) @Retention(RetentionPolicy.RUNTIME) @OnStateChanged public @interface StatesOnStates { States[] source() default {}; States[] target() default {}; } ``` ``` @WithStateMachine public class Bean10 { @StatesOnStates(source = States.S1, target = States.S2) public void fromS1ToS2() { } } ``` The methods for state entry and exit behave in the same way, as the following example shows: ``` @WithStateMachine public class Bean11 { @OnStateEntry public void anyStateEntry() { } @OnStateExit public void anyStateExit() { } } ``` ### Event Annotation There is one event-related annotation. It is named `@OnEventNotAccepted`. If you specify the `event` property, you can listen for a specific event not being accepted. If you do not specify an event, you can list for any event not being accepted. The following example shows both ways to use the `@OnEventNotAccepted`annotation: ``` @WithStateMachine public class Bean12 { @OnEventNotAccepted public void anyEventNotAccepted() { } @OnEventNotAccepted(event = "E1") public void e1EventNotAccepted() { } } ``` ### State Machine Annotations The following annotations are available for a state machine: `@OnStateMachineStart`,`@OnStateMachineStop`, and `@OnStateMachineError`. During a state machine’s start and stop, lifecycle methods are called. The following example shows how to use `@OnStateMachineStart` and`@OnStateMachineStop` to listen to these events: ``` @WithStateMachine public class Bean13 { @OnStateMachineStart public void onStateMachineStart() { } @OnStateMachineStop public void onStateMachineStop() { } } ``` If a state machine goes into an error with exception, `@OnStateMachineStop`annotation is called. The following example shows how to use it: ``` @WithStateMachine public class Bean14 { @OnStateMachineError public void onStateMachineError() { } } ``` ### Extended State Annotation There is one extended state-related annotation. It is named`@OnExtendedStateChanged`. You can also listen to changes only for specific `key` changes. The following example shows how to use the`@OnExtendedStateChanged`, both with and without a `key` property: ``` @WithStateMachine public class Bean15 { @OnExtendedStateChanged public void anyStateChange() { } @OnExtendedStateChanged(key = "key1") public void key1Changed() { } } ``` ## Using `StateMachineAccessor` `StateMachine` is the main interface for communicating with a state machine. From time to time, you may need to get more dynamic and programmatic access to internal structures of a state machine and its nested machines and regions. For these use cases, `StateMachine`exposes a functional interface called `StateMachineAccessor`, which provides an interface to get access to individual `StateMachine` and`Region` instances. `StateMachineFunction` is a simple functional interface that lets you apply the `StateMachineAccess` interface to a state machine. With JDK 7, these create code that is a little verbose code. However, with JDK 8 lambdas, the doce is relatively non-verbose. The `doWithAllRegions` method gives access to all `Region` instances in a state machine. The following example shows how to use it: ``` stateMachine.getStateMachineAccessor().doWithAllRegions(function -> function.setRelay(stateMachine)); stateMachine.getStateMachineAccessor() .doWithAllRegions(access -> access.setRelay(stateMachine)); ``` The `doWithRegion` method gives access to single `Region` instance in a state machine. The following example shows how to use it: ``` stateMachine.getStateMachineAccessor().doWithRegion(function -> function.setRelay(stateMachine)); stateMachine.getStateMachineAccessor() .doWithRegion(access -> access.setRelay(stateMachine)); ``` The `withAllRegions` method gives access to all of the `Region` instances in a state machine. The following example shows how to use it: ``` for (StateMachineAccess access : stateMachine.getStateMachineAccessor().withAllRegions()) { access.setRelay(stateMachine); } stateMachine.getStateMachineAccessor().withAllRegions() .stream().forEach(access -> access.setRelay(stateMachine)); ``` The `withRegion` method gives access to single `Region` instance in a state machine. The following example shows how to use it: ``` stateMachine.getStateMachineAccessor() .withRegion().setRelay(stateMachine); ``` ## Using `StateMachineInterceptor` Instead of using a `StateMachineListener` interface, you can use a `StateMachineInterceptor`. One conceptual difference is that you can use an interceptor to intercept and stop a current state change or change its transition logic. Instead of implementing a full interface, you can use an adapter class called `StateMachineInterceptorAdapter` to override the default no-op methods. | |One recipe ([Persist](#statemachine-recipes-persist)) and one sample
([Persist](#statemachine-examples-persist)) are related to using an
interceptor.| |---|-------------------------------------------------------------------------------------------------------------------------------------------------------------| You can register an interceptor through `StateMachineAccessor`. The concept of an interceptor is a relatively deep internal feature and, thus, is not exposed directly through the `StateMachine` interface. The following example shows how to add a `StateMachineInterceptor` and override selected methods: ``` stateMachine.getStateMachineAccessor() .withRegion().addStateMachineInterceptor(new StateMachineInterceptor() { @Override public Message preEvent(Message message, StateMachine stateMachine) { return message; } @Override public StateContext preTransition(StateContext stateContext) { return stateContext; } @Override public void preStateChange(State state, Message message, Transition transition, StateMachine stateMachine, StateMachine rootStateMachine) { } @Override public StateContext postTransition(StateContext stateContext) { return stateContext; } @Override public void postStateChange(State state, Message message, Transition transition, StateMachine stateMachine, StateMachine rootStateMachine) { } @Override public Exception stateMachineError(StateMachine stateMachine, Exception exception) { return exception; } }); ``` | |For more about the error handling shown in preceding example, see[State Machine Error Handling](#sm-error-handling).| |---|--------------------------------------------------------------------------------------------------------------------| ## State Machine Security Security features are built atop of functionality from[Spring Security](https://projects.spring.io/spring-security). Security features are handy when it is required to protect part of a state machine execution and interaction with it. | |We expect you to be fairly familiar with Spring Security, meaning
that we do not go into details of how the overall security framework works. For
this information, you should read the Spring Security reference documentation
(available [here](https://spring.io/projects/spring-security#learn)).| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| The first level of defense with security is naturally protecting events, which really drive what is going to happen in a state machine. You can then define more fine-grained security settings for transitions and actions. This parallel to giving an employee access to a building and then giving access to specific rooms within the building and even the ability to turn on and off the lights in specific rooms. If you trust your users, event security may be all you need. If not, you need to apply more detailed security. You can find more detailed information in [Understanding Security](#sm-security-details). | |For a complete example, see the [Security](#statemachine-examples-security) sample.| |---|-----------------------------------------------------------------------------------| ### Configuring Security All generic configurations for security are done in`SecurityConfigurer`, which is obtained from`StateMachineConfigurationConfigurer`. By default, security is disabled, even if Spring Security classes are present. The following example shows how to enable security: ``` @Configuration @EnableStateMachine static class Config4 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withSecurity() .enabled(true) .transitionAccessDecisionManager(null) .eventAccessDecisionManager(null); } } ``` If you absolutely need to, you can customize `AccessDecisionManager` for both events and transitions. If you do not define decision managers or set them to `null`, default managers are created internally. ### Securing Events Event security is defined on a global level by a `SecurityConfigurer`. The following example shows how to enable event security: ``` @Configuration @EnableStateMachine static class Config1 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withSecurity() .enabled(true) .event("true") .event("ROLE_ANONYMOUS", ComparisonType.ANY); } } ``` In the preceding configuration example, we use an expression of `true`, which always evaluates to `TRUE`. Using an expression that always evaluates to `TRUE`would not make sense in a real application but shows the point that expression needs to return either `TRUE` or `FALSE`. We also defined an attribute of `ROLE_ANONYMOUS` and a `ComparisonType` of `ANY`. For more about using attributes and expressions, see [Using Security Attributes and Expressions](#sm-security-attributes-expressions). ### Securing Transitions You can define transition security globally, as the following example shows. ``` @Configuration @EnableStateMachine static class Config6 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withSecurity() .enabled(true) .transition("true") .transition("ROLE_ANONYMOUS", ComparisonType.ANY); } } ``` If security is defined in a transition itself, it override any globally set security. The following example shows how to do so: ``` @Configuration @EnableStateMachine static class Config2 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S0") .target("S1") .event("A") .secured("ROLE_ANONYMOUS", ComparisonType.ANY) .secured("hasTarget('S1')"); } } ``` For more about using attributes and expressions, see [Using Security Attributes and Expressions](#sm-security-attributes-expressions). ### Securing Actions There are no dedicated security definitions for actions in a state machine, but you can secure actions by using a global method security from Spring Security. This requires that an `Action` be defined as a proxied `@Bean` and its `execute` method be annotated with`@Secured`. The following example shows how to do so: ``` @Configuration @EnableStateMachine static class Config3 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withSecurity() .enabled(true); } @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S0") .state("S1"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S0") .target("S1") .action(securedAction()) .event("A"); } @Scope(proxyMode = ScopedProxyMode.TARGET_CLASS) @Bean public Action securedAction() { return new Action() { @Secured("ROLE_ANONYMOUS") @Override public void execute(StateContext context) { } }; } } ``` Global method security needs to be enabled with Spring Security. The following example shows how to do so: ``` @Configuration @EnableGlobalMethodSecurity(securedEnabled = true) public static class Config5 extends WebSecurityConfigurerAdapter { @Autowired public void configureGlobal(AuthenticationManagerBuilder auth) throws Exception { auth .inMemoryAuthentication() .withUser("user").password("password").roles("USER"); } } ``` See the Spring Security reference guide (available[here](https://spring.io/projects/spring-security#learn)) for more detail. ### Using Security Attributes and Expressions Generally, you can define security properties in either of two ways: by using security attributes and by using security expressions. Attributes are easier to use but are relatively limited in terms of functionality. Expressions provide more features but are a little bit harder to use. #### Generic Attribute Usage By default, `AccessDecisionManager` instances for events and transitions both use a `RoleVoter`, meaning you can use role attributes from Spring Security. For attributes, we have three different comparison types: `ANY`, `ALL`, and`MAJORITY`. These comparison types map onto default access decision managers (`AffirmativeBased`, `UnanimousBased`, and `ConsensusBased`, respectively). If you have defined a custom `AccessDecisionManager`, the comparison type is effectively discarded, as it is used only to create a default manager. #### Generic Expression Usage Security expressions must return either `TRUE` or `FALSE`. The base class for the expression root objects is`SecurityExpressionRoot`. It provides some common expressions, which are available in both transition and event security. The following table describes the most often used built-in expressions: | Expression | Description | |--------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | `hasRole([role])` | Returns `true` if the current principal has the specified role. By
default, if the supplied role does not start with `ROLE_`, it is
added. You can customize this by modifying the `defaultRolePrefix` on`DefaultWebSecurityExpressionHandler`. | | `hasAnyRole([role1,role2])` |Returns `true` if the current principal has any of the supplied
roles (given as a comma-separated list of strings). By default, if each
supplied role does not start with `ROLE_`, it is added. You can customize this
by modifying the `defaultRolePrefix` on`DefaultWebSecurityExpressionHandler`.| | `hasAuthority([authority])` | Returns `true` if the current principal has the specified authority. | | `hasAnyAuthority([authority1,authority2])` | Returns `true` if the current principal has any of the supplied
roles (given as a comma-separated list of strings). | | `principal` | Allows direct access to the principal object that represents the
current user. | | `authentication` | Allows direct access to the current `Authentication` object obtained
from the `SecurityContext`. | | `permitAll` | Always evaluates to `true`. | | `denyAll` | Always evaluates to `false`. | | `isAnonymous()` | Returns `true` if the current principal is an anonymous user. | | `isRememberMe()` | Returns `true` if the current principal is a remember-me user. | | `isAuthenticated()` | Returns `true` if the user is not anonymous. | | `isFullyAuthenticated()` | Returns `true` if the user is not an anonymous or a remember-me user. | | `hasPermission(Object target, Object permission)` | Returns `true` if the user has access to the provided target for the
given permission — for example, `hasPermission(domainObject, 'read')`. | |`hasPermission(Object targetId, String targetType, Object
permission)`| Returns `true` if the user has access to the provided target for the
given permission — for example, `hasPermission(1,
'com.example.domain.Message', 'read')`. | #### Event Attributes You can match an event ID by using a prefix of `EVENT_`. For example, matching event `A` would match an attribute of `EVENT_A`. #### Event Expressions The base class for the expression root object for events is`EventSecurityExpressionRoot`. It provides access to a `Message`object, which is passed around with eventing. `EventSecurityExpressionRoot`has only one method, which the following table describes: | Expression | Description | |------------------------|------------------------------------------------| |`hasEvent(Object event)`|Returns `true` if the event matches given event.| #### Transition Attributes When matching transition sources and targets, you can use the`TRANSITION_SOURCE_` and `TRANSITION_TARGET_` prefixes respectively. #### Transition Expressions The base class for the expression root object for transitions is`TransitionSecurityExpressionRoot`. It provides access to a`Transition`object, which is passed around for transition changes.`TransitionSecurityExpressionRoot` has two methods, which the following table describes: | Expression | Description | |--------------------------|-------------------------------------------------------------| |`hasSource(Object source)`|Returns `true` if the transition source matches given source.| |`hasTarget(Object target)`|Returns `true` if the transition target matches given target.| ### Understanding Security This section provides more detailed information about how security works within a state machine. You may not really need to know, but it is always better to be transparent instead of hiding all the magic what happens behind the scenes. | |Security makes sense only if Spring Statemachine runs in a walled
garden where user have no direct access to the application and could consequently
modify Spring Security’s `SecurityContext` hold in a local thread.
If the user controls the JVM, then effectively there is no security
at all.| |---|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| The integration point for security is created with a[`StateMachineInterceptor`](#sm-interceptor), which is then automatically added into a state machine if security is enabled. The specific class is`StateMachineSecurityInterceptor`, which intercepts events and transitions. This interceptor then consults Spring Security’s`AccessDecisionManager` to determine whether an event can be sent or whether a transition can be executed. Effectively, if a decision or a vote with a `AccessDecisionManager`results in an exception, the event or transition is denied. Due to how `AccessDecisionManager` from Spring Security works, we need one instance of it per secured object. This is one reason why there are different managers for events and transitions. In this case, events and transitions are different class objects that we secure. By default, for events, voters (`EventExpressionVoter`, `EventVoter`, and`RoleVoter`) are added into an `AccessDecisionManager`. By default, for transitions, voters (`TransitionExpressionVoter`,`TransitionVoter`, and `RoleVoter`) are added into an `AccessDecisionManager`. ## State Machine Error Handling If a state machine detects an internal error during a state transition logic, it may throw an exception. Before this exception is processed internally, you are given a chance to intercept. Normally, you can use `StateMachineInterceptor` to intercept errors and the following listing shows an example of it: ``` StateMachine stateMachine; void addInterceptor() { stateMachine.getStateMachineAccessor() .doWithRegion(function -> function.addStateMachineInterceptor(new StateMachineInterceptorAdapter() { @Override public Exception stateMachineError(StateMachine stateMachine, Exception exception) { return exception; } }) ); } ``` When errors are detected, the normal event notify mechanism is executed. This lets you use either a `StateMachineListener` or a Spring Application context event listener. For more about these, see[Listening to State Machine Events](#sm-listeners). Having said that, the following example shows a simple listener: ``` public class ErrorStateMachineListener extends StateMachineListenerAdapter { @Override public void stateMachineError(StateMachine stateMachine, Exception exception) { // do something with error } } ``` The following example shows a generic `ApplicationListener` checking `StateMachineEvent`: ``` public class GenericApplicationEventListener implements ApplicationListener { @Override public void onApplicationEvent(StateMachineEvent event) { if (event instanceof OnStateMachineError) { // do something with error } } } ``` You can also directly define `ApplicationListener` to recognize only `StateMachineEvent` instances, as the following example shows: ``` public class ErrorApplicationEventListener implements ApplicationListener { @Override public void onApplicationEvent(OnStateMachineError event) { // do something with error } } ``` | |Actions defined for transitions also have their own error handling
logic. See [Transition Action Error Handling](#statemachine-config-transition-actions-errorhandling).| |---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------| With a reactive api’s it is possible to get *Action* execution error back from a *StateMachineEventResult*. Having simple machine which errors within action transitioning into state `S1`. ``` @Configuration @EnableStateMachine static class Config1 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("SI") .stateEntry("S1", (context) -> { throw new RuntimeException("example error"); }); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("SI") .target("S1") .event("E1"); } } ``` Below test concept shows how possible error can be consumed from a *StateMachineEventResult*. ``` @Autowired private StateMachine machine; @Test public void testActionEntryErrorWithEvent() throws Exception { StepVerifier.create(machine.startReactively()).verifyComplete(); assertThat(machine.getState().getIds()).containsExactlyInAnyOrder("SI"); StepVerifier.create(machine.sendEvent(Mono.just(MessageBuilder.withPayload("E1").build()))) .consumeNextWith(result -> { StepVerifier.create(result.complete()).consumeErrorWith(e -> { assertThat(e).isInstanceOf(StateMachineException.class).hasMessageContaining("example error"); }).verify(); }) .verifyComplete(); assertThat(machine.getState().getIds()).containsExactlyInAnyOrder("S1"); } ``` | |Error in entry/exit actions will not prevent transition to happen.| |---|------------------------------------------------------------------| ## State Machine Services StateMachine services are higher-level implementations meant to provide more user-level functionalities to ease normal runtime operations. Currently, only one service interface (`StateMachineService`) exists. ### Using `StateMachineService` `StateMachineService` is an interface that is meant to handle running machines and have simple methods to “acquire” and “release” machines. It has one default implementation, named `DefaultStateMachineService`. ## Persisting a State Machine Traditionally, an instance of a state machine is used as is within a running program. You can achieve more dynamic behavior by using dynamic builders and factories, which allows state machine instantiation on-demand. Building an instance of a state machine is a relatively heavy operation. Consequently, if you need to (for example) handle an arbitrary state change in a database by using a state machine, you need to find a better and faster way to do it. The persist feature lets you save a state of a state machine into an external repository and later reset a state machine based off the serialized state. For example, if you have a database table keeping orders, it would be way too expensive to update an order state with a state machine if a new instance would need to be built for every change. The persist feature lets you reset a state machine state without instantiating a new state machine instance. | |There is one recipe (see [Persist](#statemachine-recipes-persist)) and one sample
(see [Persist](#statemachine-examples-persist)) that provide more info about
persisting states.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| While you can build a custom persistence feature by using a`StateMachineListener`, it has one conceptual problem. When a listener notifies about a change of state, the state change has already happened. If a custom persistent method within a listener fails to update the serialized state in an external repository, the state in a state machine and the state in an external repository are then in an inconsistent state. You can instead use a state machine interceptor to try to save the serialized state into external storage during the state change within a state machine. If this interceptor callback fails, you can halt the state change attempt and, instead of ending in an inconsistent state, you can then handle this error manually. See[Using `StateMachineInterceptor`](#sm-interceptor) for how to use interceptors. ### Using `StateMachineContext` You cannot persist a `StateMachine` by using normal java serialization, as the object graph is too rich and contains too many dependencies on other Spring context classes. `StateMachineContext`is a runtime representation of a state machine that you can use to restore an existing machine into a state represented by a particular`StateMachineContext` object. `StateMachineContext` contains two different ways to include information for a child context. These are generally used when a machine contains orthogonal regions. First, a context can have a list of child contexts that can be used as is if they exist. Second, you can include a list of references that are used if raw context children are not in place. These child references are really the only way to persist a machine where multiple parallel regions are running independently. | |The [Data Multi Persist](#statemachine-examples-datajpamultipersist) sample shows
how you can persist parallel regions.| |---|---------------------------------------------------------------------------------------------------------------------------| ### Using `StateMachinePersister` Building a `StateMachineContext` and then restoring a state machine from it has always been a little bit of “black magic” if done manually. The `StateMachinePersister` interface aims to ease these operations by providing `persist` and `restore` methods. The default implementation of this interface is `DefaultStateMachinePersister`. We can show how to use a `StateMachinePersister` by following a snippets from tests. We start by creating two similar configurations (`machine1` and `machine2`) for a state machine. Note that we could build different machines for this demonstration in other ways but this way works for this case. The following example configures the two state machines: ``` @Configuration @EnableStateMachine(name = "machine1") static class Config1 extends Config { } @Configuration @EnableStateMachine(name = "machine2") static class Config2 extends Config { } static class Config extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S1") .state("S1") .state("S2"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S1") .target("S2") .event("E1"); } } ``` As we are using a `StateMachinePersist` object, we can create an in-memory implementation. | |This in-memory sample is only for demonstration purposes. For real
applications, you should use a real persistent storage implementation.| |---|---------------------------------------------------------------------------------------------------------------------------------------------| The following listing shows how to use the in-memory sample: ``` static class InMemoryStateMachinePersist implements StateMachinePersist { private final HashMap> contexts = new HashMap<>(); @Override public void write(StateMachineContext context, String contextObj) throws Exception { contexts.put(contextObj, context); } @Override public StateMachineContext read(String contextObj) throws Exception { return contexts.get(contextObj); } } ``` After we have instantiated the two different machines, we can transfer`machine1` into state `S2` through event `E1`. Then we can persist it and restore`machine2`. The following example shows how to do so: ``` InMemoryStateMachinePersist stateMachinePersist = new InMemoryStateMachinePersist(); StateMachinePersister persister = new DefaultStateMachinePersister<>(stateMachinePersist); StateMachine stateMachine1 = context.getBean("machine1", StateMachine.class); StateMachine stateMachine2 = context.getBean("machine2", StateMachine.class); stateMachine1.startReactively().block(); stateMachine1 .sendEvent(Mono.just(MessageBuilder .withPayload("E1").build())) .blockLast(); assertThat(stateMachine1.getState().getIds()).containsExactly("S2"); persister.persist(stateMachine1, "myid"); persister.restore(stateMachine2, "myid"); assertThat(stateMachine2.getState().getIds()).containsExactly("S2"); ``` ### Using Redis `RepositoryStateMachinePersist` (which implements`StateMachinePersist`) offers support for persisting a state machine into Redis. The specific implementation is a`RedisStateMachineContextRepository`, which uses `kryo` serialization to persist a `StateMachineContext` into `Redis`. For `StateMachinePersister`, we have a Redis-related`RedisStateMachinePersister` implementation, which takes an instance of a `StateMachinePersist` and uses `String` as its context object. | |See the [Event Service](#statemachine-examples-eventservice) sample for detailed usage.| |---|---------------------------------------------------------------------------------------| `RedisStateMachineContextRepository` needs a`RedisConnectionFactory` for it to work. We recommend using a`JedisConnectionFactory` for it, as the preceding example shows. ### Using `StateMachineRuntimePersister` `StateMachineRuntimePersister` is a simple extension to`StateMachinePersist` that adds an interface-level method to get`StateMachineInterceptor` associated with it. This interceptor is then required to persist a machine during state changes without needing to stop and start a machine. Currently, there are implementations for this interface for the supported Spring Data Repositories. These implementations are`JpaPersistingStateMachineInterceptor`, `MongoDbPersistingStateMachineInterceptor`, and `RedisPersistingStateMachineInterceptor`. | |See the [Data Persist](#statemachine-examples-datapersist) sample for detailed usage.| |---|-------------------------------------------------------------------------------------| ## Spring Boot Support The auto-configuration module (`spring-statemachine-autoconfigure`) contains all the logic for integrating with Spring Boot, which provides functionality for auto-configuration and actuators. All you need is to have this Spring Statemachine library as part of a boot application. ### Monitoring and Tracing `BootStateMachineMonitor` is created automatically and associated with a state machine. `BootStateMachineMonitor` is a custom `StateMachineMonitor`implementation that integrates with Spring Boot’s `MeterRegistry` and endpoints through a custom `StateMachineTraceRepository`. Optionally, you can disable this auto-configuration by setting the `spring.statemachine.monitor.enabled` key to`false`. The[Monitoring](#statemachine-examples-monitoring) sample shows how to use this auto-configuration. ### Repository Config If the required classes are found from the classpath, Spring Data Repositories and entity class scanning is automatically auto-configured for [Repository Support](#sm-repository). The currently supported configurations are `JPA`, `Redis`, and`MongoDB`. You can disable repository auto-configuration by using the`spring.statemachine.data.jpa.repositories.enabled`,`spring.statemachine.data.redis.repositories.enabled` and`spring.statemachine.data.mongo.repositories.enabled` properties, respectively. ## Monitoring a State Machine You can use `StateMachineMonitor` to get more information about the durations of how long transitions and actions take to execute. The following listing shows how this interface is implemented. ``` public class TestStateMachineMonitor extends AbstractStateMachineMonitor { @Override public void transition(StateMachine stateMachine, Transition transition, long duration) { } @Override public void action(StateMachine stateMachine, Function, Mono> action, long duration) { } } ``` Once you have a `StateMachineMonitor` implementation, you can add it to a state machine through configuration, as the following example shows: ``` @Configuration @EnableStateMachine public class Config1 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withMonitoring() .monitor(stateMachineMonitor()); } @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S1") .state("S2"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S1") .target("S2") .event("E1"); } @Bean public StateMachineMonitor stateMachineMonitor() { return new TestStateMachineMonitor(); } } ``` | |See the [Monitoring](#statemachine-examples-monitoring) sample for detailed usage.| |---|----------------------------------------------------------------------------------| ## Using Distributed States Distributed state is probably one of a most complicated concepts of a Spring state machine. What exactly is a distributed state? A state within a single state machine is naturally really simple to understand, but, when there is a need to introduce a shared distributed state through a state machine, things get a little complicated. | |Distributed state functionality is still a preview feature and is not
yet considered to be stable in this particular release. We expect this
feature to mature towards its first official release.| |---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| For information about generic configuration support, see[Configuring Common Settings](#statemachine-config-commonsettings). For an actual usage example, see the [Zookeeper](#statemachine-examples-zookeeper) sample. A distributed state machine is implemented through a`DistributedStateMachine` class that wraps an actual instance of a `StateMachine`. `DistributedStateMachine` intercepts communication with a `StateMachine` instance and works with distributed state abstractions handled through the`StateMachineEnsemble` interface. Depending on the actual implementation, you can also use the `StateMachinePersist` interface to serialize a`StateMachineContext`, which contains enough information to reset a`StateMachine`. While a distributed state machine is implemented through an abstraction, only one implementation currently exists. It is based on Zookeeper. The following example shows how to configure a Zookeeper-based distributed state machine`: ``` @Configuration @EnableStateMachine public class Config extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withDistributed() .ensemble(stateMachineEnsemble()) .and() .withConfiguration() .autoStartup(true); } @Override public void configure(StateMachineStateConfigurer states) throws Exception { // config states } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { // config transitions } @Bean public StateMachineEnsemble stateMachineEnsemble() throws Exception { return new ZookeeperStateMachineEnsemble(curatorClient(), "/zkpath"); } @Bean public CuratorFramework curatorClient() throws Exception { CuratorFramework client = CuratorFrameworkFactory .builder() .defaultData(new byte[0]) .connectString("localhost:2181").build(); client.start(); return client; } } ``` You can find the current technical documentation for a Zookeeker-based distributed state machine [in the appendix](#appendices-zookeeper). ### Using `ZookeeperStateMachineEnsemble` `ZookeeperStateMachineEnsemble` itself needs two mandatory settings, an instance of `curatorClient` and a `basePath`. The client is a`CuratorFramework`, and the path is the root of a tree in a `Zookeeper` instance. Optionally, you can set `cleanState`, which defaults to `TRUE`and clears existing data if no members exists in an ensemble. You can set it to `FALSE` if you want to preserve distributed state within application restarts. Optionally, you can set the size of a `logSize` (defaults to `32`) to a keep history of state changes. The value of this setting must be a power of two. `32` is generally a good default value. If a particular state machine is left behind by more than the size of the log, it is put into an error state and disconnected from the ensemble, indicating it has lost its history and its ability to fully reconstruct the synchronized status. ## Testing Support We have also added a set of utility classes to ease testing of state machine instances. These are used in the framework itself but are also very useful for end users. `StateMachineTestPlanBuilder` builds a `StateMachineTestPlan`, which has one method (called `test()`). That method runs a plan.`StateMachineTestPlanBuilder` contains a fluent builder API to let you add steps to a plan. During these steps, you can send events and check various conditions, such as state changes, transitions, and extended state variables. The following example uses `StateMachineBuilder` to build a state machine: ``` private StateMachine buildMachine() throws Exception { StateMachineBuilder.Builder builder = StateMachineBuilder.builder(); builder.configureConfiguration() .withConfiguration() .autoStartup(true); builder.configureStates() .withStates() .initial("SI") .state("S1"); builder.configureTransitions() .withExternal() .source("SI").target("S1") .event("E1") .action(c -> { c.getExtendedState().getVariables().put("key1", "value1"); }); return builder.build(); } ``` In the following test plan, we have two steps. First, we check that the initial state (`SI`) is indeed set. Second, we send an event (`E1`) and expect one state change to happen and expect the machine to end up in a state of `S1`. The following listing shows the test plan: ``` StateMachine machine = buildMachine(); StateMachineTestPlan plan = StateMachineTestPlanBuilder.builder() .defaultAwaitTime(2) .stateMachine(machine) .step() .expectStates("SI") .and() .step() .sendEvent("E1") .expectStateChanged(1) .expectStates("S1") .expectVariable("key1") .expectVariable("key1", "value1") .expectVariableWith(hasKey("key1")) .expectVariableWith(hasValue("value1")) .expectVariableWith(hasEntry("key1", "value1")) .expectVariableWith(not(hasKey("key2"))) .and() .build(); plan.test(); ``` These utilities are also used within a framework to test distributed state machine features. Note that you can add multiple machines to a plan. If you add multiple machines, yuo can also choose to send an event a particular machine, a random machine, or all machines. The preceding testing example uses the following Hamcrest imports: ``` import static org.hamcrest.CoreMatchers.not; import static org.hamcrest.collection.IsMapContaining.hasKey; import static org.hamcrest.collection.IsMapContaining.hasValue; import org.junit.jupiter.api.Test; import static org.hamcrest.collection.IsMapContaining.hasEntry; ``` | |All possible options for expected results are documented in the Javadoc for[`StateMachineTestPlanStepBuilder`](https://docs.spring.io/spring-statemachine/docs/3.0.1/api/org/springframework/statemachine/test/StateMachineTestPlanBuilder.StateMachineTestPlanStepBuilder.html).| |---|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ## Eclipse Modeling Support Defining a state machine configuration with UI modeling is supported through the Eclipse Papyrus framework. From the Eclipse wizard, you can create a new Papyrus Model with the UML Diagram Language. In this example, it is named `simple-machine`. Then you have an option to choose from various diagram kinds, and you must choose a `StateMachine Diagram`. We want to create a machine that has two states (`S1` and `S2`), where`S1` is the initial state. Then, we need to create event `E1` to do a transition from `S1` to `S2`. In Papyrus, a machine would then look like something the following example: simple machine Behind the scenes, a raw UML file would look like the following example: ``` ``` | |When opening an existing model that has been defined as UML, you have three
files: `.di`, `.notation`, and `.uml`. If a model was not created in your
eclipse’s session, it does not understand how to open an actual state
chart. This is a known issue in the Papyrus plugin, and there is an easy
workaround. In a Papyrus perspective, you can see a model explorer for
your model. Double click Diagram StateMachine Diagram, which
instructs Eclipse to open this specific model in its proper Papyrus
modeling plugin.| |---|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ### Using `UmlStateMachineModelFactory` After a UML file is in place in your project, you can import it into your configuration by using `StateMachineModelConfigurer`, where`StateMachineModelFactory` is associated with a model.`UmlStateMachineModelFactory` is a special factory that knows how to process a Eclipse Papyrus\_generated UML structure. The source UML file can either be given as a Spring `Resource` or as a normal location string. The following example shows how to create an instance of`UmlStateMachineModelFactory`: ``` @Configuration @EnableStateMachine public static class Config1 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineModelConfigurer model) throws Exception { model .withModel() .factory(modelFactory()); } @Bean public StateMachineModelFactory modelFactory() { return new UmlStateMachineModelFactory("classpath:org/springframework/statemachine/uml/docs/simple-machine.uml"); } } ``` As usual, Spring Statemachine works with guards and actions, which are defined as beans. Those need to be hooked into UML by its internal modeling structure. The following sections show how customized bean references are defined within UML definitions. Note that it is also possible to register particular methods manually without defining those as beans. If `UmlStateMachineModelFactory` is created as a bean, its`ResourceLoader` is automatically wired to find registered actions and guards. You can also manually define a`StateMachineComponentResolver`, which is then used to find these components. The factory also has *registerAction* and*registerGuard* methods, which you can use to register these components. For more about this, see [Using `StateMachineComponentResolver`](#sm-papyrus-statemachinecomponentresolver). A UML model is relatively loose when it comes to an implementation such as Spring Statemachine itself. Spring Statemachine leaves how to implement a lot of features and functionalities up to the actual implementation. The following sections go through how Spring Statemachine implements UML models based on the Eclipse Papyrus plugin. #### Using `StateMachineComponentResolver` The next example shows how `UmlStateMachineModelFactory` is defined with a `StateMachineComponentResolver`, which registers the`myAction` and `myGuard` functions, respectively. Note that these components are not created as beans. The following listing shows the example: ``` @Configuration @EnableStateMachine public static class Config2 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineModelConfigurer model) throws Exception { model .withModel() .factory(modelFactory()); } @Bean public StateMachineModelFactory modelFactory() { UmlStateMachineModelFactory factory = new UmlStateMachineModelFactory( "classpath:org/springframework/statemachine/uml/docs/simple-machine.uml"); factory.setStateMachineComponentResolver(stateMachineComponentResolver()); return factory; } @Bean public StateMachineComponentResolver stateMachineComponentResolver() { DefaultStateMachineComponentResolver resolver = new DefaultStateMachineComponentResolver<>(); resolver.registerAction("myAction", myAction()); resolver.registerGuard("myGuard", myGuard()); return resolver; } public Action myAction() { return new Action() { @Override public void execute(StateContext context) { } }; } public Guard myGuard() { return new Guard() { @Override public boolean evaluate(StateContext context) { return false; } }; } } ``` ### Creating a Model We start by creating an empty state machine model, shown in the following image: papyrus gs 1 You can start by creating a new model and giving it a name, as the following image shows: papyrus gs 2 Then you need to choose StateMachine Diagram, as follows: ![papyrus gs 3](images/papyrus-gs-3.png) You end up with an empty state machine. In the preceding images, you should have created a sample named `model`. You should have wound up with three files: `model.di`,`model.notation`, and `model.uml`. You can then used these files in any other Eclipse instance. Further, you can import `model.uml` into a Spring Statemachine. ### Defining States The state identifier comes from a component name in a diagram. You must have an initial state in your machine, which you can do by adding a root element and then drawing a transition to your own initial state, as the following image shows: ![papyrus gs 4](images/papyrus-gs-4.png) In the preceding image, we added a root element and an initial state (`S1`). Then we drew a transition between those two to indicate that `S1` is an initial state. ![papyrus gs 5](images/papyrus-gs-5.png) In the preceding image, we added a second state (`S2`) and added a transition between S1 and S2 (indicating that we have two states). ### Defining Events To associate an event with a transition, you need to create a Signal (`E1`, in this case). To do so, choose RootElement → New Child → Signal. The following image shows the result: ![papyrus gs 6](images/papyrus-gs-6.png) Then you need to crate a SignalEvent with the new Signal, `E1`. To do so, choose RootElement → New Child → SignalEvent. The following image shows the result: ![papyrus gs 7](images/papyrus-gs-7.png) Now that you have defined a `SignalEvent`, you can use it to associate a trigger with a transition. For more about that, see[Defining Transitions](#sm-papyrus-transitions). #### Deferring an Event You can defer events to process them at a more appropriate time. In UML, this is done from a state itself. Choose any state, create a new trigger under **Deferrable trigger** and choose the SignalEvent which matches the Signal you want to defer. ### Defining Transitions You can create a transition by drawing a transition line between the source and target states. In the preceding images, we have states `S1` and `S2` and an anonymous transition between the two. We want to associate event`E1` with that transition. We choose a transition, create a new trigger, and define SignalEventE1 for that, as the following image shows: ![papyrus gs 8](images/papyrus-gs-8.png) This gives you something like the arrangement shown in the following image: ![papyrus gs 9](images/papyrus-gs-9.png) | |If you omit SignalEvent for a transition, it becomes an
anonymous transition.| |---|---------------------------------------------------------------------------------| ### Defining Timers Transitions can also happen based on timed events. Spring Statemachine support two types of timers, ones which fires continuously on a background and ones which fires once with a delay when state is entered. To add a new TimeEvent child to Model Explorer, modify When as an expression defined as LiteralInteger. The value of it (in milliseconds) becomes the timer. Leave Is Relative false to make the timer fire continuously. ![papyrus gs 10](images/papyrus-gs-10.png) To define one timed based event that triggers when a state is entered, the process is exactly same as described earlier, but leave Is Relative set to true. The following image shows the result: ![papyrus gs 11](images/papyrus-gs-11.png) Then the user can pick one of these timed events instead of a signal event for a particular transition. ### Defining a Choice A choice is defined by drawing one incoming transition into a CHOICE state and drawing multiple outgoing transitions from it to target states. The configuration model in our `StateConfigurer` lets you define an if/elseif/else structure. However, with UML, we need to work with individual Guards for outgoing transitions. You must ensure that the guards defined for transitions do not overlap so that, whatever happens, only one guard evaluates to TRUE at any given time. This gives precise and predictable results for choice branch evaluation. Also we recommend leaving one transition without a guard so that at least one transition path is guaranteed. The following image shows the result of making a choice with three branches: ![papyrus gs 16](images/papyrus-gs-16.png) | |Junction works similarly same, except that it allows multiple incoming
transitions. Thus, its behavior compared to Choice is purely
academic. The actual logic to select the outgoing transition is exactly the same.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ### Defining a Junction See [Defining a Choice](#sm-papyrus-choice). ### Defining Entry and Exit Points You can use EntryPoint and ExitPoint to create controlled entry and exit with states that have sub-states. In the following state chart, events `E1` and`E2` have normal state behavior by entering and exiting state`S2`, where normal state behavior happens by entering initial state`S21`. Using event `E3` takes the machine into the `ENTRY` EntryPoint, which then leads to `S22` without activating initial state `S21` at any time. Similarly the `EXIT` ExitPoint with event `E4` controls the specific exit into state `S4`, while normal exit behavior from `S2` would take the machine into state `S3`. While on state `S22`, you can choose from events `E4` and `E2` to take the machine into states `S3` or `S4`, respectively. The following image shows the result: ![papyrus gs 17](images/papyrus-gs-17.png) | |If state is defined as a sub-machine reference and you need to use entry and exit points,
you must externally define a ConnectionPointReference, with
its entry and exit reference set to point to a correct entry or exit point
within a submachine reference. Only after that, is it possible to
target a transition that correctly links from the outside to the inside of
a sub-machine reference. With ConnectionPointReference, you may need
to find these settings from Properties → Advanced → UML →
Entry/Exit. The UML specification lets you define multiple entries and exits. However,
with a state machine, only one is allowed.| |---|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ### Defining History States When working with history states, three different concepts are in play. UML defines a Deep History and a Shallow History. The Default History State comes into play when history state is not yet known. These are represented in following sections. #### Shallow History In the following image, Shallow History is selected and a transition is defined into it: ![papyrus gs 18](images/papyrus-gs-18.png) #### Deep History Deep History is used for state that has other deep nested states, thus giving a chance to save whole nested state structure. The following image shows a definition that uses Deep History: ![papyrus gs 19](images/papyrus-gs-19.png) #### Default History In cases where a Transition terminates on a history when the state has not been entered before it had reached its final state, there is an option to force a transition to a specific substate, using the default history mechanism. For this to happen, you must define a transition into this default state. This is the transition from `SH` to`S22`. In the following image, state `S22` is entered if state `S2` has never been active, as its history has never been recorded. If state`S2` has been active, then either `S20` or `S21` gets chosen. ![papyrus gs 20](images/papyrus-gs-20.png) ### Defining Forks and Joins Both Fork and Join are represented as bars in Papyrus. As shown in the next image, you need to draw one outgoing transition from `FORK` into state`S2` to have orthogonal regions. `JOIN` is then the reverse, where joined states are collected together from incoming transitions. ![papyrus gs 21](images/papyrus-gs-21.png) ### Defining Actions You can assoiate swtate entry and exit actions by using a behavior. For more about this, see [Defining a Bean Reference](#sm-papyrus-beanref). #### Using an Initial Action An initial action (as shown in [Configuring Actions](#statemachine-config-actions)) is defined in UML by adding an action in the transition that leads from the Initial State marker into the actual state. This Action is then run when the state machine is started. ### Defining Guards You can define a guard by first adding a Constraint and then defining its Specification as OpaqueExpression, which works in the same way as [Defining a Bean Reference](#sm-papyrus-beanref). ### Defining a Bean Reference When you need to make a bean reference in any UML effect, action, or guard, you can do so with`FunctionBehavior` or `OpaqueBehavior`, where the defined language needs to be `bean` and the language body msut have a bean reference id. ### Defining a SpEL Reference When you need to use a SpEL expression instead of a bean reference in any UML effect, action, or guard, you can do so by using`FunctionBehavior` or `OpaqueBehavior`, where the defined language needs to be `spel` and the language body must be a SpEL expression. ### Using a Sub-Machine Reference Normally, when you use sub-states, you draw those into the state chart itself. The chart may become too complex and big to follow, so we also support defining a sub-state as a state machine reference. To create a sub-machine reference, you must first create a new diagram and give it a name (for example, SubStateMachine Diagram). The following image shows the menu choices to use: ![papyrus gs 12](images/papyrus-gs-12.png) Give the new diagram the design you need. The following image shows a simple design as an example: ![papyrus gs 13](images/papyrus-gs-13.png) From the state you want to link (in this case,m state `S2`), click the`Submachine` field and choose your linked machine (in our example,`SubStateMachine`). ![papyrus gs 14](images/papyrus-gs-14.png) Finally, in the following image, you can see that state `S2` is linked to `SubStateMachine` as a sub-state. ![papyrus gs 15](images/papyrus-gs-15.png) ### Using a Machine Import It’s also possible to use import functionality where uml files can reference to other models. ![papyrus gs 22](images/papyrus-gs-22.png) Within `UmlStateMachineModelFactory` it’s possible to use additional resources or locations to define referenced model files. ``` @Configuration @EnableStateMachine public static class Config3 extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineModelConfigurer model) throws Exception { model .withModel() .factory(modelFactory()); } @Bean public StateMachineModelFactory modelFactory() { return new UmlStateMachineModelFactory( "classpath:org/springframework/statemachine/uml/import-main/import-main.uml", new String[] { "classpath:org/springframework/statemachine/uml/import-sub/import-sub.uml" }); } } ``` | |Links between files in uml models needs to be relative as
otherwise things break when model files are copied out from a
classpath to a temporary directory so that eclipse parsing classes can
read those.| |---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ## Repository Support This section contains documentation related to using 'Spring Data Repositories' in Spring Statemachine. ### Repository Configuration You can keep machine configuration in external storage, from which it can be loaded on demand, instead of creating a static configuration by using either Java configuration or UML-based configuration. This integration works through a Spring Data Repository abstraction. We have created a special `StateMachineModelFactory` implementation called `RepositoryStateMachineModelFactory`. It can use the base repository interfaces (`StateRepository`, `TransitionRepository`,`ActionRepository` and `GuardRepository`) and base entity interfaces (`RepositoryState`, `RepositoryTransition`,`RepositoryAction`, and `RepositoryGuard`). Due to way how entities and repositories work in Spring Data, from a user perspective, read access can be fully abstracted as it is done in `RepositoryStateMachineModelFactory`. There is no need to know the actual mapped entity class with which a repository works. Writing into a repository is always dependent on using a real repository-specific entity class. From a machine-configuration point of view, we do not need to know these, meaning that we do not need to know whether the actual implementation is JPA, Redis, or anything else that Spring Data supports. Using an actual repository-related entity class comes into play when you manually try to write new states or transitions into a backed repository. | |Entity classes for `RepositoryState` and `RepositoryTransition` have a`machineId` field, which is at your disposal and can be used to
differentiate between configurations — for example, if machines are built
via `StateMachineFactory`.| |---|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| Actual implementations are documented in later sections. The following images are UML-equivalent state charts of repository configurations. ![sm repository simplemachine](images/sm-repository-simplemachine.png) Figure 1. SimpleMachine ![sm repository simplesubmachine](images/sm-repository-simplesubmachine.png) Figure 2. SimpleSubMachine ![sm repository showcasemachine](images/sm-repository-showcasemachine.png) Figure 3. ShowcaseMachine #### JPA The actual repository implementations for JPA are`JpaStateRepository`, `JpaTransitionRepository`, `JpaActionRepository`, and `JpaGuardRepository`, which are backed by the entity classes `JpaRepositoryState`, `JpaRepositoryTransition`,`JpaRepositoryAction`, and `JpaRepositoryGuard`, respectively. | |Unfortunately, version '1.2.8' had to make a change in JPA’s entity
model regarding used table names. Previously, generated table names
always had a prefix of `JPA_REPOSITORY_`, derived from entity class
names. As this caused breaking issues with databases imposing
restrictions on database object lengths, all entity classes have
spesific definitions to force table names. For example,`JPA_REPOSITORY_STATE` is now 'STATE' — and so on with other
ntity classes.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| The generic way to update states and transitions manually for JPA is shown in the following example (equivalent to the machine shown in[SimpleMachine](#image-sm-repository-simplemachine)): ``` @Autowired StateRepository stateRepository; @Autowired TransitionRepository transitionRepository; void addConfig() { JpaRepositoryState stateS1 = new JpaRepositoryState("S1", true); JpaRepositoryState stateS2 = new JpaRepositoryState("S2"); JpaRepositoryState stateS3 = new JpaRepositoryState("S3"); stateRepository.save(stateS1); stateRepository.save(stateS2); stateRepository.save(stateS3); JpaRepositoryTransition transitionS1ToS2 = new JpaRepositoryTransition(stateS1, stateS2, "E1"); JpaRepositoryTransition transitionS2ToS3 = new JpaRepositoryTransition(stateS2, stateS3, "E2"); transitionRepository.save(transitionS1ToS2); transitionRepository.save(transitionS2ToS3); } ``` The following example is also equivalent to the machine shown in[SimpleSubMachine](#image-sm-repository-simplesubmachine). ``` @Autowired StateRepository stateRepository; @Autowired TransitionRepository transitionRepository; void addConfig() { JpaRepositoryState stateS1 = new JpaRepositoryState("S1", true); JpaRepositoryState stateS2 = new JpaRepositoryState("S2"); JpaRepositoryState stateS3 = new JpaRepositoryState("S3"); JpaRepositoryState stateS21 = new JpaRepositoryState("S21", true); stateS21.setParentState(stateS2); JpaRepositoryState stateS22 = new JpaRepositoryState("S22"); stateS22.setParentState(stateS2); stateRepository.save(stateS1); stateRepository.save(stateS2); stateRepository.save(stateS3); stateRepository.save(stateS21); stateRepository.save(stateS22); JpaRepositoryTransition transitionS1ToS2 = new JpaRepositoryTransition(stateS1, stateS2, "E1"); JpaRepositoryTransition transitionS2ToS3 = new JpaRepositoryTransition(stateS21, stateS22, "E2"); JpaRepositoryTransition transitionS21ToS22 = new JpaRepositoryTransition(stateS2, stateS3, "E3"); transitionRepository.save(transitionS1ToS2); transitionRepository.save(transitionS2ToS3); transitionRepository.save(transitionS21ToS22); } ``` First, you must access all repositories. The following example shows how to do so: ``` @Autowired StateRepository stateRepository; @Autowired TransitionRepository transitionRepository; @Autowired ActionRepository actionRepository; @Autowired GuardRepository guardRepository; ``` Second, you mus create actions and guards. The following example shows how to do so: ``` JpaRepositoryGuard foo0Guard = new JpaRepositoryGuard(); foo0Guard.setName("foo0Guard"); JpaRepositoryGuard foo1Guard = new JpaRepositoryGuard(); foo1Guard.setName("foo1Guard"); JpaRepositoryAction fooAction = new JpaRepositoryAction(); fooAction.setName("fooAction"); guardRepository.save(foo0Guard); guardRepository.save(foo1Guard); actionRepository.save(fooAction); ``` Third, you must create states. The following example shows how to do so: ``` JpaRepositoryState stateS0 = new JpaRepositoryState("S0", true); stateS0.setInitialAction(fooAction); JpaRepositoryState stateS1 = new JpaRepositoryState("S1", true); stateS1.setParentState(stateS0); JpaRepositoryState stateS11 = new JpaRepositoryState("S11", true); stateS11.setParentState(stateS1); JpaRepositoryState stateS12 = new JpaRepositoryState("S12"); stateS12.setParentState(stateS1); JpaRepositoryState stateS2 = new JpaRepositoryState("S2"); stateS2.setParentState(stateS0); JpaRepositoryState stateS21 = new JpaRepositoryState("S21", true); stateS21.setParentState(stateS2); JpaRepositoryState stateS211 = new JpaRepositoryState("S211", true); stateS211.setParentState(stateS21); JpaRepositoryState stateS212 = new JpaRepositoryState("S212"); stateS212.setParentState(stateS21); stateRepository.save(stateS0); stateRepository.save(stateS1); stateRepository.save(stateS11); stateRepository.save(stateS12); stateRepository.save(stateS2); stateRepository.save(stateS21); stateRepository.save(stateS211); stateRepository.save(stateS212); ``` Fourth and finally, you must create transitions. The following example shows how to do so: ``` JpaRepositoryTransition transitionS1ToS1 = new JpaRepositoryTransition(stateS1, stateS1, "A"); transitionS1ToS1.setGuard(foo1Guard); JpaRepositoryTransition transitionS1ToS11 = new JpaRepositoryTransition(stateS1, stateS11, "B"); JpaRepositoryTransition transitionS21ToS211 = new JpaRepositoryTransition(stateS21, stateS211, "B"); JpaRepositoryTransition transitionS1ToS2 = new JpaRepositoryTransition(stateS1, stateS2, "C"); JpaRepositoryTransition transitionS1ToS0 = new JpaRepositoryTransition(stateS1, stateS0, "D"); JpaRepositoryTransition transitionS211ToS21 = new JpaRepositoryTransition(stateS211, stateS21, "D"); JpaRepositoryTransition transitionS0ToS211 = new JpaRepositoryTransition(stateS0, stateS211, "E"); JpaRepositoryTransition transitionS1ToS211 = new JpaRepositoryTransition(stateS1, stateS211, "F"); JpaRepositoryTransition transitionS2ToS21 = new JpaRepositoryTransition(stateS2, stateS21, "F"); JpaRepositoryTransition transitionS11ToS211 = new JpaRepositoryTransition(stateS11, stateS211, "G"); JpaRepositoryTransition transitionS0 = new JpaRepositoryTransition(stateS0, stateS0, "H"); transitionS0.setKind(TransitionKind.INTERNAL); transitionS0.setGuard(foo0Guard); transitionS0.setActions(new HashSet<>(Arrays.asList(fooAction))); JpaRepositoryTransition transitionS1 = new JpaRepositoryTransition(stateS1, stateS1, "H"); transitionS1.setKind(TransitionKind.INTERNAL); JpaRepositoryTransition transitionS2 = new JpaRepositoryTransition(stateS2, stateS2, "H"); transitionS2.setKind(TransitionKind.INTERNAL); transitionS2.setGuard(foo1Guard); transitionS2.setActions(new HashSet<>(Arrays.asList(fooAction))); JpaRepositoryTransition transitionS11ToS12 = new JpaRepositoryTransition(stateS11, stateS12, "I"); JpaRepositoryTransition transitionS12ToS212 = new JpaRepositoryTransition(stateS12, stateS212, "I"); JpaRepositoryTransition transitionS211ToS12 = new JpaRepositoryTransition(stateS211, stateS12, "I"); JpaRepositoryTransition transitionS11 = new JpaRepositoryTransition(stateS11, stateS11, "J"); JpaRepositoryTransition transitionS2ToS1 = new JpaRepositoryTransition(stateS2, stateS1, "K"); transitionRepository.save(transitionS1ToS1); transitionRepository.save(transitionS1ToS11); transitionRepository.save(transitionS21ToS211); transitionRepository.save(transitionS1ToS2); transitionRepository.save(transitionS1ToS0); transitionRepository.save(transitionS211ToS21); transitionRepository.save(transitionS0ToS211); transitionRepository.save(transitionS1ToS211); transitionRepository.save(transitionS2ToS21); transitionRepository.save(transitionS11ToS211); transitionRepository.save(transitionS0); transitionRepository.save(transitionS1); transitionRepository.save(transitionS2); transitionRepository.save(transitionS11ToS12); transitionRepository.save(transitionS12ToS212); transitionRepository.save(transitionS211ToS12); transitionRepository.save(transitionS11); transitionRepository.save(transitionS2ToS1); ``` You can find a complete example[here](#statemachine-examples-datajpa). This example also shows how you can pre-populate a repository from an existing JSON file that has definitions for entity classes. #### Redis The actual repository implementations for a Redis instance are`RedisStateRepository`, `RedisTransitionRepository`, `RedisActionRepository`, and `RedisGuardRepository`, which are backed by the entity classes `RedisRepositoryState`, `RedisRepositoryTransition`,`RedisRepositoryAction`, and `RedisRepositoryGuard`, respectively. The next example shows the generic way to manually update states and transitions for Redis. This is equivalent to machine shown in[SimpleMachine](#image-sm-repository-simplemachine). ``` @Autowired StateRepository stateRepository; @Autowired TransitionRepository transitionRepository; void addConfig() { RedisRepositoryState stateS1 = new RedisRepositoryState("S1", true); RedisRepositoryState stateS2 = new RedisRepositoryState("S2"); RedisRepositoryState stateS3 = new RedisRepositoryState("S3"); stateRepository.save(stateS1); stateRepository.save(stateS2); stateRepository.save(stateS3); RedisRepositoryTransition transitionS1ToS2 = new RedisRepositoryTransition(stateS1, stateS2, "E1"); RedisRepositoryTransition transitionS2ToS3 = new RedisRepositoryTransition(stateS2, stateS3, "E2"); transitionRepository.save(transitionS1ToS2); transitionRepository.save(transitionS2ToS3); } ``` The following example is equivalent to machine shown in[SimpleSubMachine](#image-sm-repository-simplesubmachine): ``` @Autowired StateRepository stateRepository; @Autowired TransitionRepository transitionRepository; void addConfig() { RedisRepositoryState stateS1 = new RedisRepositoryState("S1", true); RedisRepositoryState stateS2 = new RedisRepositoryState("S2"); RedisRepositoryState stateS3 = new RedisRepositoryState("S3"); stateRepository.save(stateS1); stateRepository.save(stateS2); stateRepository.save(stateS3); RedisRepositoryTransition transitionS1ToS2 = new RedisRepositoryTransition(stateS1, stateS2, "E1"); RedisRepositoryTransition transitionS2ToS3 = new RedisRepositoryTransition(stateS2, stateS3, "E2"); transitionRepository.save(transitionS1ToS2); transitionRepository.save(transitionS2ToS3); } ``` #### MongoDB The actual repository implementations for a MongoDB instance are`MongoDbStateRepository`, `MongoDbTransitionRepository`, `MongoDbActionRepository`, and `MongoDbGuardRepository`, which are backed by the entity classes `MongoDbRepositoryState`, `MongoDbRepositoryTransition`,`MongoDbRepositoryAction`, and `MongoDbRepositoryGuard`, respectively. The next example shows the generic way to manually update states and transitions for MongoDB. This is equivalent to the machine shown in[SimpleMachine](#image-sm-repository-simplemachine). ``` @Autowired StateRepository stateRepository; @Autowired TransitionRepository transitionRepository; void addConfig() { MongoDbRepositoryState stateS1 = new MongoDbRepositoryState("S1", true); MongoDbRepositoryState stateS2 = new MongoDbRepositoryState("S2"); MongoDbRepositoryState stateS3 = new MongoDbRepositoryState("S3"); stateRepository.save(stateS1); stateRepository.save(stateS2); stateRepository.save(stateS3); MongoDbRepositoryTransition transitionS1ToS2 = new MongoDbRepositoryTransition(stateS1, stateS2, "E1"); MongoDbRepositoryTransition transitionS2ToS3 = new MongoDbRepositoryTransition(stateS2, stateS3, "E2"); transitionRepository.save(transitionS1ToS2); transitionRepository.save(transitionS2ToS3); } ``` The following example is equivalent to the machine shown in[SimpleSubMachine](#image-sm-repository-simplesubmachine). ``` @Autowired StateRepository stateRepository; @Autowired TransitionRepository transitionRepository; void addConfig() { MongoDbRepositoryState stateS1 = new MongoDbRepositoryState("S1", true); MongoDbRepositoryState stateS2 = new MongoDbRepositoryState("S2"); MongoDbRepositoryState stateS3 = new MongoDbRepositoryState("S3"); MongoDbRepositoryState stateS21 = new MongoDbRepositoryState("S21", true); stateS21.setParentState(stateS2); MongoDbRepositoryState stateS22 = new MongoDbRepositoryState("S22"); stateS22.setParentState(stateS2); stateRepository.save(stateS1); stateRepository.save(stateS2); stateRepository.save(stateS3); stateRepository.save(stateS21); stateRepository.save(stateS22); MongoDbRepositoryTransition transitionS1ToS2 = new MongoDbRepositoryTransition(stateS1, stateS2, "E1"); MongoDbRepositoryTransition transitionS2ToS3 = new MongoDbRepositoryTransition(stateS21, stateS22, "E2"); MongoDbRepositoryTransition transitionS21ToS22 = new MongoDbRepositoryTransition(stateS2, stateS3, "E3"); transitionRepository.save(transitionS1ToS2); transitionRepository.save(transitionS2ToS3); transitionRepository.save(transitionS21ToS22); } ``` ### Repository Persistence Apart from storing machine configuration (as shown in[Repository Configuration](#sm-repository-config)), in an external repository, you canx also persist machines into repositories. The `StateMachineRepository` interface is a central access point that interacts with machine persistence and is backed by the entity class`RepositoryStateMachine`. #### JPA The actual repository implementation for JPA is`JpaStateMachineRepository`, which is backed by the entity class`JpaRepositoryStateMachine`. The following example shows the generic way to persist a machine for JPA: ``` @Autowired StateMachineRepository stateMachineRepository; void persist() { JpaRepositoryStateMachine machine = new JpaRepositoryStateMachine(); machine.setMachineId("machine"); machine.setState("S1"); // raw byte[] representation of a context machine.setStateMachineContext(new byte[] { 0 }); stateMachineRepository.save(machine); } ``` #### Redis The actual repository implementation for a Redis is`RedisStateMachineRepository`, which is backed by the entity class`RedisRepositoryStateMachine`. The following example shows the generic way to persist a machine for Redis: ``` @Autowired StateMachineRepository stateMachineRepository; void persist() { RedisRepositoryStateMachine machine = new RedisRepositoryStateMachine(); machine.setMachineId("machine"); machine.setState("S1"); // raw byte[] representation of a context machine.setStateMachineContext(new byte[] { 0 }); stateMachineRepository.save(machine); } ``` #### MongoDB The actual repository implementation for MongoDB is`MongoDbStateMachineRepository`, which is backed by the entity class`MongoDbRepositoryStateMachine`. The following example shows the generic way to persist a machine for MongoDB: ``` @Autowired StateMachineRepository stateMachineRepository; void persist() { MongoDbRepositoryStateMachine machine = new MongoDbRepositoryStateMachine(); machine.setMachineId("machine"); machine.setState("S1"); // raw byte[] representation of a context machine.setStateMachineContext(new byte[] { 0 }); stateMachineRepository.save(machine); } ``` # Recipes This chapter contains documentation for existing built-in state machine recipes. Spring Statemachine is a foundational framework. That is, it does not have much higher-level functionality or many dependencies beyond Spring Framework. Consequently, correctly using a state machine may be difficult. To help, we have created a set of recipe modules that address common use cases. What exactly is a recipe? A state machine recipe is a module that addresses a common use case. In essence, a state machine recipe is both an example that we have tried to make it easy for you to reuse and extend. | |Recipes are a great way to make external contributions to the Spring
Statemachine project. If you are not ready to contribute to the
framework core itself, a custom and common recipe is a great way to
share functionality with other users.| |---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ## Persist The persist recipe is a simple utility that lets you use a single state machine instance to persist and update the state of an arbitrary item in a repository. The recipe’s main class is `PersistStateMachineHandler`, which makes three assumptions: * An instance of a `StateMachine` needs to be used with a `PersistStateMachineHandler`. Note that states and Events are required to be type of `String`. * `PersistStateChangeListener` needs to be registered with handler to react to persist request. * The `handleEventWithState` method is used to orchestrate state changes. You can find a sample that shows how to use this recipe at[Persist](#statemachine-examples-persist). ## Tasks The tasks recipe is a concept to run DAG (Directed Acrylic Graph) of `Runnable` instances that use a state machine. This recipe has been developed from ideas introduced in [Tasks](#statemachine-examples-tasks) sample. The next image shows the generic concept of a state machine. In this state chart, everything under `TASKS` shows a generic concept of how a single task is executed. Because this recipe lets you register a deep hierarchical DAG of tasks (meaning a real state chart would be a deeply nested collection of sub-states and regions), we have no need to be more precise. For example, if you have only two registered tasks, the following state chart would be correct when `TASK_id` is replaced with `TASK_1` and `TASK_2` (assuming the registered tasks IDs are `1` and `2`). statechart9 Executing a `Runnable` may result an error. Especially if a complex DAG of tasks is involved, you want to have a way to handle task execution errors and then have a way to continue execution without executing already successfully executed tasks. Also, it would be nice if some execution errors can be handled automatically. As a last fallback, if an error cannot be handled automatically, the state machine is put into a state where the user can handle errors manually. `TasksHandler` contains a builder method to configure a handler instance and follows a simple builder pattern. You can use this builder to register `Runnable` tasks and `TasksListener` instances and define`StateMachinePersist` hook. Now we can take a simple `Runnable` that runs a simple sleep as the following example shows: ``` private Runnable sleepRunnable() { return new Runnable() { @Override public void run() { try { Thread.sleep(2000); } catch (InterruptedException e) { } } }; } ``` | |The preceding example is the base for all of the examples in this chapter.| |---|--------------------------------------------------------------------------| To execute multiple `sleepRunnable` tasks, you can register tasks and execute `runTasks()` method from `TasksHandler`, as the following example shows: ``` TasksHandler handler = TasksHandler.builder() .task("1", sleepRunnable()) .task("2", sleepRunnable()) .task("3", sleepRunnable()) .build(); handler.runTasks(); ``` To listen to what is happening with a task execution, you can register an instance of a `TasksListener` with a `TasksHandler`. This recipe provides an adapter `TasksListenerAdapter` if you do not want to implement a full interface. The listener provides a various hooks to listen tasks execution events. The following example shows the definition of the`MyTasksListener` class: ``` private class MyTasksListener extends TasksListenerAdapter { @Override public void onTasksStarted() { } @Override public void onTasksContinue() { } @Override public void onTaskPreExecute(Object id) { } @Override public void onTaskPostExecute(Object id) { } @Override public void onTaskFailed(Object id, Exception exception) { } @Override public void onTaskSuccess(Object id) { } @Override public void onTasksSuccess() { } @Override public void onTasksError() { } @Override public void onTasksAutomaticFix(TasksHandler handler, StateContext context) { } } ``` You can either register listeners by using a builder or register them directly with a`TasksHandler` as the following example shows: ``` MyTasksListener listener1 = new MyTasksListener(); MyTasksListener listener2 = new MyTasksListener(); TasksHandler handler = TasksHandler.builder() .task("1", sleepRunnable()) .task("2", sleepRunnable()) .task("3", sleepRunnable()) .listener(listener1) .build(); handler.addTasksListener(listener2); handler.removeTasksListener(listener2); handler.runTasks(); ``` Every task needs to have a unique identifier, and (optionally) a task can be defined to be a sub-task. Effectively, this creates a DAG of tasks. The following example shows how to create a deep nested DAG of tasks: ``` TasksHandler handler = TasksHandler.builder() .task("1", sleepRunnable()) .task("1", "12", sleepRunnable()) .task("1", "13", sleepRunnable()) .task("2", sleepRunnable()) .task("2", "22", sleepRunnable()) .task("2", "23", sleepRunnable()) .task("3", sleepRunnable()) .task("3", "32", sleepRunnable()) .task("3", "33", sleepRunnable()) .build(); handler.runTasks(); ``` When an error happens and the state machine running these tasks goes into an`ERROR` state, you can call `fixCurrentProblems` handler method to reset the current state of the tasks kept in the state machine’s extended state variables. You can then use the `continueFromError` handler method to instruct the state machine to transition from the `ERROR` state back to the`READY` state, where you can again run tasks. The following example shows how to do so: ``` TasksHandler handler = TasksHandler.builder() .task("1", sleepRunnable()) .task("2", sleepRunnable()) .task("3", sleepRunnable()) .build(); handler.runTasks(); handler.fixCurrentProblems(); handler.continueFromError(); ``` # State Machine Examples This part of the reference documentation explains the use of state machines together with sample code and UML state charts. We use a few shortcuts when representing the relationship between a state chart, Spring Statemachine configuration, and what an application does with a state machine. For complete examples, you should study the samples repository. Samples are built directly from a main source distribution during a normal build cycle. This chapter includes the following samples: [Turnstile](#statemachine-examples-turnstile) [Turnstile Reactive](#statemachine-examples-turnstilereactive) [Showcase](#statemachine-examples-showcase) [CD Player](#statemachine-examples-cdplayer) [Tasks](#statemachine-examples-tasks) [Washer](#statemachine-examples-washer) [Persist](#statemachine-examples-persist) [Zookeeper](#statemachine-examples-zookeeper) [Web](#statemachine-examples-web) [Scope](#statemachine-examples-scope) [Security](#statemachine-examples-security) [Event Service](#statemachine-examples-eventservice) [Deploy](#statemachine-examples-deploy) [Order Shipping](#statemachine-examples-ordershipping) [JPA Configuration](#statemachine-examples-datajpa) [Data Persist](#statemachine-examples-datapersist) [Data JPA Persist](#statemachine-examples-datajpapersist) [Data Multi Persist](#statemachine-examples-datajpamultipersist) [Monitoring](#statemachine-examples-monitoring) The following listing shows how to build the samples: ``` ./gradlew clean build -x test ``` Every sample is located in its own directory under`spring-statemachine-samples`. The samples are based on Spring Boot and Spring Shell, and you can find the usual Boot fat jars under every sample project’s `build/libs` directory. | |The filenames for the jars to which we refer in this section are populated during a
build of this document, meaning that, if you build samples from
master, you have files with a `BUILD-SNAPSHOT` postfix.| |---|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| ## Turnstile Turnstile is a simple device that gives you access if payment is made. It is a concept that is simple to model using a state machine. In its simplest, form there are only two states: `LOCKED` and `UNLOCKED`. Two events, `COIN` and `PUSH` can happen, depending on whether someone makes a payment or tries to go through the turnstile. The following image shows the state machine: statechart1 The following listing shows the enumeration that defines the possible states: States ``` public enum States { LOCKED, UNLOCKED } ``` The following listing shows the enumeration that defines the events: Events ``` public enum Events { COIN, PUSH } ``` The following listing shows the code that configures the state machine: Configuration ``` @Configuration @EnableStateMachine static class StateMachineConfig extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.LOCKED) .states(EnumSet.allOf(States.class)); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.LOCKED) .target(States.UNLOCKED) .event(Events.COIN) .and() .withExternal() .source(States.UNLOCKED) .target(States.LOCKED) .event(Events.PUSH); } } ``` You can see how this sample state machine interacts with events by running the `turnstile` sample. The following listing shows how to do so and shows the command’s output: ``` $ java -jar spring-statemachine-samples-turnstile-3.0.1.jar sm>sm print +----------------------------------------------------------------+ | SM | +----------------------------------------------------------------+ | | | +----------------+ +----------------+ | | *-->| LOCKED | | UNLOCKED | | | +----------------+ +----------------+ | | +---| entry/ | | entry/ |---+ | | | | exit/ | | exit/ | | | | | | | | | | | | PUSH| | |---COIN-->| | |COIN | | | | | | | | | | | | | | | | | | | | |<--PUSH---| | | | | +-->| | | |<--+ | | | | | | | | +----------------+ +----------------+ | | | +----------------------------------------------------------------+ sm>sm start State changed to LOCKED State machine started sm>sm event COIN State changed to UNLOCKED Event COIN send sm>sm event PUSH State changed to LOCKED Event PUSH send ``` ## Turnstile Reactive Turnstile reactive is an enhacement to [Turnstile](#statemachine-examples-turnstile) sample using same *StateMachine* concept and adding a reactive web layer communicating reactively with a *StateMachine* reactive interfaces. `StateMachineController` is a simple `@RestController` where we autowire our `StateMachine`. ``` @Autowired private StateMachine stateMachine; ``` We create first mapping to return a machine state. As state doesn’t come out from a machine reactively, we can *defer* it so that when a returned `Mono` is subscribed, actual state is requested. ``` @GetMapping("/state") public Mono state() { return Mono.defer(() -> Mono.justOrEmpty(stateMachine.getState().getId())); } ``` To send a single event or multiple events to a machine we can use a `Flux` in both incoming and outgoing layers. `EventResult` here is just for this sample and simply wraps `ResultType` and event. ``` @PostMapping("/events") public Flux events(@RequestBody Flux eventData) { return eventData .filter(ed -> ed.getEvent() != null) .map(ed -> MessageBuilder.withPayload(ed.getEvent()).build()) .flatMap(m -> stateMachine.sendEvent(Mono.just(m))) .map(EventResult::new); } ``` You can use the following command to run the sample: ``` $ java -jar spring-statemachine-samples-turnstilereactive-3.0.1.jar ``` Example of getting a state: ``` GET http://localhost:8080/state ``` Would then response: ``` "LOCKED" ``` Example of sending an event: ``` POST http://localhost:8080/events content-type: application/json { "event": "COIN" } ``` Would then response: ``` [ { "event": "COIN", "resultType": "ACCEPTED" } ] ``` You can post multiple events: ``` POST http://localhost:8080/events content-type: application/json [ { "event": "COIN" }, { "event": "PUSH" } ] ``` Response then contains results for both events: ``` [ { "event": "COIN", "resultType": "ACCEPTED" }, { "event": "PUSH", "resultType": "ACCEPTED" } ] ``` ## Showcase Showcase is a complex state machine that shows all possible transition topologies up to four levels of state nesting. The following image shows the state machine: statechart2 The following listing shows the enumeration that defines the possible states: States ``` public enum States { S0, S1, S11, S12, S2, S21, S211, S212 } ``` The following listing shows the enumeration that defines the events: Events ``` public enum Events { A, B, C, D, E, F, G, H, I } ``` The following listing shows the code that configures the state machine: Configuration - states ``` @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.S0, fooAction()) .state(States.S0) .and() .withStates() .parent(States.S0) .initial(States.S1) .state(States.S1) .and() .withStates() .parent(States.S1) .initial(States.S11) .state(States.S11) .state(States.S12) .and() .withStates() .parent(States.S0) .state(States.S2) .and() .withStates() .parent(States.S2) .initial(States.S21) .state(States.S21) .and() .withStates() .parent(States.S21) .initial(States.S211) .state(States.S211) .state(States.S212); } ``` The following listing shows the code that configures the state machine’s transitions: Configuration - transitions ``` @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.S1).target(States.S1).event(Events.A) .guard(foo1Guard()) .and() .withExternal() .source(States.S1).target(States.S11).event(Events.B) .and() .withExternal() .source(States.S21).target(States.S211).event(Events.B) .and() .withExternal() .source(States.S1).target(States.S2).event(Events.C) .and() .withExternal() .source(States.S2).target(States.S1).event(Events.C) .and() .withExternal() .source(States.S1).target(States.S0).event(Events.D) .and() .withExternal() .source(States.S211).target(States.S21).event(Events.D) .and() .withExternal() .source(States.S0).target(States.S211).event(Events.E) .and() .withExternal() .source(States.S1).target(States.S211).event(Events.F) .and() .withExternal() .source(States.S2).target(States.S11).event(Events.F) .and() .withExternal() .source(States.S11).target(States.S211).event(Events.G) .and() .withExternal() .source(States.S211).target(States.S0).event(Events.G) .and() .withInternal() .source(States.S0).event(Events.H) .guard(foo0Guard()) .action(fooAction()) .and() .withInternal() .source(States.S2).event(Events.H) .guard(foo1Guard()) .action(fooAction()) .and() .withInternal() .source(States.S1).event(Events.H) .and() .withExternal() .source(States.S11).target(States.S12).event(Events.I) .and() .withExternal() .source(States.S211).target(States.S212).event(Events.I) .and() .withExternal() .source(States.S12).target(States.S212).event(Events.I); } ``` The following listing shows the code that configures the state machine’s actions and guards: Configuration - actions and guards ``` @Bean public FooGuard foo0Guard() { return new FooGuard(0); } @Bean public FooGuard foo1Guard() { return new FooGuard(1); } @Bean public FooAction fooAction() { return new FooAction(); } ``` The following listing shows how the single action is defined: Action ``` private static class FooAction implements Action { @Override public void execute(StateContext context) { Map variables = context.getExtendedState().getVariables(); Integer foo = context.getExtendedState().get("foo", Integer.class); if (foo == null) { log.info("Init foo to 0"); variables.put("foo", 0); } else if (foo == 0) { log.info("Switch foo to 1"); variables.put("foo", 1); } else if (foo == 1) { log.info("Switch foo to 0"); variables.put("foo", 0); } } } ``` The following listing shows how the single guard is defined: Guard ``` private static class FooGuard implements Guard { private final int match; public FooGuard(int match) { this.match = match; } @Override public boolean evaluate(StateContext context) { Object foo = context.getExtendedState().getVariables().get("foo"); return !(foo == null || !foo.equals(match)); } } ``` The following listing shows the output that this state machine produces when it runs and various events are sent to it: ``` sm>sm start Init foo to 0 Entry state S0 Entry state S1 Entry state S11 State machine started sm>sm event A Event A send sm>sm event C Exit state S11 Exit state S1 Entry state S2 Entry state S21 Entry state S211 Event C send sm>sm event H Switch foo to 1 Internal transition source=S0 Event H send sm>sm event C Exit state S211 Exit state S21 Exit state S2 Entry state S1 Entry state S11 Event C send sm>sm event A Exit state S11 Exit state S1 Entry state S1 Entry state S11 Event A send ``` In the preceding output, we can see that: * The state machine is started, which takes it to its initial state (`S11`) through superstates (`S1`) and (`S0`). Also, the extended state variable, `foo`, is initialized to `0`. * We try to execute a self transition in state `S1` with event `A`, but nothing happens because the transition is guarded by variable `foo` to be `1`. * We send event `C`, which takes us to the other state machine, where the initial state (`S211`) and its superstates are entered. In there, we can use event `H`, which does a simple internal transition to flip the`foo` variable. Then we go back by using event `C`. * Event `A` is sent again, and now `S1` does a self transition because the guard evaluates to `true`. The following example offers a closer look at how hierarchical states and their event handling works: ``` sm>sm variables No variables sm>sm start Init foo to 0 Entry state S0 Entry state S1 Entry state S11 State machine started sm>sm variables foo=0 sm>sm event H Internal transition source=S1 Event H send sm>sm variables foo=0 sm>sm event C Exit state S11 Exit state S1 Entry state S2 Entry state S21 Entry state S211 Event C send sm>sm variables foo=0 sm>sm event H Switch foo to 1 Internal transition source=S0 Event H send sm>sm variables foo=1 sm>sm event H Switch foo to 0 Internal transition source=S2 Event H send sm>sm variables foo=0 ``` In the preceding sample: * We print extended state variables in various stages. * With event `H`, we end up running an internal transition, which is logged with its source state. * Note how event `H` is handled in different states (`S0`, `S1`, and `S2`). This is a good example of how hierarchical states and their event handling works. If state `S2` is unable to handle event `H` due to a guard condition, its parent is checked next. This guarantees that, while the machine is on state `S2`, the `foo` flag is always flipped around. However, in state `S1`, event `H` always matches to its dummy transition without guard or action, so it never happens. ## CD Player CD Player is a sample which resembles a use case that many people have used in the real world. CD Player itself is a really simple entity that allows a user to open a deck, insert or change a disk, and then drive the player’s functionality by pressing various buttons (`eject`, `play`,`stop`, `pause`, `rewind`, and `backward`). How many of us have really given thought to what it will take to make code that interacts with hardware to drive a CD Player. Yes, the concept of a player is simple, but, if you look behind the scenes, things actually get a bit convoluted. You have probably noticed that, if your deck is open and you press play, the deck closes and a song starts to play (if a CD was inserted). In a sense, when the deck is open, you first need to close it and then try to start playing (again, if a CD is actually inserted). Hopefully, you have now realized that a simple CD Player is so simple. Sure, you can wrap all this with a simple class that has a few boolean variables and probably a few nested if-else clauses. That will do the job, but what about if you need to make all this behavior much more complex? Do you really want to keep adding more flags and if-else clauses? The following image shows the state machine for our simple CD player: statechart3 The rest of this section goes through how this sample and its state machine is designed and how those two interacts with each other. The following three configuration sections are used within an `EnumStateMachineConfigurerAdapter`. ``` @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.IDLE) .state(States.IDLE) .and() .withStates() .parent(States.IDLE) .initial(States.CLOSED) .state(States.CLOSED, closedEntryAction(), null) .state(States.OPEN) .and() .withStates() .state(States.BUSY) .and() .withStates() .parent(States.BUSY) .initial(States.PLAYING) .state(States.PLAYING) .state(States.PAUSED); } ``` ``` @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.CLOSED).target(States.OPEN).event(Events.EJECT) .and() .withExternal() .source(States.OPEN).target(States.CLOSED).event(Events.EJECT) .and() .withExternal() .source(States.OPEN).target(States.CLOSED).event(Events.PLAY) .and() .withExternal() .source(States.PLAYING).target(States.PAUSED).event(Events.PAUSE) .and() .withInternal() .source(States.PLAYING) .action(playingAction()) .timer(1000) .and() .withInternal() .source(States.PLAYING).event(Events.BACK) .action(trackAction()) .and() .withInternal() .source(States.PLAYING).event(Events.FORWARD) .action(trackAction()) .and() .withExternal() .source(States.PAUSED).target(States.PLAYING).event(Events.PAUSE) .and() .withExternal() .source(States.BUSY).target(States.IDLE).event(Events.STOP) .and() .withExternal() .source(States.IDLE).target(States.BUSY).event(Events.PLAY) .action(playAction()) .guard(playGuard()) .and() .withInternal() .source(States.OPEN).event(Events.LOAD).action(loadAction()); } ``` ``` @Bean public ClosedEntryAction closedEntryAction() { return new ClosedEntryAction(); } @Bean public LoadAction loadAction() { return new LoadAction(); } @Bean public TrackAction trackAction() { return new TrackAction(); } @Bean public PlayAction playAction() { return new PlayAction(); } @Bean public PlayingAction playingAction() { return new PlayingAction(); } @Bean public PlayGuard playGuard() { return new PlayGuard(); } ``` In the preceding configuration: * We used `EnumStateMachineConfigurerAdapter` to configure states and transitions. * The `CLOSED` and `OPEN` states are defined as substates of `IDLE`, and the `PLAYING` and `PAUSED` states are defined as substates of `BUSY`. * With the `CLOSED` state, we added an entry action as a bean called`closedEntryAction`. * In the transitions we mostly map events to expected state transitions, such as `EJECT` closing and opening a deck and `PLAY`, `STOP`, and `PAUSE` doing their natural transitions. For other transitions, we did the following: * For source state `PLAYING`, we added a timer trigger, which is needed to automatically track elapsed time within a playing track and to have a facility for making the decision about when to switch the to next track. * For the `PLAY` event, if the source state is `IDLE` and the target state is`BUSY`, we defined an action called `playAction` and a guard called `playGuard`. * For the `LOAD` event and the `OPEN` state, we defined an internal transition with an action called `loadAction`, which tracks inserting a disc with extended-state variables. * The `PLAYING` state defines three internal transitions. One is triggered by a timer that runs an action called `playingAction`, which updates the extended state variables. The other two transitions use `trackAction`with different events (`BACK` and `FORWARD`, respectively) to handle when the user wants to go back or forward in tracks. This machine has only have six states, which are defined by the following enumeration: ``` public enum States { // super state of PLAYING and PAUSED BUSY, PLAYING, PAUSED, // super state of CLOSED and OPEN IDLE, CLOSED, OPEN } ``` Events represent the buttons the user can press and whether the user loads a disc into the player. The following enumeration defines the events: ``` public enum Events { PLAY, STOP, PAUSE, EJECT, LOAD, FORWARD, BACK } ``` The `cdPlayer` and `library` beans are used to drive the application. The following listing shows the definition of these two beans: ``` @Bean public CdPlayer cdPlayer() { return new CdPlayer(); } @Bean public Library library() { return Library.buildSampleLibrary(); } ``` We define extended state variable keys as simple enumerations, as the following listing shows: ``` public enum Variables { CD, TRACK, ELAPSEDTIME } public enum Headers { TRACKSHIFT } ``` We wanted to make this sample type safe, so we define our own annotation (`@StatesOnTransition`), which has a mandatory meta annotation (`@OnTransition`). The following listing defines the `@StatesOnTransition` annotation: ``` @Target(ElementType.METHOD) @Retention(RetentionPolicy.RUNTIME) @OnTransition public @interface StatesOnTransition { States[] source() default {}; States[] target() default {}; } ``` `ClosedEntryAction` is an entry action for the `CLOSED` state, to send a `PLAY` event to the state machine if a disc is present. The following listing defines `ClosedEntryAction`: ``` public static class ClosedEntryAction implements Action { @Override public void execute(StateContext context) { if (context.getTransition() != null && context.getEvent() == Events.PLAY && context.getTransition().getTarget().getId() == States.CLOSED && context.getExtendedState().getVariables().get(Variables.CD) != null) { context.getStateMachine() .sendEvent(Mono.just(MessageBuilder .withPayload(Events.PLAY).build())) .subscribe(); } } } ``` `LoadAction` update an extended state variable if event headers contain information about a disc to load. The following listing defines `LoadAction`: ``` public static class LoadAction implements Action { @Override public void execute(StateContext context) { Object cd = context.getMessageHeader(Variables.CD); context.getExtendedState().getVariables().put(Variables.CD, cd); } } ``` `PlayAction` resets the player’s elapsed time, which is kept as an extended state variable. The following listing defines `PlayAction`: ``` public static class PlayAction implements Action { @Override public void execute(StateContext context) { context.getExtendedState().getVariables().put(Variables.ELAPSEDTIME, 0l); context.getExtendedState().getVariables().put(Variables.TRACK, 0); } } ``` `PlayGuard` guards the transition from `IDLE` to `BUSY` with the`PLAY` event if the `CD` extended state variable does not indicate that a disc has been loaded. The following listing defines `PlayGuard`: ``` public static class PlayGuard implements Guard { @Override public boolean evaluate(StateContext context) { ExtendedState extendedState = context.getExtendedState(); return extendedState.getVariables().get(Variables.CD) != null; } } ``` `PlayingAction` updates an extended state variable called `ELAPSEDTIME`, which the player can use to read and update its LCD status display. `PlayingAction` also handles track shifting when the user goe back or forward in tracks. The following example defines `PlayingAction`: ``` public static class PlayingAction implements Action { @Override public void execute(StateContext context) { Map variables = context.getExtendedState().getVariables(); Object elapsed = variables.get(Variables.ELAPSEDTIME); Object cd = variables.get(Variables.CD); Object track = variables.get(Variables.TRACK); if (elapsed instanceof Long) { long e = ((Long)elapsed) + 1000l; if (e > ((Cd) cd).getTracks()[((Integer) track)].getLength()*1000) { context.getStateMachine() .sendEvent(Mono.just(MessageBuilder .withPayload(Events.FORWARD) .setHeader(Headers.TRACKSHIFT.toString(), 1).build())) .subscribe(); } else { variables.put(Variables.ELAPSEDTIME, e); } } } } ``` `TrackAction` handles track shift actions when the user goes back or forward in tracks. If a track is the last on a disc, playing is stopped and the `STOP`event is sent to a state machine. The following example defines `TrackAction`: ``` public static class TrackAction implements Action { @Override public void execute(StateContext context) { Map variables = context.getExtendedState().getVariables(); Object trackshift = context.getMessageHeader(Headers.TRACKSHIFT.toString()); Object track = variables.get(Variables.TRACK); Object cd = variables.get(Variables.CD); if (trackshift instanceof Integer && track instanceof Integer && cd instanceof Cd) { int next = ((Integer)track) + ((Integer)trackshift); if (next >= 0 && ((Cd)cd).getTracks().length > next) { variables.put(Variables.ELAPSEDTIME, 0l); variables.put(Variables.TRACK, next); } else if (((Cd)cd).getTracks().length <= next) { context.getStateMachine() .sendEvent(Mono.just(MessageBuilder .withPayload(Events.STOP).build())) .subscribe(); } } } } ``` One other important aspect of state machines is that they have their own responsibilities (mostly around handling states) and that all application level logic should be kept outside. This means that applications need to have a ways to interact with a state machine. Also, note that we annotated `CdPlayer` with `@WithStateMachine`, which instructs a state machine to find methods from your POJO, which are then called with various transitions. The following example shows how it updates its LCD status display: ``` @OnTransition(target = "BUSY") public void busy(ExtendedState extendedState) { Object cd = extendedState.getVariables().get(Variables.CD); if (cd != null) { cdStatus = ((Cd)cd).getName(); } } ``` In the preceding example, we use the `@OnTransition` annotation to hook a callback when a transition happens with a target state of `BUSY`. The following listing shows how our state machine handles whether the player is closed: ``` @StatesOnTransition(target = {States.CLOSED, States.IDLE}) public void closed(ExtendedState extendedState) { Object cd = extendedState.getVariables().get(Variables.CD); if (cd != null) { cdStatus = ((Cd)cd).getName(); } else { cdStatus = "No CD"; } trackStatus = ""; } ``` `@OnTransition` (which we used in the preceding examples) can only be used with strings that are matched from enumerations. `@StatesOnTransition`lets you create your own type-safe annotations that use real enumerations. The following example shows how this state machine actually works. ``` sm>sm start Entry state IDLE Entry state CLOSED State machine started sm>cd lcd No CD sm>cd library 0: Greatest Hits 0: Bohemian Rhapsody 05:56 1: Another One Bites the Dust 03:36 1: Greatest Hits II 0: A Kind of Magic 04:22 1: Under Pressure 04:08 sm>cd eject Exit state CLOSED Entry state OPEN sm>cd load 0 Loading cd Greatest Hits sm>cd play Exit state OPEN Entry state CLOSED Exit state CLOSED Exit state IDLE Entry state BUSY Entry state PLAYING sm>cd lcd Greatest Hits Bohemian Rhapsody 00:03 sm>cd forward sm>cd lcd Greatest Hits Another One Bites the Dust 00:04 sm>cd stop Exit state PLAYING Exit state BUSY Entry state IDLE Entry state CLOSED sm>cd lcd Greatest Hits ``` In the preceding run: * The state machine is started, which causes the machine to be initialized. * The CD player’s LCD screen status is printed. * The CD library is printed. * The CD player’s deck is opened. * The CD with index 0 is loaded into a deck. * Play causes the deck to get closed and immediate play, because a disc was inserted. * We print the LCD status and request the next track. * We stop playing. ## Tasks The Tasks sample demonstrates parallel task handling within regions and adds error handling to either automatically or manually fix task problems before continuing back to a state where the tasks can be run again. The following image shows the Tasks state machine: statechart5 On a high level, in this state machine: * We always try to get into the `READY` state so that we can use the RUN event to execute tasks. * Tkhe `TASKS` state, which is composed of three independent regions, has been put in the middle of `FORK` and `JOIN` states, which will cause the regions to go into their initial states and to be joined by their end states. * From the `JOIN` state, we automatically go into a `CHOICE` state, which checks for the existence of error flags in extended state variables. Tasks can set these flags, and doing so gives the `CHOICE` state the ability to go into the `ERROR`state, where errors can be handled either automatically or manually. * The `AUTOMATIC` state in `ERROR` can try to automatically fix an error and goes back to `READY` if it succeeds. If the error is something what cannot be handled automatically, user intervention is needed and the machine is put into the `MANUAL` state by the `FALLBACK` event. The following listing shows the enumeration that defines the possible states: States ``` public enum States { READY, FORK, JOIN, CHOICE, TASKS, T1, T1E, T2, T2E, T3, T3E, ERROR, AUTOMATIC, MANUAL } ``` The following listing shows the enumeration that defines the events: Events ``` public enum Events { RUN, FALLBACK, CONTINUE, FIX; } ``` The following listing configures the possible states: Configuration - states ``` @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.READY) .fork(States.FORK) .state(States.TASKS) .join(States.JOIN) .choice(States.CHOICE) .state(States.ERROR) .and() .withStates() .parent(States.TASKS) .initial(States.T1) .end(States.T1E) .and() .withStates() .parent(States.TASKS) .initial(States.T2) .end(States.T2E) .and() .withStates() .parent(States.TASKS) .initial(States.T3) .end(States.T3E) .and() .withStates() .parent(States.ERROR) .initial(States.AUTOMATIC) .state(States.AUTOMATIC, automaticAction(), null) .state(States.MANUAL); } ``` The following listing configures the possible transitions: Configuration - transitions ``` @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.READY).target(States.FORK) .event(Events.RUN) .and() .withFork() .source(States.FORK).target(States.TASKS) .and() .withExternal() .source(States.T1).target(States.T1E) .and() .withExternal() .source(States.T2).target(States.T2E) .and() .withExternal() .source(States.T3).target(States.T3E) .and() .withJoin() .source(States.TASKS).target(States.JOIN) .and() .withExternal() .source(States.JOIN).target(States.CHOICE) .and() .withChoice() .source(States.CHOICE) .first(States.ERROR, tasksChoiceGuard()) .last(States.READY) .and() .withExternal() .source(States.ERROR).target(States.READY) .event(Events.CONTINUE) .and() .withExternal() .source(States.AUTOMATIC).target(States.MANUAL) .event(Events.FALLBACK) .and() .withInternal() .source(States.MANUAL) .action(fixAction()) .event(Events.FIX); } ``` The following guard sends a choice entry into the `ERROR` state and needs to return `TRUE` if an error has happened. This guard checks that all extended state variables(`T1`, `T2`, and `T3`) are `TRUE`. ``` @Bean public Guard tasksChoiceGuard() { return new Guard() { @Override public boolean evaluate(StateContext context) { Map variables = context.getExtendedState().getVariables(); return !(ObjectUtils.nullSafeEquals(variables.get("T1"), true) && ObjectUtils.nullSafeEquals(variables.get("T2"), true) && ObjectUtils.nullSafeEquals(variables.get("T3"), true)); } }; } ``` The following actions below send events to the state machine to request the next step, which is either to fall back or to continue back to ready. ``` @Bean public Action automaticAction() { return new Action() { @Override public void execute(StateContext context) { Map variables = context.getExtendedState().getVariables(); if (ObjectUtils.nullSafeEquals(variables.get("T1"), true) && ObjectUtils.nullSafeEquals(variables.get("T2"), true) && ObjectUtils.nullSafeEquals(variables.get("T3"), true)) { context.getStateMachine() .sendEvent(Mono.just(MessageBuilder .withPayload(Events.CONTINUE).build())) .subscribe(); } else { context.getStateMachine() .sendEvent(Mono.just(MessageBuilder .withPayload(Events.FALLBACK).build())) .subscribe(); } } }; } @Bean public Action fixAction() { return new Action() { @Override public void execute(StateContext context) { Map variables = context.getExtendedState().getVariables(); variables.put("T1", true); variables.put("T2", true); variables.put("T3", true); context.getStateMachine() .sendEvent(Mono.just(MessageBuilder .withPayload(Events.CONTINUE).build())) .subscribe(); } }; } ``` Default region execution is synchronous meaning a regions would be processed sequentially. In this sample we simply want all task regions to get processed parallel. This can be accomplished by defining `RegionExecutionPolicy`: ``` @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withConfiguration() .regionExecutionPolicy(RegionExecutionPolicy.PARALLEL); } ``` The following example shows how this state machine actually works: ``` sm>sm start State machine started Entry state READY sm>tasks run Exit state READY Entry state TASKS run task on T2 run task on T1 run task on T3 run task on T2 done run task on T1 done run task on T3 done Entry state T2 Entry state T1 Entry state T3 Exit state T2 Exit state T1 Exit state T3 Entry state T3E Entry state T1E Entry state T2E Exit state TASKS Entry state READY ``` In the preceding listing, we can see that tasks run multiple times. In the next listing, we introduce errors: ``` sm>tasks list Tasks {T1=true, T3=true, T2=true} sm>tasks fail T1 sm>tasks list Tasks {T1=false, T3=true, T2=true} sm>tasks run Entry state TASKS run task on T1 run task on T3 run task on T2 run task on T1 done run task on T3 done run task on T2 done Entry state T1 Entry state T3 Entry state T2 Entry state T1E Entry state T2E Entry state T3E Exit state TASKS Entry state JOIN Exit state JOIN Entry state ERROR Entry state AUTOMATIC Exit state AUTOMATIC Exit state ERROR Entry state READY ``` In the preceding listing, if we simulate a failure for task T1, it is fixed automatically. In the next listing, we introduce more errors: ``` sm>tasks list Tasks {T1=true, T3=true, T2=true} sm>tasks fail T2 sm>tasks run Entry state TASKS run task on T2 run task on T1 run task on T3 run task on T2 done run task on T1 done run task on T3 done Entry state T2 Entry state T1 Entry state T3 Entry state T1E Entry state T2E Entry state T3E Exit state TASKS Entry state JOIN Exit state JOIN Entry state ERROR Entry state AUTOMATIC Exit state AUTOMATIC Entry state MANUAL sm>tasks fix Exit state MANUAL Exit state ERROR Entry state READY ``` In the precding example, if we simulate failure for either task `T2` or `T3`, the state machine goes to the `MANUAL` state, where problem needs to be fixed manually before it can go back to the `READY` state. ## Washer The washer sample demonstrates how to use a history state to recover a running state configuration with a simulated power-off situation. Anyone who has ever used a washing machine knows that if you somehow pause the program, it continue from the same state when unpaused. You can implement this kind of behavior in a state machine by using a history pseudo state. The following image shows our state machine for a washer: statechart6 The following listing shows the enumeration that defines the possible states: States ``` public enum States { RUNNING, HISTORY, END, WASHING, RINSING, DRYING, POWEROFF } ``` The following listing shows the enumeration that defines the events: Events ``` public enum Events { RINSE, DRY, STOP, RESTOREPOWER, CUTPOWER } ``` The following listing configures the possible states: Configuration - states ``` @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.RUNNING) .state(States.POWEROFF) .end(States.END) .and() .withStates() .parent(States.RUNNING) .initial(States.WASHING) .state(States.RINSING) .state(States.DRYING) .history(States.HISTORY, History.SHALLOW); } ``` The following listing configures the possible transitions: Configuration - transitions ``` @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.WASHING).target(States.RINSING) .event(Events.RINSE) .and() .withExternal() .source(States.RINSING).target(States.DRYING) .event(Events.DRY) .and() .withExternal() .source(States.RUNNING).target(States.POWEROFF) .event(Events.CUTPOWER) .and() .withExternal() .source(States.POWEROFF).target(States.HISTORY) .event(Events.RESTOREPOWER) .and() .withExternal() .source(States.RUNNING).target(States.END) .event(Events.STOP); } ``` The following example shows how this state machine actually works: ``` sm>sm start Entry state RUNNING Entry state WASHING State machine started sm>sm event RINSE Exit state WASHING Entry state RINSING Event RINSE send sm>sm event DRY Exit state RINSING Entry state DRYING Event DRY send sm>sm event CUTPOWER Exit state DRYING Exit state RUNNING Entry state POWEROFF Event CUTPOWER send sm>sm event RESTOREPOWER Exit state POWEROFF Entry state RUNNING Entry state WASHING Entry state DRYING Event RESTOREPOWER send ``` In the preceding run: * The state machine is started, which causes machine to get initialized. * The state machine goes to RINSING state. * The state machine goes to DRYING state. * The state machine cuts power and goes to POWEROFF state. * The state is restored from the HISTORY state, which takes state machine back to its previous known state. ## Persist Persist is a sample that uses the [Persist](#statemachine-recipes-persist) recipe to demonstrate how database entry update logic can be controlled by a state machine. The following image shows the state machine logic and configuration: statechart10 The following listing shows the state machine configuration: StateMachine Config ``` @Configuration @EnableStateMachine static class StateMachineConfig extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("PLACED") .state("PROCESSING") .state("SENT") .state("DELIVERED"); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("PLACED").target("PROCESSING") .event("PROCESS") .and() .withExternal() .source("PROCESSING").target("SENT") .event("SEND") .and() .withExternal() .source("SENT").target("DELIVERED") .event("DELIVER"); } } ``` The following configuration creates `PersistStateMachineHandler`: Handler Config ``` @Configuration static class PersistHandlerConfig { @Autowired private StateMachine stateMachine; @Bean public Persist persist() { return new Persist(persistStateMachineHandler()); } @Bean public PersistStateMachineHandler persistStateMachineHandler() { return new PersistStateMachineHandler(stateMachine); } } ``` The following listing shows the `Order` class used with this sample: Order Class ``` public static class Order { int id; String state; public Order(int id, String state) { this.id = id; this.state = state; } @Override public String toString() { return "Order [id=" + id + ", state=" + state + "]"; } } ``` The following example shows the state machine’s output: ``` sm>persist db Order [id=1, state=PLACED] Order [id=2, state=PROCESSING] Order [id=3, state=SENT] Order [id=4, state=DELIVERED] sm>persist process 1 Exit state PLACED Entry state PROCESSING sm>persist db Order [id=2, state=PROCESSING] Order [id=3, state=SENT] Order [id=4, state=DELIVERED] Order [id=1, state=PROCESSING] sm>persist deliver 3 Exit state SENT Entry state DELIVERED sm>persist db Order [id=2, state=PROCESSING] Order [id=4, state=DELIVERED] Order [id=1, state=PROCESSING] Order [id=3, state=DELIVERED] ``` In the preceding run, the state machine: * Listed rows from an existing embedded database, which is already populated with sample data. * Requested to update order `1` into the `PROCESSING` state. * List database entries again and see that the state has been changed from`PLACED` to `PROCESSING`. * Update order `3` to update its state from `SENT` to`DELIVERED`. | |You may wonder where the database is, because there are literally no
signs of it in the sample code. The sample is based on Spring Boot and,
because the necessary classes are in a classpath, an embedded `HSQL` instance
is created automatically.

Spring Boot even creates an instance of `JdbcTemplate`, which you
can autowire, as we did in `Persist.java`, shown in the following listing:

```
@Autowired
private JdbcTemplate jdbcTemplate;
```| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| Next, we need to handle state changes. The following listing shows how we do so: ``` public void change(int order, String event) { Order o = jdbcTemplate.queryForObject("select id, state from orders where id = ?", new RowMapper() { public Order mapRow(ResultSet rs, int rowNum) throws SQLException { return new Order(rs.getInt("id"), rs.getString("state")); } }, new Object[] { order }); handler.handleEventWithStateReactively(MessageBuilder .withPayload(event).setHeader("order", order).build(), o.state) .subscribe(); } ``` Finally, we use a `PersistStateChangeListener` to update the database, as the following listing shows: ``` private class LocalPersistStateChangeListener implements PersistStateChangeListener { @Override public void onPersist(State state, Message message, Transition transition, StateMachine stateMachine) { if (message != null && message.getHeaders().containsKey("order")) { Integer order = message.getHeaders().get("order", Integer.class); jdbcTemplate.update("update orders set state = ? where id = ?", state.getId(), order); } } } ``` ## Zookeeper Zookeeper is a distributed version from the[Turnstile](#statemachine-examples-turnstile) sample. | |This sample needs an external `Zookeeper` instance that is accessible from`localhost` and has the default port and settings.| |---|----------------------------------------------------------------------------------------------------------------------------| Configuration of this sample is almost the same as the `turnstile` sample. We add only the configuration for the distributed state machine where we configure `StateMachineEnsemble`, as the following listing shows: ``` @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withDistributed() .ensemble(stateMachineEnsemble()); } ``` The actual `StateMachineEnsemble` needs to be created as a bean, together with the `CuratorFramework` client, as the following example shows: ``` @Bean public StateMachineEnsemble stateMachineEnsemble() throws Exception { return new ZookeeperStateMachineEnsemble(curatorClient(), "/foo"); } @Bean public CuratorFramework curatorClient() throws Exception { CuratorFramework client = CuratorFrameworkFactory.builder().defaultData(new byte[0]) .retryPolicy(new ExponentialBackoffRetry(1000, 3)) .connectString("localhost:2181").build(); client.start(); return client; } ``` For the next example, we need to create two different shell instances. We need to create one instance, see what happens, and then create the second instance. The following command starts the shell instances (remember to start only one instance for now): ``` @n1:~# java -jar spring-statemachine-samples-zookeeper-3.0.1.jar ``` When state machine is started, its initial state is`LOCKED`. Then it sends a `COIN` event to transition into `UNLOCKED` state. The following example shows what happens: Shell1 ``` sm>sm start Entry state LOCKED State machine started sm>sm event COIN Exit state LOCKED Entry state UNLOCKED Event COIN send sm>sm state UNLOCKED ``` Now you can open a second shell instance and start a state machine, by using the same command that you used to start the first state machine. You should see that the distributed state (`UNLOCKED`) is entered instead of the default initial state (`LOCKED`). The following example shows the state machine and its output: Shell2 ``` sm>sm start State machine started sm>sm state UNLOCKED ``` Then from either shell (we use second instance in the next example), send a`PUSH` event to transit from the `UNLOCKED` into the `LOCKED` state. The following example shows the state machine command and its output: Shell2 ``` sm>sm event PUSH Exit state UNLOCKED Entry state LOCKED Event PUSH send ``` In the other shell (the first shell if you ran the preceding command in the second shell), you should see the state be changed automatically, based on distributed state kept in Zookeeper. The following example shows the state machine command and its output: Shell1 ``` sm>Exit state UNLOCKED Entry state LOCKED ``` ## Web Web is a distributed state machine example that uses a zookeeper state machine to handle distributed state. See [Zookeeper](#statemachine-examples-zookeeper). | |This example is meant to be run on multiple
browser sessions against multiple different hosts.| |---|--------------------------------------------------------------------------------------------------| This sample uses a modified state machine structure from[Showcase](#statemachine-examples-showcase) to work with a distributed state machine. The following image shows the state machine logic: statechart11 | |Due to the nature of this sample, an instance of a `Zookeeper` state machine is expected to
be available from a localhost for every individual sample instance.| |---|-------------------------------------------------------------------------------------------------------------------------------------------------------------------| This demonstration uses an example that starts three different sample instances. If you run different instances on the same host, you need to distinguish the port each one uses by adding `--server.port=` to the command. Otherwise the default port for each host is `8080`. In this sample run, we have three hosts: `n1`, `n2`, and `n3`. Each one has a local zookeeper instance running and a state machine sample running on a port `8080`. In there different terminals, start the three different state machines by running the following command: ``` # java -jar spring-statemachine-samples-web-3.0.1.jar ``` When all instances are running, you should see that all show similar information when you access them with a browser. The states should be `S0`, `S1`, and `S11`. The extended state variable named `foo` should have a value of `0`. The main state is `S11`. sm dist n1 1 When you press the `Event C` button in any of the browser windows, the distributed state is changed to `S211,` which is the target state denoted by the transition associated with an event of type `C`. The following image shows the change: sm dist n2 2 Now we can press the `Event H` button and see that the internal transition runs on all state machines to change the the value of the extended state variable named `foo` from `0` to `1`. This change is first done on the state machine that receives the event and is then propagated to the other state machines. You should see only the variable named `foo` change from `0` to `1`. sm dist n3 3 Finally, we can send `Event K`, which takes the state machine state back to state `S11`. You should see this happen in all of the browsers. The following image shows the result in one browser: sm dist n1 4 ## Scope Scope is a state machine example that uses session scope to provide an individual instance for every user. The following image shows the states and events within the Scope state machine: statechart12 This simple state machine has three states: `S0`, `S1`, and `S2`. Transitions between those are controlled by three events: `A`, `B`, and `C`. To start the state machine, run the following command in a terminal: ``` # java -jar spring-statemachine-samples-scope-3.0.1.jar ``` When the instance is running, you can open a browser and play with the state machine. If you open the same page in a different browser, (for example, one in Chrome and one in Firefox), you should get a new state machine instance for each user session. The following image shows the state machine in a browser: sm scope 1 ## Security Security is a state machine example that uses most of the possible combinations of securing a state machine. It secures sending events, transitions, and actions. The following image shows the state machine’s states and events: statechart13 To start the state machine, run the following command: ``` # java -jar spring-statemachine-samples-secure-3.0.1.jar ``` We secure event sending by requiring that users have a role of `USER`. Spring Security ensures that no other users can send events to this state machine. The following listing secures event sending: ``` @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withConfiguration() .autoStartup(true) .and() .withSecurity() .enabled(true) .event("hasRole('USER')"); } ``` In this sample we define two users: * A user named `user` who has a role of `USER` * A user named `admin` who has two roles: `USER` and `ADMIN` The password for both users is `password`. The following listing configures the two users: ``` @EnableWebSecurity @EnableGlobalMethodSecurity(securedEnabled = true) static class SecurityConfig extends WebSecurityConfigurerAdapter { @Autowired public void configureGlobal(AuthenticationManagerBuilder auth) throws Exception { auth .inMemoryAuthentication() .withUser("user") .password("password") .roles("USER") .and() .withUser("admin") .password("password") .roles("USER", "ADMIN"); } } ``` We define various transitions between states according to the state chart shown at the beginning of the example. Only a user with an active `ADMIN` role can run the external transitions between `S2` and `S3`. Similarly only an `ADMIN` can run the internal transition the `S1` state. The following listing defines the transitions, including their security: ``` @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.S0).target(States.S1).event(Events.A) .and() .withExternal() .source(States.S1).target(States.S2).event(Events.B) .and() .withExternal() .source(States.S2).target(States.S0).event(Events.C) .and() .withExternal() .source(States.S2).target(States.S3).event(Events.E) .secured("ROLE_ADMIN", ComparisonType.ANY) .and() .withExternal() .source(States.S3).target(States.S0).event(Events.C) .and() .withInternal() .source(States.S0).event(Events.D) .action(adminAction()) .and() .withInternal() .source(States.S1).event(Events.F) .action(transitionAction()) .secured("ROLE_ADMIN", ComparisonType.ANY); } ``` The following listing uses a method called `adminAction` whose return type is `Action` to specify that the action is secured with a role of `ADMIN`: ``` @Scope(proxyMode = ScopedProxyMode.TARGET_CLASS) @Bean public Action adminAction() { return new Action() { @Secured("ROLE_ADMIN") @Override public void execute(StateContext context) { log.info("Executed only for admin role"); } }; } ``` The following `Action` runs an internal transition in state `S` when event `F` is sent. ``` @Bean public Action transitionAction() { return new Action() { @Override public void execute(StateContext context) { log.info("Executed only for admin role"); } }; } ``` The transition itself is secured with a role of `ADMIN`, so this transition does not run if the current user does not hate that role. ## Event Service The event service example shows how you can use state machine concepts as a processing engine for events. This sample evolved from a question: Can I use Spring Statemachine as a microservice to feed events to different state machine instances? In fact, Spring Statemachine can feed events to potentially millions of different state machine instances. This example uses a `Redis` instance to persist state machine instances. Obviously, a million state machine instances in a JVM would be a bad idea, due to memory constraints. This leads to other features of Spring Statemachine that let you persist a`StateMachineContext` and re-use existing instances. For this example, we assume that a shopping application sends different types of `PageView` events to a separate microservice which then tracks user behavior by using a state machine. The following image shows the state model, which has a few states that represent a user navigating a product items list, adding and removing items from a cart, going to a payment page, and initiating a payment operation: statechart14 An actual shopping application would send these events into this service by (for example) using a rest call. More about this later. | |Remember that the focus here is to have an application that exposes a`REST` API that the user can use to send events that can be processed by a
state machine for each request.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| The following state machine configuration models what we have in a state chart. Various actions update the state machine’s `Extended State` to track the number of entries into various states and also how many times the internal transitions for `ADD` and `DEL` are called and whether`PAY` has been executed: ``` @Bean(name = "stateMachineTarget") @Scope(scopeName="prototype") public StateMachine stateMachineTarget() throws Exception { Builder builder = StateMachineBuilder.builder(); builder.configureConfiguration() .withConfiguration() .autoStartup(true); builder.configureStates() .withStates() .initial(States.HOME) .states(EnumSet.allOf(States.class)); builder.configureTransitions() .withInternal() .source(States.ITEMS).event(Events.ADD) .action(addAction()) .and() .withInternal() .source(States.CART).event(Events.DEL) .action(delAction()) .and() .withInternal() .source(States.PAYMENT).event(Events.PAY) .action(payAction()) .and() .withExternal() .source(States.HOME).target(States.ITEMS) .action(pageviewAction()) .event(Events.VIEW_I) .and() .withExternal() .source(States.CART).target(States.ITEMS) .action(pageviewAction()) .event(Events.VIEW_I) .and() .withExternal() .source(States.ITEMS).target(States.CART) .action(pageviewAction()) .event(Events.VIEW_C) .and() .withExternal() .source(States.PAYMENT).target(States.CART) .action(pageviewAction()) .event(Events.VIEW_C) .and() .withExternal() .source(States.CART).target(States.PAYMENT) .action(pageviewAction()) .event(Events.VIEW_P) .and() .withExternal() .source(States.ITEMS).target(States.HOME) .action(resetAction()) .event(Events.RESET) .and() .withExternal() .source(States.CART).target(States.HOME) .action(resetAction()) .event(Events.RESET) .and() .withExternal() .source(States.PAYMENT).target(States.HOME) .action(resetAction()) .event(Events.RESET); return builder.build(); } ``` Do not focus on `stateMachineTarget` or`@Scope` for now, as we explain those later in this section. We set up a `RedisConnectionFactory` that defaults to localhost and default port. We use `StateMachinePersist` with a`RepositoryStateMachinePersist` implementation. Finally, we create a`RedisStateMachinePersister` that uses a previously created `StateMachinePersist` bean. These are then used in a `Controller` that handles `REST` calls, as the following listing shows: ``` @Bean public RedisConnectionFactory redisConnectionFactory() { return new JedisConnectionFactory(); } @Bean public StateMachinePersist stateMachinePersist(RedisConnectionFactory connectionFactory) { RedisStateMachineContextRepository repository = new RedisStateMachineContextRepository(connectionFactory); return new RepositoryStateMachinePersist(repository); } @Bean public RedisStateMachinePersister redisStateMachinePersister( StateMachinePersist stateMachinePersist) { return new RedisStateMachinePersister(stateMachinePersist); } ``` We create a bean named `stateMachineTarget`. State machine instantiation is a relatively expensive operation, so it is better to try to pool instances instead of instantiating a new instance for every request. To do so, we first create a `poolTargetSource` that wraps `stateMachineTarget` and pools it with a max size of three. When then proxy this `poolTargetSource` with`ProxyFactoryBean` by using a `request` scope. Effectively, this means that every `REST` request gets a pooled state machine instance from a bean factory. Later, we show how these instances are used. The following listing shows how we create the `ProxyFactoryBean`and set the target source: ``` @Bean @Scope(value = "request", proxyMode = ScopedProxyMode.TARGET_CLASS) public ProxyFactoryBean stateMachine() { ProxyFactoryBean pfb = new ProxyFactoryBean(); pfb.setTargetSource(poolTargetSource()); return pfb; } ``` The following listing shows we set the maximum size and set the target bean name: ``` @Bean public CommonsPool2TargetSource poolTargetSource() { CommonsPool2TargetSource pool = new CommonsPool2TargetSource(); pool.setMaxSize(3); pool.setTargetBeanName("stateMachineTarget"); return pool; } ``` Now we can get into actual demo. You need to have a Redis server running on localhost with default settings. Then you need to run the Boot-based sample application by running the following command: ``` # java -jar spring-statemachine-samples-eventservice-3.0.1.jar ``` In a browser, you see something like the following: sm eventservice 1 In this UI, you can use three users: `joe`, `bob`, and `dave`. Clicking a button shows the current state and the extended state. Enabling a radio button before clicking a button sends a particular event for that user. This arrangement lets you play with the UI. In our `StateMachineController`, we autowire `StateMachine` and`StateMachinePersister`. `StateMachine` is `request` scoped, so you get a new instance for each request, while `StateMachinePersist` is a normal singleton bean. The following listing autowires `StateMachine` and`StateMachinePersist`: ``` @Autowired private StateMachine stateMachine; @Autowired private StateMachinePersister stateMachinePersister; ``` In the following listing, `feedAndGetState` is used with a UI to do same things that an actual `REST` api might do: ``` @RequestMapping("/state") public String feedAndGetState(@RequestParam(value = "user", required = false) String user, @RequestParam(value = "id", required = false) Events id, Model model) throws Exception { model.addAttribute("user", user); model.addAttribute("allTypes", Events.values()); model.addAttribute("stateChartModel", stateChartModel); // we may get into this page without a user so // do nothing with a state machine if (StringUtils.hasText(user)) { resetStateMachineFromStore(user); if (id != null) { feedMachine(user, id); } model.addAttribute("states", stateMachine.getState().getIds()); model.addAttribute("extendedState", stateMachine.getExtendedState().getVariables()); } return "states"; } ``` In the following listing, `feedPageview` is a `REST` method that accepts a post with JSON content. ``` @RequestMapping(value = "/feed",method= RequestMethod.POST) @ResponseStatus(HttpStatus.OK) public void feedPageview(@RequestBody(required = true) Pageview event) throws Exception { Assert.notNull(event.getUser(), "User must be set"); Assert.notNull(event.getId(), "Id must be set"); resetStateMachineFromStore(event.getUser()); feedMachine(event.getUser(), event.getId()); } ``` In the following listing, `feedMachine` sends an event into a `StateMachine` and persists its state by using a `StateMachinePersister`: ``` private void feedMachine(String user, Events id) throws Exception { stateMachine .sendEvent(Mono.just(MessageBuilder .withPayload(id).build())) .blockLast(); stateMachinePersister.persist(stateMachine, "testprefix:" + user); } ``` The following listing shows a `resetStateMachineFromStore` that is used to restore a state machine for a particular user: ``` private StateMachine resetStateMachineFromStore(String user) throws Exception { return stateMachinePersister.restore(stateMachine, "testprefix:" + user); } ``` As you would usually send an event by using a UI, you can do the same by using `REST` calls, as the following curl command shows: ``` # curl http://localhost:8080/feed -H "Content-Type: application/json" --data '{"user":"joe","id":"VIEW_I"}' ``` At this point, you should have content in Redis with a key of`testprefix:joe`, as the following example shows: ``` $ ./redis-cli 127.0.0.1:6379> KEYS * 1) "testprefix:joe" ``` The next three images show when state for `joe` has been changed from`HOME` to `ITEMS` and when the `ADD` action has been executed. The following image the `ADD` event being sent: sm eventservice 2 Now your are still on the `ITEMS` state, and the internal transition caused the `COUNT` extended state variable to increase to `1`, as the following image shows: sm eventservice 3 Now you can run the following `curl` rest call a few times (or do it through the UI) and see the `COUNT` variable increase with every call: ``` # curl http://localhost:8080/feed -H "Content-Type: application/json" # --data '{"user":"joe","id":"ADD"}' ``` The following image shows the result of these operations: sm eventservice 4 ## Deploy The deploy example shows how you can use state machine concepts with UML modeling to provide a generic error handling state. This state machine is a relatively complex example of how you can use various features to provide a centralized error handling concept. The following image shows the deploy state machine: model deployer | |The preceding state chart was designed by using the Eclipse Papyrus Plugin
(see[Eclipse Modeling Support](#sm-papyrus)) and imported into Spring StateMachine through the resulting UML
model file. Actions and guards defined in a model are resolved
from a Spring Application Context.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| In this state machine scenario, we have two different behaviors (`DEPLOY` and `UNDEPLOY`) that user tries to execute. In the preceding state chart: * In the `DEPLOY` state, the `INSTALL` and `START` states are entered conditionally. We enter `START` directly if a product is already installed and have no need to try to `START` if install fails. * In the `UNDEPLOY` state, we enter `STOP` conditionally if the application is already running. * Conditional choices for `DEPLOY` and `UNDEPLOY` are done through a choice pseudostate within those states, and the choices are selected by guards. * We use exit point pseudostates to have a more controlled exit from the`DEPLOY` and `UNDEPLOY` states. * After exiting from `DEPLOY` and `UNDEPLOY`, we go through a junction pseudostate to choose whether to go through an `ERROR` state (if an error was added into an extended state). * Finally, we go back to the `READY` state to process new requests. Now we can get to the actual demo. Run the boot based sample application by running the following command: ``` # java -jar spring-statemachine-samples-deploy-3.0.1.jar ``` In a browser, you can see something like the following image: sm deploy 1 | |As we do not have real install, start, or stop functionality, we
simulate failures by checking the existence of particular message headers.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------| Now you can start to send events to a machine and choose various message headers to drive functionality. ## Order Shipping The order shipping example shows how you can use state machine concepts to build a simple order processing system. The following image shows a state chart that drives this order shipping sample. ![sm ordershipping 1](images/sm-ordershipping-1.png) In the preceding state chart: * The state machine enters the `WAIT_NEW_ORDER` (default) state. * The event `PLACE_ORDER` transitions into the `RECEIVE_ORDER` state and the entry action (`entryReceiveOrder`) is executed. * If the order is `OK`, the state machine goes into two regions, one handling order production and one handling user-level payment. Otherwise, the state machine goes into `CUSTOMER_ERROR`, which is a final state. * The state machine loops in a lower region to remind the user to pay until `RECEIVE_PAYMENT` is sent successfully to indicate correct payment. * Both regions go into waiting states (`WAIT_PRODUCT` and`WAIT_ORDER`), where they are joined before the parent orthogonal state (`HANDLE_ORDER`) is exited. * Finally, the state machine goes through `SHIP_ORDER` to its final state (`ORDER_SHIPPED`). The following command runs the sample: ``` # java -jar spring-statemachine-samples-ordershipping-3.0.1.jar ``` In a browser, you can see something similar to the following image. You can start by choosing a customer and an order to create a state machine. ![sm ordershipping 2](images/sm-ordershipping-2.png) The state machine for a particular order is now created and you can start to play with placing an order and sending a payment. Other settings (such as`makeProdPlan`, `produce`, and `payment`) let you control how the state machine works. The following image shows the state machine waiting for an order: ![sm ordershipping 3](images/sm-ordershipping-3.png) Finally, you can see what machine does by refreshing a page, as the following image shows: ![sm ordershipping 4](images/sm-ordershipping-4.png) ## JPA Configuration The JPA configuration example shows how you can use state machine concepts with a machine configuration kept in a database. This sample uses an embedded H2 database with an H2 Console (to ease playing with the database). This sample uses `spring-statemachine-autoconfigure` (which, by default, auto-configures the repositories and entity classes needed for JPA). Thus, you need only `@SpringBootApplication`. The following example shows the `Application` class with the `@SpringBootApplication` annotation: ``` @SpringBootApplication public class Application { public static void main(String[] args) { SpringApplication.run(Application.class, args); } } ``` The following example shows how to create a `RepositoryStateMachineModelFactory`: ``` @Configuration @EnableStateMachineFactory public static class Config extends StateMachineConfigurerAdapter { @Autowired private StateRepository stateRepository; @Autowired private TransitionRepository transitionRepository; @Override public void configure(StateMachineModelConfigurer model) throws Exception { model .withModel() .factory(modelFactory()); } @Bean public StateMachineModelFactory modelFactory() { return new RepositoryStateMachineModelFactory(stateRepository, transitionRepository); } } ``` You can use the following command to run the sample: ``` # java -jar spring-statemachine-samples-datajpa-3.0.1.jar ``` Accessing the application at `[http://localhost:8080](http://localhost:8080)` brings up a newly constructed machine for each request. You can then choose to send events to a machine. The possible events and machine configuration are updated from a database with every request. The following image shows the UI and the initial events that are created when this state machine starts: ![sm datajpa 1](images/sm-datajpa-1.png) To access the embedded console, you can use the JDBC URL (which is `jdbc:h2:mem:testdb`, if it is not already set). The following image shows the H2 console: ![sm datajpa 2](images/sm-datajpa-2.png) From the console, you can see the database tables and modify them as you wish. The following image shows the result of a simple query in the UI: ![sm datajpa 3](images/sm-datajpa-3.png) Now that you have gotten this far, you have probably wondered how those default states and transitions got populated into the database. Spring Data has a nice trick to auto-populate repositories, and we used this feature through `Jackson2RepositoryPopulatorFactoryBean`. The following example shows how we create such a bean: ``` @Bean public StateMachineJackson2RepositoryPopulatorFactoryBean jackson2RepositoryPopulatorFactoryBean() { StateMachineJackson2RepositoryPopulatorFactoryBean factoryBean = new StateMachineJackson2RepositoryPopulatorFactoryBean(); factoryBean.setResources(new Resource[]{new ClassPathResource("data.json")}); return factoryBean; } ``` The following listing shows the source of the data with which we populate the database: ``` [ { "@id": "10", "_class": "org.springframework.statemachine.data.jpa.JpaRepositoryAction", "spel": "T(System).out.println('hello exit S1')" }, { "@id": "11", "_class": "org.springframework.statemachine.data.jpa.JpaRepositoryAction", "spel": "T(System).out.println('hello entry S2')" }, { "@id": "12", "_class": "org.springframework.statemachine.data.jpa.JpaRepositoryAction", "spel": "T(System).out.println('hello state S3')" }, { "@id": "13", "_class": "org.springframework.statemachine.data.jpa.JpaRepositoryAction", "spel": "T(System).out.println('hello')" }, { "@id": "1", "_class": "org.springframework.statemachine.data.jpa.JpaRepositoryState", "initial": true, "state": "S1", "exitActions": ["10"] }, { "@id": "2", "_class": "org.springframework.statemachine.data.jpa.JpaRepositoryState", "initial": false, "state": "S2", "entryActions": ["11"] }, { "@id": "3", "_class": "org.springframework.statemachine.data.jpa.JpaRepositoryState", "initial": false, "state": "S3", "stateActions": ["12"] }, { "_class": "org.springframework.statemachine.data.jpa.JpaRepositoryTransition", "source": "1", "target": "2", "event": "E1", "kind": "EXTERNAL" }, { "_class": "org.springframework.statemachine.data.jpa.JpaRepositoryTransition", "source": "2", "target": "3", "event": "E2", "actions": ["13"] } ] ``` ## Data Persist The data persist sample shows how you can state machine concepts with a persisting machine in an external repository. This sample uses an embedded H2 database with an H2 Console (to ease playing with the database). Optionally, you can also enable Redis or MongoDB. This sample uses `spring-statemachine-autoconfigure` (which, by default, auto-configures the repositories and entity classes needed for JPA). Thus, you need only `@SpringBootApplication`. The following example shows the `Application` class with the `@SpringBootApplication` annotation: ``` @SpringBootApplication public class Application { public static void main(String[] args) { SpringApplication.run(Application.class, args); } } ``` The `StateMachineRuntimePersister` interface works on the runtime level of a `StateMachine`. Its implementation,`JpaPersistingStateMachineInterceptor`, is meant to be used with a JPA. The following listing creates a `StateMachineRuntimePersister` bean: ``` @Configuration @Profile("jpa") public static class JpaPersisterConfig { @Bean public StateMachineRuntimePersister stateMachineRuntimePersister( JpaStateMachineRepository jpaStateMachineRepository) { return new JpaPersistingStateMachineInterceptor<>(jpaStateMachineRepository); } } ``` The following example shows how you can use a very similar configuration to create a bean for MongoDB: ``` @Configuration @Profile("mongo") public static class MongoPersisterConfig { @Bean public StateMachineRuntimePersister stateMachineRuntimePersister( MongoDbStateMachineRepository jpaStateMachineRepository) { return new MongoDbPersistingStateMachineInterceptor<>(jpaStateMachineRepository); } } ``` The following example shows how you can use a very similar configuration to create a bean for Redis: ``` @Configuration @Profile("redis") public static class RedisPersisterConfig { @Bean public StateMachineRuntimePersister stateMachineRuntimePersister( RedisStateMachineRepository jpaStateMachineRepository) { return new RedisPersistingStateMachineInterceptor<>(jpaStateMachineRepository); } } ``` You can configure `StateMachine` to use runtime persistence by using the`withPersistence` configuration method. The following listing shows how to do so: ``` @Autowired private StateMachineRuntimePersister stateMachineRuntimePersister; @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withPersistence() .runtimePersister(stateMachineRuntimePersister); } ``` This sample also uses `DefaultStateMachineService`, which makes it easier to work with multiple machines. The following listing shows how to create an instance of `DefaultStateMachineService`: ``` @Bean public StateMachineService stateMachineService( StateMachineFactory stateMachineFactory, StateMachineRuntimePersister stateMachineRuntimePersister) { return new DefaultStateMachineService(stateMachineFactory, stateMachineRuntimePersister); } ``` The following listing shows the logic that drives the `StateMachineService` in this sample: ``` private synchronized StateMachine getStateMachine(String machineId) throws Exception { listener.resetMessages(); if (currentStateMachine == null) { currentStateMachine = stateMachineService.acquireStateMachine(machineId); currentStateMachine.addStateListener(listener); currentStateMachine.startReactively().block(); } else if (!ObjectUtils.nullSafeEquals(currentStateMachine.getId(), machineId)) { stateMachineService.releaseStateMachine(currentStateMachine.getId()); currentStateMachine.stopReactively().block(); currentStateMachine = stateMachineService.acquireStateMachine(machineId); currentStateMachine.addStateListener(listener); currentStateMachine.startReactively().block(); } return currentStateMachine; } ``` You can use the following command to run the sample: ``` # java -jar spring-statemachine-samples-datapersist-3.0.1.jar ``` | |By default, the `jpa` profile is enabled in `application.yml`. If you want to try
other backends, enable either the `mongo` profile or the `redis` profile.
The following commands specify which profile to use (`jpa` is the default,
but we included it for the sake of completeness):

```
# java -jar spring-statemachine-samples-datapersist-3.0.1.jar --spring.profiles.active=jpa
# java -jar spring-statemachine-samples-datapersist-3.0.1.jar --spring.profiles.active=mongo
# java -jar spring-statemachine-samples-datapersist-3.0.1.jar --spring.profiles.active=redis
```| |---|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| Accessing the application at [http://localhost:8080](http://localhost:8080) brings up a newly constructed state machine for each request, and you can choose to send events to a machine. The possible events and machine configuration are updated from a database with every request. The state machines in this sample have a simple configuration with states 'S1' to 'S6' and events 'E1' to 'E6' to transition the state machine between those states. You can use two state machine identifiers (`datajpapersist1` and`datajpapersist2`) to request a particular state machine. The following image shows the UI that lets you pick a machine and an event and that shows what happens when you do: ![sm datajpapersist 1](images/sm-datajpapersist-1.png) The sample defaults to using machine 'datajpapersist1' and goes to its initial state 'S1'. The following image shows the result of using those defaults: ![sm datajpapersist 2](images/sm-datajpapersist-2.png) If you send events `E1` and `E2` to the `datajpapersist1` state machine, its state is persisted as 'S3'. The following image shows the result of doing so: ![sm datajpapersist 3](images/sm-datajpapersist-3.png) If you then request state machine `datajpapersist1` but send no events, the state machine is restored back to its persisted state, `S3`. ## Data Multi Persist The data multi ersist sample is an extension of two other samples:[JPA Configuration](#statemachine-examples-datajpa) and [Data Persist](#statemachine-examples-datapersist). We still keep machine configuration in a database and persist into a database. However, this time, we also have a machine that contains two orthogonal regions, to show how those are persisted independently. This sample also uses an embedded H2 database with an H2 Console (to ease playing with the database). This sample uses `spring-statemachine-autoconfigure` (which, by default, auto-configures the repositories and entity classes needed for JPA). Thus, you need only `@SpringBootApplication`. The following example shows the `Application` class with the `@SpringBootApplication` annotation: ``` @SpringBootApplication public class Application { public static void main(String[] args) { SpringApplication.run(Application.class, args); } } ``` As in the other data-driven samples, we again create a `StateMachineRuntimePersister`, as the following listing shows: ``` @Bean public StateMachineRuntimePersister stateMachineRuntimePersister( JpaStateMachineRepository jpaStateMachineRepository) { return new JpaPersistingStateMachineInterceptor<>(jpaStateMachineRepository); } ``` A `StateMachineService` bean makes it easier to work with a machines. The following listing shows how to create such a bean: ``` @Bean public StateMachineService stateMachineService( StateMachineFactory stateMachineFactory, StateMachineRuntimePersister stateMachineRuntimePersister) { return new DefaultStateMachineService(stateMachineFactory, stateMachineRuntimePersister); } ``` We use JSON data to import the configuration. The following example creates a bean to do so: ``` @Bean public StateMachineJackson2RepositoryPopulatorFactoryBean jackson2RepositoryPopulatorFactoryBean() { StateMachineJackson2RepositoryPopulatorFactoryBean factoryBean = new StateMachineJackson2RepositoryPopulatorFactoryBean(); factoryBean.setResources(new Resource[] { new ClassPathResource("datajpamultipersist.json") }); return factoryBean; } ``` The following listing shows how we get a `RepositoryStateMachineModelFactory`: ``` @Configuration @EnableStateMachineFactory public static class Config extends StateMachineConfigurerAdapter { @Autowired private StateRepository stateRepository; @Autowired private TransitionRepository transitionRepository; @Autowired private StateMachineRuntimePersister stateMachineRuntimePersister; @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withPersistence() .runtimePersister(stateMachineRuntimePersister); } @Override public void configure(StateMachineModelConfigurer model) throws Exception { model .withModel() .factory(modelFactory()); } @Bean public StateMachineModelFactory modelFactory() { return new RepositoryStateMachineModelFactory(stateRepository, transitionRepository); } } ``` You can run the sample by using the following command: ``` # java -jar spring-statemachine-samples-datajpamultipersist-3.0.1.jar ``` Accessing the application at `[http://localhost:8080](http://localhost:8080)` brings up a newly constructed machine for each request and lets you send events to a machine. The possible events and the state machine configuration are updated from a database for each request. We also print out all state machine contexts and the current root machine, as the following image shows: ![sm datajpamultipersist 1](images/sm-datajpamultipersist-1.png) The state machine named `datajpamultipersist1` is a simple “flat” machine where states `S1`,`S2` and `S3` are transitioned by events `E1`, `E2`, and `E3` (respectively). However, the state machine named `datajpamultipersist2` contains two regions (`R1` and `R2`) directly under the root level. That is why this root level machine really does not have a state. We need that root level machine to host those regions. Regions `R1` and `R2` in the `datajpamultipersist2` state machine contains states`S10`, `S11`, and `S12` and `S20`, `S21`, and `S22` (respectively). Events`E10`, `E11`, and `E12` are used for region `R1` and events `E20`, `E21`, and event `E22` is used for region `R2`. The following images shows what happens when we send events `E10` and `E20` to the`datajpamultipersist2` state machine: ![sm datajpamultipersist 2](images/sm-datajpamultipersist-2.png) Regions have their own contexts with their own IDs, and the actual ID is postfixed with `#` and the region ID. As the following image shows, different regions in a database have different contexts: ![sm datajpamultipersist 3](images/sm-datajpamultipersist-3.png) ## Data JPA Persist The data persist sample shows how you can state machine concepts with a persisting machine in an external repository. This sample uses an embedded H2 database with an H2 Console (to ease playing with the database). Optionally, you can also enable Redis or MongoDB. This sample uses `spring-statemachine-autoconfigure` (which, by default, auto-configures the repositories and entity classes needed for JPA). Thus, you need only `@SpringBootApplication`. The following example shows the `Application` class with the `@SpringBootApplication` annotation: ``` @SpringBootApplication public class Application { public static void main(String[] args) { SpringApplication.run(Application.class, args); } } ``` The `StateMachineRuntimePersister` interface works on the runtime level of a `StateMachine`. Its implementation,`JpaPersistingStateMachineInterceptor`, is meant to be used with a JPA. The following listing creates a `StateMachineRuntimePersister` bean: ``` @Configuration @Profile("jpa") public static class JpaPersisterConfig { @Bean public StateMachineRuntimePersister stateMachineRuntimePersister( JpaStateMachineRepository jpaStateMachineRepository) { return new JpaPersistingStateMachineInterceptor<>(jpaStateMachineRepository); } } ``` The following example shows how you can use a very similar configuration to create a bean for MongoDB: ``` @Configuration @Profile("mongo") public static class MongoPersisterConfig { @Bean public StateMachineRuntimePersister stateMachineRuntimePersister( MongoDbStateMachineRepository jpaStateMachineRepository) { return new MongoDbPersistingStateMachineInterceptor<>(jpaStateMachineRepository); } } ``` The following example shows how you can use a very similar configuration to create a bean for Redis: ``` @Configuration @Profile("redis") public static class RedisPersisterConfig { @Bean public StateMachineRuntimePersister stateMachineRuntimePersister( RedisStateMachineRepository jpaStateMachineRepository) { return new RedisPersistingStateMachineInterceptor<>(jpaStateMachineRepository); } } ``` You can configure `StateMachine` to use runtime persistence by using the`withPersistence` configuration method. The following listing shows how to do so: ``` @Autowired private StateMachineRuntimePersister stateMachineRuntimePersister; @Override public void configure(StateMachineConfigurationConfigurer config) throws Exception { config .withPersistence() .runtimePersister(stateMachineRuntimePersister); } ``` This sample also uses `DefaultStateMachineService`, which makes it easier to work with multiple machines. The following listing shows how to create an instance of `DefaultStateMachineService`: ``` @Bean public StateMachineService stateMachineService( StateMachineFactory stateMachineFactory, StateMachineRuntimePersister stateMachineRuntimePersister) { return new DefaultStateMachineService(stateMachineFactory, stateMachineRuntimePersister); } ``` The following listing shows the logic that drives the `StateMachineService` in this sample: ``` private synchronized StateMachine getStateMachine(String machineId) throws Exception { listener.resetMessages(); if (currentStateMachine == null) { currentStateMachine = stateMachineService.acquireStateMachine(machineId); currentStateMachine.addStateListener(listener); currentStateMachine.startReactively().block(); } else if (!ObjectUtils.nullSafeEquals(currentStateMachine.getId(), machineId)) { stateMachineService.releaseStateMachine(currentStateMachine.getId()); currentStateMachine.stopReactively().block(); currentStateMachine = stateMachineService.acquireStateMachine(machineId); currentStateMachine.addStateListener(listener); currentStateMachine.startReactively().block(); } return currentStateMachine; } ``` You can use the following command to run the sample: ``` # java -jar spring-statemachine-samples-datapersist-3.0.1.jar ``` | |By default, the `jpa` profile is enabled in `application.yml`. If you want to try
other backends, enable either the `mongo` profile or the `redis` profile.
The following commands specify which profile to use (`jpa` is the default,
but we included it for the sake of completeness):

```
# java -jar spring-statemachine-samples-datapersist-3.0.1.jar --spring.profiles.active=jpa
# java -jar spring-statemachine-samples-datapersist-3.0.1.jar --spring.profiles.active=mongo
# java -jar spring-statemachine-samples-datapersist-3.0.1.jar --spring.profiles.active=redis
```| |---|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| Accessing the application at [http://localhost:8080](http://localhost:8080) brings up a newly constructed state machine for each request, and you can choose to send events to a machine. The possible events and machine configuration are updated from a database with every request. The state machines in this sample have a simple configuration with states 'S1' to 'S6' and events 'E1' to 'E6' to transition the state machine between those states. You can use two state machine identifiers (`datajpapersist1` and`datajpapersist2`) to request a particular state machine. The following image shows the UI that lets you pick a machine and an event and that shows what happens when you do: ![sm datajpapersist 1](images/sm-datajpapersist-1.png) The sample defaults to using machine 'datajpapersist1' and goes to its initial state 'S1'. The following image shows the result of using those defaults: ![sm datajpapersist 2](images/sm-datajpapersist-2.png) If you send events `E1` and `E2` to the `datajpapersist1` state machine, its state is persisted as 'S3'. The following image shows the result of doing so: ![sm datajpapersist 3](images/sm-datajpapersist-3.png) If you then request state machine `datajpapersist1` but send no events, the state machine is restored back to its persisted state, `S3`. ## Monitoring The monitoring sample shows how you can use state machine concepts to monitor state machine transitions and actions. The following listing configures the state machine that we use for this sample: ``` @Configuration @EnableStateMachine public static class Config extends StateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial("S1") .state("S2", null, (c) -> {System.out.println("hello");}) .state("S3", (c) -> {System.out.println("hello");}, null); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source("S1").target("S2").event("E1") .action((c) -> {System.out.println("hello");}) .and() .withExternal() .source("S2").target("S3").event("E2"); } } ``` You can use the following command to run the sample: ``` # java -jar spring-statemachine-samples-monitoring-3.0.1.jar ``` The following image shows the state machine’s initial state: ![sm monitoring 1](images/sm-monitoring-1.png) The following image shows the state of the state machine after we have performed some actions: ![sm monitoring 2](images/sm-monitoring-2.png) You can view metrics from Spring Boot by running the following two `curl`commands (shown with their output): ``` # curl http://localhost:8080/actuator/metrics/ssm.transition.duration { "name":"ssm.transition.duration", "measurements":[ { "statistic":"COUNT", "value":3.0 }, { "statistic":"TOTAL_TIME", "value":0.007 }, { "statistic":"MAX", "value":0.004 } ], "availableTags":[ { "tag":"transitionName", "values":[ "INITIAL_S1", "EXTERNAL_S1_S2" ] } ] } ``` ``` # curl http://localhost:8080/actuator/metrics/ssm.transition.transit { "name":"ssm.transition.transit", "measurements":[ { "statistic":"COUNT", "value":3.0 } ], "availableTags":[ { "tag":"transitionName", "values":[ "EXTERNAL_S1_S2", "INITIAL_S1" ] } ] } ``` You can also view tracing from Spring Boot by running the following `curl`command (shown with its output): ``` # curl http://localhost:8080/actuator/statemachinetrace [ { "timestamp":"2018-02-11T06:44:12.723+0000", "info":{ "duration":2, "machine":null, "transition":"EXTERNAL_S1_S2" } }, { "timestamp":"2018-02-11T06:44:12.720+0000", "info":{ "duration":0, "machine":null, "action":"demo.monitoring.StateMachineConfig$Config$$Lambda$576/[email protected]" } }, { "timestamp":"2018-02-11T06:44:12.714+0000", "info":{ "duration":1, "machine":null, "transition":"INITIAL_S1" } }, { "timestamp":"2018-02-11T06:44:09.689+0000", "info":{ "duration":4, "machine":null, "transition":"INITIAL_S1" } } ] ``` # FAQ This chapter answers the questions that Spring Statemachine users most often ask. ## State Changes How can I automatically transit to the next state? You can choose from three approaches: * Implement an action and send an appropriate event to a state machine to trigger a transition into the proper target state. * Define a deferred event within a state and, before sending an event, send another event that is deferred. Doing so causes the next appropriate state transition when it is more convenient to handle that event. * Implement a triggerless transition, which automatically causes a state transition into the next state when state is entered and its actions has been completed. ## Extended State How I can initialize variables on state machine start? An important concept in a state machine is that nothing really happens unless a trigger causes a state transition that then can fire actions. However, having said that, Spring Statemachine always has an initial transition when a state machine is started. With this initial transition, you can run a simple action that, within a `StateContext`, can do whatever it likes with extended state variables. # Appendices ## Appendix A: Support Content This appendix provides generic information about the classes and material that are used in this reference documentation. ### Classes Used in This Document The following listings show the classes used throughout this reference guide: ``` public enum States { SI,S1,S2,S3,S4,SF } ``` ``` public enum States2 { S1,S2,S3,S4,S5,SF, S2I,S21,S22,S2F, S3I,S31,S32,S3F } ``` ``` public enum States3 { S1,S2,SH, S2I,S21,S22,S2F } ``` ``` public enum Events { E1,E2,E3,E4,EF } ``` ## Appendix B: State Machine Concepts This appendix provides generial information about state machines. ### Quick Example Assuming we have states named `STATE1` and `STATE2` and events named `EVENT1` and`EVENT2`, you can define the logic of the state machine as the following image shows: statechart0 The following listings define the state machine in the preceding image: ``` public enum States { STATE1, STATE2 } public enum Events { EVENT1, EVENT2 } ``` ``` @Configuration @EnableStateMachine public class Config1 extends EnumStateMachineConfigurerAdapter { @Override public void configure(StateMachineStateConfigurer states) throws Exception { states .withStates() .initial(States.STATE1) .states(EnumSet.allOf(States.class)); } @Override public void configure(StateMachineTransitionConfigurer transitions) throws Exception { transitions .withExternal() .source(States.STATE1).target(States.STATE2) .event(Events.EVENT1) .and() .withExternal() .source(States.STATE2).target(States.STATE1) .event(Events.EVENT2); } } ``` ``` @WithStateMachine public class MyBean { @OnTransition(target = "STATE1") void toState1() { } @OnTransition(target = "STATE2") void toState2() { } } ``` ``` public class MyApp { @Autowired StateMachine stateMachine; void doSignals() { stateMachine .sendEvent(Mono.just(MessageBuilder .withPayload(Events.EVENT1).build())) .subscribe(); stateMachine .sendEvent(Mono.just(MessageBuilder .withPayload(Events.EVENT2).build())) .subscribe(); } } ``` ### Glossary **State Machine** The main entity that drives a collection of states, together with regions, transitions, and events. **State** A state models a situation during which some invariant condition holds. The state is the main entity of a state machine where state changes are driven by events. **Extended State** An extended state is a special set of variables kept in a state machine to reduce the number of needed states. **Transition** A transition is a relationship between a source state and a target state. It may be part of a compound transition, which takes the state machine from one state configuration to another, representing the complete response of the state machine to an occurrence of an event of a particular type. **Event** An entity that is sent to a state machine and then drives a various state changes. **Initial State** A special state in which the state machine starts. The initial state is always bound to a particular state machine or a region. A state machine with multiple regions may have a multiple initial states. **End State** (Also called as a final state.) A special kind of state signifying that the enclosing region is completed. If the enclosing region is directly contained in a state machine and all other regions in the state machine are also completed, the entire state machine is completed. **History State** A pseudo state that lets a state machine remember its last active state. Two types of history state exists: *shallow* (which remembers only top level state) and *deep* (which remembers active states in sub-machines). **Choice State** A pseudo state that allows for making a transition choice based on (for example) event headers or extended state variables. **Junction State** A pseudo state that is relatively similar to choice state but allows multiple incoming transitions, while choice allows only one incoming transition. **Fork State** A pseudo state that gives controlled entry into a region. **Join State** A pseudo state that gives controlled exit from a region. **Entry Point** A pseudo state that allows controlled entry into a submachine. **Exit Point** A pseudo state that allows controlled exit from a submachine. **Region** A region is an orthogonal part of either a composite state or a state machine. It contains states and transitions. **Guard** A boolean expression evaluated dynamically based on the value of extended state variables and event parameters. Guard conditions affect the behavior of a state machine by enabling actions or transitions only when they evaluate to `TRUE` and disabling them when they evaluate to `FALSE`. **Action** A action is a behavior run during the triggering of the transition. ### A State Machine Crash Course This appendix provides a generic crash course to state machine concepts. #### States A state is a model in which a state machine can be. It is always easier to describe state as a real world example rather than trying to use abstract concepts ingeneric documentation. To that end, consider a simple example of a keyboard — most of us use one every single day. If you have a full keyboard that has normal keys on the left side and the numeric keypad on the right side, you may have noticed that the numeric keypad may be in a two different states, depending on whether numlock is activated. If it is not active, pressing the number pad keys result in navigation by using arrows and so on. If the number pad is active, pressing those keys results in numbers being typed. Essentially, the number pad part of a keyboard can be in two different states. To relate state concept to programming, it means that instead of using flags, nested if/else/break clauses, or other impractical (and sometimes tortuous) logic, you can rely on state, state variables, or another interaction with a state machine. #### Pseudo States Pseudostate is a special type of state that usually introduces more higher-level logic into a state machine by either giving a state a special meaning (such as initial state). A state machine can then internally react to these states by doing various actions that are available in UML state machine concepts. ##### Initial The **Initial pseudostate** state is always needed for every single state machine, whether you have a simple one-level state machine or a more complex state machine composed of submachines or regions. The initial state defines where a state machine should go when it starts. Without it, a state machine is ill-formed. ##### End The **Terminate pseudostate** (which is also called “end state”) indicates that a particular state machine has reached its final state. Effectively, this mean that a state machine no longer processes any events and does not transit to any other state. However, in the case where submachines are regions, a state machine can restart from its terminal state. ##### Choice You can use the **Choice pseudostate** choose a dynamic conditional branch of a transition from this state. The dynamic condition is evaluated by guards so that one branch is selected. Usually a simple if/elseif/else structure is used to make sure that one branch is selected. Otherwise, the state machine might end up in a deadlock, and the configuration is ill-formed. ##### Junction The **Junction pseudostate** is functionally similar to choice, as both are implemented with if/elseif/else structures. The only real difference is that junction allows multiple incoming transitions, while choice allows only one. Thus difference is largely academic but does have some differences, such as when a state machine is designed is used with a real UI modeling framework. ##### History You can use the **History pseudostate** to remember the last active state configuration. After a state machine has exited, you can use a history state to restore a previously known configuration. There are two types of history states available: `SHALLOW` (which remembers only the active state of a state machine itself) and `DEEP` (which also remembers nested states). A history state could be implemented externally by listening state machine events, but this would soon make for very difficult logic, especially if a state machine contains complex nested structures. Letting the state machine itself handle the recording of history states makes things much simpler. The user need only create a transition into a history state, and the state machine handles the needed logic to go back to its last known recorded state. In cases where a Transition terminates on a history state when the state has not been previously entered (in other words, no prior history exists) or it had reached its end state, a transition can force the state machine to a specific substate, by using the default history mechanism. This transition originates in the history state and terminates on a specific vertex (the default history state) of the region that contains the history state. This transition is taken only if its execution leads to the history state and the state had never before been active. Otherwise, the normal history entry into the region is executed. If no default history transition is defined, the standard default entry of the region is performed. ##### Fork You can use the **Fork pseudostate** to do an explicit entry into one or more regions. The following image shows how a fork works: statechart7 The target state can be a parent state that hosts regions, which simply means that regions are activated by entering their initial states. You can also add targets directly to any state in a region, which allows more controlled entry into a state. ##### Join The **Join pseudostate** merges together several transitions that originate from different regions. It is generally used to wait and block for participating regions to get into its join target states. The following image shows how a join works: statechart8 The source state can be a parent state that hosts regions, which means that join states are the terminal states of the participating regions. You can also define source states to be any state in a region, which allows controlled exit from regions. ##### Entry Point An **Entry Point pseudostate** represents an entry point for a state machine or a composite state that provides encapsulation of the insides of the state or state machine. In each region of the state machine or composite state that owns the entry point, there is at most a single transition from the entry point to a vertex within that region. ##### Exit Point An **Exit Point pseudostate** is an exit point of a state machine or composite state that provides encapsulation of the insides of the state or state machine. Transitions that terminate on an exit point within any region of the composite state (or a state machine referenced by a submachine state) imply exiting of this composite state or submachine state (with execution of its associated exit behavior). #### Guard Conditions Guard conditions are expressions which evaluates to either `TRUE` or`FALSE`, based on extended state variables and event parameters. Guards are used with actions and transitions to dynamically choose whether a particular action or transition should be run. The various spects of guards, event parameters, and extended state variables exist to make state machine design much more simple. #### Events Event is the most-used trigger behavior to drive a state machine. There are other ways to trigger behavior in a state machine (such as a timer), but events are the ones that really let users interact with a state machine. Events are also called “signals”. They basically indicate something that can possibly alter a state machine state. #### Transitions A transition is a relationship between a source state and a target state. A switch from one state to another is a state transition caused by a trigger. ##### Internal Transition Internal transition is used when an action needs to be run without causing a state transition. In an internal transition, the source state and the target state is always the same, and it is identical with a self-transition in the absence of state entry and exit actions. ##### External versus Local Transitions In most cases, external and local transitions are functionally equivalent, except in cases where the transition happens between super and sub states. Local transitions do not cause exit and entry to a source state if the target state is a substate of a source state. Conversely, local transitions do not cause exit and entry to a target state if the target is a superstate of a source state. The following image shows the difference between local and external transitions with very simplistic super and sub states: statechart4 #### Triggers A trigger begins a transition. Triggers can be driven by either events or timers. #### Actions Actions really glue state machine state changes to a user’s own code. A state machine can run an action on various changes and on the steps in a state machine (such as entering or exiting a state) or doing a state transition. Actions usually have access to a state context, which gives running code a choice to interact with a state machine in various ways. State context exposes a whole state machine so that a user can access extended state variables, event headers (if a transition is based on an event), or an actual transition (where it is possible to see more detailed about where this state change is coming from and where it is going). #### Hierarchical State Machines The concept of a hierarchical state machine is used to simplify state design when particular states must exist together. Hierarchical states are really an innovation in UML state machines over traditional state machines, such as Mealy or Moore machines. Hierarchical states lets you define some level of abstraction (parallel to how a Java developer might define a class structure with abstract classes). For example, with a nested state machine, you can define transition on a multiple level of states (possibly with different conditions). A state machine always tries to see if the current state is able to handle an event, together with transition guard conditions. If these conditions do not evaluate to `TRUE`, the state machine merely see what the super state can handle. #### Regions Regions (which are also called as orthogonal regions) are usually viewed as exclusive OR (XOR) operations applied to states. The concept of a region in terms of a state machine is usually a little difficult to understand, but things gets a little simpler with a simple example. Some of us have a full size keyboard with the main keys on the left side and numeric keys on the right side. You have probably noticed that both sides really have their own state, which you see if you press a “numlock” key (which alters only the behaviour of the number pad itself). If you do not have a full-size keyboard, you can buy an external USB number pad. Given that the left and right side of a keyboard can each exist without the other, they must have totally different states, which means they are operating on different state machines. In state machine terms, the main part of a keyboard is one region and the number pad is another region. It would be a little inconvenient to handle two different state machines as totally separate entities, because they still work together in some fashion. This independence lets orthogonal regions combine together in multiple simultaneous states within a single state in a state machine. ## Appendix C: Distributed State Machine Technical Paper This appendix provides more detailed technical documentation about using a Zookeeper instance with Spring Statemachine. ### Abstract Introducing a “distributed state” on top of a single state machine instance running on a single JVM is a difficult and a complex topic. The concept of a “Distributed State Machine” introduces a few relatively complex problems on top of a simple state machine, due to its run-to-completion model and, more generally, because of its single-thread execution model, though orthogonal regions can be run in parallel. One other natural problem is that state machine transition execution is driven by triggers, which are either `event` or `timer` based. Spring State Machine tries to solve the problem of spanning a generic “State Machine” through a JVM boundary by supporting distributed state machines. Here we show that you can use generic “State Machine” concepts across multiple JVMs and Spring Application Contexts. We found that, if `Distributed State Machine` abstraction is carefully chosen and backing distributed state repository guarantees `CP` readiness, it is possible to create a consistent state machine that can share distributed state among other state machines in an ensemble. Our results demonstrate that distributed state changes are consistent if the backing repository is “CP” (discussed [later](#state-machine-technical-paper-introduction)). We anticipate our distributed state machine can provide a foundation to applications that need to work with shared distributed states. This model aims to provide good methods for cloud applications to have much easier ways to communicate with each other without having to explicitly build these distributed state concepts. ### Introduction Spring State Machine is not forced to use a single threaded execution model, because, once multiple regions are used, regions can be executed in parallel if the necessary configuration is applied. This is an important topic, because, once a user wants to have parallel state machine execution, it makes state changes faster for independent regions. When state changes are no longer driven by a trigger in a local JVM or a local state machine instance, transition logic needs to be controlled externally in an arbitrary persistent storage. This storage needs to have a way to notify participating state machines when distributed state is changed. [CAP Theorem](https://en.wikipedia.org/wiki/CAP_theorem) states that it is impossible for a distributed computer system to simultaneously provide all three of the following guarantees: consistency, availability, and partition tolerance. This means that, whatever is chosen for a backing persistence storage, it is advisable to be “CP”. In this context, “CP” means “consistency” and “partition tolerance”. Naturally, a distributed Spring Statemachine does not care about its “CAP” level but, in reality, “consistency” and “partition tolerance” are more important than “availability”. This is an exact reason why (for example) Zookeeper uses “CP” storage. All tests presented in this article are accomplished by running custom Jepsen tests in the following environment: * A cluster having nodes n1, n2, n3, n4 and n5. * Each node has a `Zookeeper` instance that constructs an ensemble with all other nodes. * Each node has a [Web](#statemachine-examples-web) sample installed, to connect to a local `Zookeeper` node. * Every state machine instance communicates only with a local`Zookeeper` instance. While connecting a machine to multiple instances is possible, it is not used here. * All state machine instances, when started, create a`StateMachineEnsemble` by using a Zookeeper ensemble. * Each sample contains a custom rest API, which Jepsen uses to send events and check particular state machine statuses. All Jepsen tests for `Spring Distributed Statemachine` are available from[Jepsen Tests.](https://github.com/spring-projects/spring-statemachine/tree/master/jepsen/spring-statemachine-jepsen) ### Generic Concepts One design decision of a `Distributed State Machine` was not to make each individual state machine instance be aware that it is part of a “distributed ensemble”. Because the main functions and features of a`StateMachine` can be accessed through its interface, it makes sense to wrap this instance in a `DistributedStateMachine`, which intercepts all state machine communication and collaborates with an ensemble to orchestrate distributed state changes. One other important concept is to be able to persist enough information from a state machine to reset a state machine state from an arbitrary state into a new deserialized state. This is naturally needed when a new state machine instance joins with an ensemble and needs to synchronize its own internal state with a distributed state. Together with using concepts of distributed states and state persisting, it is possible to create a distributed state machine. Currently, the only backing repository of a `Distributed State Machine` is implemented by using Zookeeper. As mentioned in [Using Distributed States](#sm-distributed), distributed states are enabled by wrapping an instance of a `StateMachine` in a`DistributedStateMachine`. The specific `StateMachineEnsemble`implementation is `ZookeeperStateMachineEnsemble` provides integration with Zookeeper. ### The Role of `ZookeeperStateMachinePersist` We wanted to have a generic interface (`StateMachinePersist`) that Can persist `StateMachineContext` into arbitrary storage and`ZookeeperStateMachinePersist` implements this interface for`Zookeeper`. ### The Role of `ZookeeperStateMachineEnsemble` While a distributed state machine uses one set of serialized contexts to update its own state, with zookeeper, we have a conceptual problem around how to listen to these context changes. We can serialize context into a zookeeper `znode` and eventually listen when the `znode` data is modified. However, `Zookeeper` does not guarantee that you get a notification for every data change, because a registered `watcher` for a `znode` is disabled once it fires and the user need to re-register that `watcher`. During this short time, a `znode` data can be changed, thus resulting in missing events. It is actually very easy to miss these events by changing data from multiple threads in a concurrent manner. To overcome this issue, we keep individual context changes in multiple `znodes` and we use a simple integer counter to mark which `znode` is the current active one. Doing so lets us replay missed events. We do not want to create more and more znodes and then later delete old ones. Instead, we use the simple concept of a circular set of znodes. This lets us use a predefined set of znodes where the current node can be determined with a simple integer counter. We already have this counter by tracking the main `znode` data version (which, in`Zookeeper`, is an integer). The size of a circular buffer is mandated to be a power of two, to avoid trouble when the integer goes to overflow. For this reason, we need not handle any specific cases. ### Distributed Tolerance To show how a various distributed actions against a state machine work in real life, we use a set of Jepsen tests to simulate various conditions that might happen in a real distributed cluster. These include a “brain split” on a network level, parallel events with multiple “distributed state machines”, and changes in “extended state variables”. Jepsen tests are based on a sample[Web](#statemachine-examples-web), where this sample instance runs on multiple hosts together with a Zookeeper instance on every node where the state machine is run. Essentially, every state machine sample connects to a local Zookeeper instance, which lets us, by using Jepsen, to simulate network conditions. The plotted graphs shown later in this chapter contain states and events that directly map to a state chart, which you can be find in[Web](#statemachine-examples-web). #### Isolated Events Sending an isolated single event into exactly one state machine in an ensemble is the simplest testing scenario and demonstrates that a state change in one state machine is properly propagated into other state machines in an ensemble. In this test, we demonstrate that a state change in one machine eventually causes a consistent state change in other machines. The following image shows the events and state changes for a test state machine: sm tech isolated events In the preceding image: * All machines report state `S21`. * Event `I` is sent to node `n1` and all nodes report state change from `S21` to `S22`. * Event `C` is sent to node `n2` and all nodes report state change from `S22` to `S211`. * Event `I` is sent to node `n5` and all nodes report state change from `S211` to `S212`. * Event `K` is sent to node `n3` and all nodes report state change from `S212` to `S21`. * We cycle events `I`, `C`, `I`, and `K` one more time, through random nodes. #### Parallel Events One logical problem with multiple distributed state machines is that, if the same event is sent into multiple state machines at exactly the same time, only one of those events causes a distributed state transitions. This is a somewhat expected scenario, because the first state machine (for this event) that is able to change a distributed state controls the distributed transition logic. Effectively, all other machines that receive this same event silently discard the event, because the distributed state is no longer in a state where a particular event can be processed. In the test shown in the following image, we demonstrate that a state change caused by a parallel event throughout an ensemble eventually causes a consistent state change in all machines: sm tech parallel events In the preceding image, we use the same event flow that we used in the previous sample ([Isolated Events](#sm-tech-isolated-events)), with the difference that events are always sent to all nodes. #### Concurrent Extended State Variable Changes Extended state machine variables are not guaranteed to be atomic at any given time, but, after a distributed state change, all state machines in an ensemble should have a synchronized extended state. In this test, we demonstrate that a change in extended state variables in one distributed state machine eventually becomes consistent in all the distributed state machines. The following image shows this test: sm tech isolated events with variable In the preceding image: * Event `J` is send to node `n5` with event variable `testVariable`having value `v1`. All nodes then report having a variable named`testVariable` with a value of `v1`. * Event `J` is repeated from variable `v2` to `v8`, doing the same checks. #### Partition Tolerance We need to always assume that, sooner or later, things in a cluster go bad, whether it is a crash of a Zookeeper instance, a state machine crash, or a network problem such as a “brain split”. (A brain split is a situation where existing cluster members are isolated so that only parts of hosts are able to see each other). The usual scenario is that a brain split creates minority and majority partitions of an ensemble such that hosts in the minority cannot participate in an ensemble until the network status has been healed. In the following tests, we demonstrate that various types of brain split in an ensemble eventually cause a fully synchronized state of all the distributed state machines. There are two scenarios that have a straight brain split in a network where where `Zookeeper` and `Statemachine` instances are split in half (assuming each `Statemachine` connects to a local `Zookeeper` instance): * If the current zookeeper leader is kept in a majority, all clients connected to the majority keep functioning properly. * If the current zookeeper leader is left in the minority, all clients disconnect from it and try to connect back till previous minority members have successfully joined back to existing majority ensemble. | |In our current Jepsen tests, we cannot separate Zookeeper split-brain
scenarios between the leader being left in the majority or in the minority, so we need to
run the tests multiple times to accomplish this situation.| |---|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | |In the following plots, we have mapped a state machine error state into an`error` to indicate that the state machine is in an error state instead of
a normal state. Please remember this when interpreting chart states.| |---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| In this first test, we show that, when an existing Zookeeper leader was kept in the majority, three out of five machines continue as is. The following image shows this test: sm tech partition half 1 In the preceding image: * The first event, `C`, is sent to all machines, leading a state change to`S211`. * Jepsen nemesis causes a brain split, which causes partitions of `n1/n2/n5` and `n3/n4`. Nodes `n3/n4` are left in the minority, and nodes `n1/n2/n5` construct a new healthy majority. Nodes in the majority keep functioning without problems, but nodes in the minority go into error states. * Jepsen heals the network and, after some time, nodes `n3/n4` join back into the ensemble and synchronize its distributed status. * Finally, event `K1` is sent to all state machines to ensure that the ensemble is working properly. This state change leads back to state`S21`. In the second test, we show that, when the existing zookeeper leader was kept in the minority, all machines error out. The following image shows the second test: sm tech partition half 2 In the preceding image: * The first event, `C`, is sent to all machines leading to a state change to`S211`. * Jepsen nemesis causes a brain split, which causes partitions such that the existing `Zookeeper` leader is kept in the minority and all instances are disconnected from the ensemble. * Jepsen heals the network and, after some time, all nodes join back into the ensemble and synchronize its distributed status. * Finally, event `K1` is sent to all state machines to ensure that ensemble workS properly. This state change leads back to state`S21`. #### Crash and Join Tolerance In this test, we demonstrate that killing an existing state machine and then joining a new instance back into an ensemble keeps the distributed state healthy and the newly joined state machines synchronize their states properly. The following image shows the crash and join tolerance test: sm tech stop start | |In this test, states are not checked between first the `X` and last the `X`.
Thus, the graph shows a flat line in between. The states are checked
exactly where the state change happens between `S21` and `S211`.| |---|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| In the preceding image: * All state machines are transitioned from the initial state (`S21`) into state `S211` so that we can test proper state synchronize during the join. * `X` marks when a specific node has been crashed and started. * At the same time, we request states from all machines and plot the result. * Finally, we do a simple transition back to `S21` from `S211` to make sure that all state machines still function properly. ## Developer Documentation This appendix provides generic information for adevelopers who may want to contribute or other people who want to understand how state machine works or understand its internal concepts. ### StateMachine Config Model `StateMachineModel` and other related SPI classes are an abstraction between various configuration and factory classes. This also allows easier integration for others to build state machines. As the following listing shows, you can instantiate a state machine by building a model with configuration data classes and then asking a factory to build a state machine: ``` // setup configuration data ConfigurationData configurationData = new ConfigurationData<>(); // setup states data Collection> stateData = new ArrayList<>(); stateData.add(new StateData("S1", true)); stateData.add(new StateData("S2")); StatesData statesData = new StatesData<>(stateData); // setup transitions data Collection> transitionData = new ArrayList<>(); transitionData.add(new TransitionData("S1", "S2", "E1")); TransitionsData transitionsData = new TransitionsData<>(transitionData); // setup model StateMachineModel stateMachineModel = new DefaultStateMachineModel<>(configurationData, statesData, transitionsData); // instantiate machine via factory ObjectStateMachineFactory factory = new ObjectStateMachineFactory<>(stateMachineModel); StateMachine stateMachine = factory.getStateMachine(); ``` ## Appendix D: Reactor Migration Guide Main task for a work for `3.x` has been to both internally and externally to move and change as much as we can from imperative code into a reactive world. This means that some of a main interfaces has added a new reative methods and most of a internal execution locig (where applicable) has been moved over to handled by a reactor. Essentially what this means is that thread handling model is considerably different compared to `2.x`. Following chapters go throught all these changes. ### Communicating with a Machine We’ve added new reactive methods to `StateMachine` while still keeping old blocking event methods in place. ``` Flux> sendEvent(Mono> event); Flux> sendEvents(Flux> events); Mono>> sendEventCollect(Mono> event); ``` We’re now solely working on a spring `Message` and reactor `Mono` and `Flux` classes. You can send a `Mono` of a `Message` and receive back a `Flux` of `StateMachineEventResult`. Remember that nothing happens until you subscribe to this `Flux`. More about this returned value, see [StateMachineEventResult](#sm-triggers-statemachineeventresult). Method `sendEventCollect`is just a syntactic sugar to pass in a `Mono` and get a `Mono` which wraps results as a list. ``` Message message = MessageBuilder.withPayload("EVENT").build(); machine.sendEvent(Mono.just(message)).subscribe(); ``` You can also send a `Flux` of messages instead of a single `Mono` message. ``` machine.sendEvents(Flux.just(message)).subscribe(); ``` All of the reactor methods are on your disposal and for example not to block and do something when event handling is completed, you could do something like. ``` Mono> mono = Mono.just(MessageBuilder.withPayload("EVENT").build()); machine.sendEvent(mono) .doOnComplete(() -> { System.out.println("Event handling complete"); }) .subscribe(); ``` Old API methods returning a `boolean` for accepted status are still in place but are deprecated to get removed in future releases. ``` boolean accepted = machine.sendEvent("EVENT"); ``` ### TaskExecutor and TaskScheduler StateMachine execution with `TaskExecutor` and state action scheduling with `TaskScheduler`has been fully replaced in favour or Reactor execution and scheduling. Essentially execution outside of a main thread is needed in two places, firstly with*State Actions* which needs to be cancellable and secondly with *Regions* which should be always be executed independently. Currently we’ve chosen to just use *Reactor*`Schedulers.parallel()` for these which should give relatively good results as it tries to automatically use available number of cpu cores from a system. ### Reactive Examples While most of an examples are still same, we’ve overhauled some of them and created some new: * Tunrstile Reactive [Turnstile Reactive](#statemachine-examples-turnstilereactive)