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//! Automafish DFA builder //! ====================== //! **Makes state machines that do things** //! //! Automafish can be used to optimize state machines defined through states and overlapping //! transitions into more effective-to-evaluate deterministic forms. //! //! In technical terms Automafish takes [nondeterministic] [Moore machines] and creates a //! [deterministic state machine] for it through [powerset construction]. //! //! [deterministic state machine]: https://en.wikipedia.org/wiki/Deterministic_finite_automaton //! [nondeterministic]: https://en.wikipedia.org/wiki/Nondeterministic_finite_automaton //! [Moore machines]: https://en.wikipedia.org/wiki/Moore_machine //! [powerset construction]: https://en.wikipedia.org/wiki/Powerset_construction //! //! # Example //! //! ``` //! # // Update README when changing the example here. //! # env_logger::init(); //! use std::iter::FromIterator; //! use automafish::{Builder, State, Transition, Criteria, Condition}; //! //! let mut builder : Builder<Condition<char>, &mut dyn FnMut(&mut char)> = Builder::new(); //! //! // Set up an automata that capitalizes first character of a word. //! let mut upper_case = |mut c: &mut char| { c.make_ascii_uppercase(); }; //! let wait_not_space = builder.create_initial_state(); //! let first_not_space = builder.add_state(State::with_action(&mut upper_case)); //! let wait_for_space = builder.add_state(State::new()); //! //! builder.add_transition(Transition::new( //! wait_not_space, Condition::Is(vec![' ']), wait_not_space)); //! builder.add_transition(Transition::new( //! wait_not_space, Condition::Not(vec![' ']), first_not_space)); //! builder.add_transition(Transition::new( //! first_not_space, Condition::Not(vec![' ']), wait_for_space)); //! builder.add_transition(Transition::new( //! first_not_space, Condition::Is(vec![' ']), wait_not_space)); //! builder.add_transition(Transition::new( //! wait_for_space, Condition::Not(vec![' ']), wait_for_space)); //! builder.add_transition(Transition::new( //! wait_for_space, Condition::Is(vec![' ']), wait_not_space)); //! //! // Set up an automata that counts all exclamation marks. //! // This automata modifies a value outside the state machine. //! let mut exclamations = 0; //! let mut exclamation_counter = |_: &mut char| { exclamations += 1; }; //! let wait_exclamation = builder.create_initial_state(); //! let exclamation = builder.add_state(State::with_action(&mut exclamation_counter)); //! //! builder.add_transition(Transition::new( //! wait_exclamation, Condition::Any, wait_exclamation)); //! builder.add_transition(Transition::new( //! wait_exclamation, Condition::Is(vec!['!']), exclamation)); //! //! // Build the machine. //! let mut machine = builder.build(); //! //! // Execute the machine on an input string. //! let mut current_state = machine.start(); //! let mut input : Vec<char> = "hello world! this is rust!".chars().collect(); //! for i in &mut input { //! current_state = machine.step_and_execute_mut(current_state, i); //! } //! //! let output : String = String::from_iter(input); //! //! assert_eq!("Hello World! This Is Rust!", output); //! assert_eq!(2, exclamations); //! ``` #![warn(missing_docs)] use std::collections::{BTreeMap, BTreeSet, HashMap, HashSet}; use std::hash::Hash; use std::sync::atomic::{AtomicUsize, Ordering}; static ID_COUNTER: AtomicUsize = AtomicUsize::new(1); mod refs { use super::*; use std::ops::{Index, IndexMut}; macro_rules! ImplIndex { (<$($generics:tt),*> $idx_ty:ty => $target_ty:ty) => { ImplIndex! { @ ($($generics),*) $idx_ty => $target_ty } }; ($idx_ty:ty => $target_ty:ty) => { ImplIndex! { @ () $idx_ty => $target_ty } }; ( @ ($($generics:tt),*) $idx_ty:ty => $target_ty:ty) => { impl<$($generics),*> Index<$idx_ty> for Vec<$target_ty> { type Output = $target_ty; fn index(&self, idx: $idx_ty) -> &Self::Output { &self[idx.idx] } } impl<$($generics),*> IndexMut<$idx_ty> for Vec<$target_ty> { fn index_mut(&mut self, idx: $idx_ty) -> &mut Self::Output { &mut self[idx.idx] } } impl $idx_ty { #[allow(dead_code)] pub(super) fn new_unchecked(m: usize, idx: usize) -> Self { Self { m, idx } } #[allow(dead_code)] pub(super) fn next_ref<$($generics),*>(m: usize, v: &[$target_ty]) -> Self { Self { m, idx: v.len() } } #[allow(dead_code)] pub(crate) fn uninit() -> Self { Self { m: usize::MAX, idx: usize::MAX } } #[allow(dead_code)] pub(crate) fn assert_same_machine(&self, other: Self) { if self.m != other.m { panic!("Incompatible machine") } } #[allow(dead_code)] pub(crate) fn assert_machine(&self, m: usize) { if self.m != m { panic!("Wrong machine") } } } impl std::fmt::Debug for $idx_ty { fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { f.debug_struct(stringify!($idx_ty)) .field("#", &self.idx) .finish() } } }; } #[derive(Clone, Copy, PartialEq, Eq, Hash, PartialOrd, Ord)] pub struct MachineState { m: usize, idx: usize, } #[derive(Clone, Copy, PartialEq, Eq, Hash, PartialOrd, Ord)] pub struct StateRef { m: usize, idx: usize, } #[derive(Clone, Copy, PartialEq, Eq, Hash, PartialOrd, Ord)] pub struct TransitionRef { m: usize, idx: usize, } #[derive(Clone, Copy, PartialEq, Eq, Hash, PartialOrd, Ord)] pub(super) struct ActionRef { m: usize, idx: usize, } #[derive(Clone, Copy, PartialEq, Eq, Hash, PartialOrd, Ord)] pub(super) struct MixedTransitionRef { m: usize, idx: usize, } #[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)] pub(super) struct MixedStateKey(BTreeSet<StateRef>); impl MixedStateKey { pub fn new<I>(i: I) -> Self where I: IntoIterator<Item = StateRef>, { use std::iter::FromIterator; Self(BTreeSet::from_iter(i)) } pub fn empty() -> Self { Self(BTreeSet::new()) } pub fn is_empty(&self) -> bool { self.0.is_empty() } pub fn extend(&mut self, new: MixedStateKey) { self.0.extend(new.0); } pub fn add(&mut self, new: StateRef) { self.0.insert(new); } } impl<'a> IntoIterator for &'a MixedStateKey { type Item = &'a StateRef; type IntoIter = <&'a BTreeSet<StateRef> as IntoIterator>::IntoIter; fn into_iter(self) -> Self::IntoIter { (&self.0).iter() } } ImplIndex! { <C> MachineState => FinalState<C> } ImplIndex! { <T> StateRef => State<T> } ImplIndex! { <T> TransitionRef => Transition<T> } ImplIndex! { <T> ActionRef => T } ImplIndex! { <T> MixedTransitionRef => MixedTransition<T> } } use refs::{ActionRef, MachineState, MixedStateKey, StateRef, TransitionRef}; /// A compiled state machine. /// /// The `StateMachine` can be created with the [`Builder`]. #[derive(Debug)] pub struct StateMachine<TCriteria, TAction> { machine_id: usize, initial_state: MachineState, actions: Vec<TAction>, states: Vec<FinalState<TCriteria>>, } #[derive(Debug)] struct FinalState<TCriteria> { actions: Vec<ActionRef>, transitions: Vec<(TCriteria, MachineState)>, } /// A state machine state. /// /// `State` is used to define possible states when building a [`StateMachine`] /// with a [`Builder`]. Each state may contain actions that are executed when /// the state is reached. #[derive(Debug)] pub struct State<TAction> { self_ref: StateRef, actions: Vec<TAction>, transitions: Vec<TransitionRef>, } #[derive(Debug)] struct MixedState<TCriteria> { states: MixedStateKey, transitions: Vec<MixedTransition<TCriteria>>, } /// A state machine transition. /// /// `Transition` is used to define possible transition between different [`State`]. The transitions /// are triggered based on some [`Criteria`] when the state machine is being executed. #[derive(Debug)] pub struct Transition<TCriteria> { source: StateRef, target: StateRef, criteria: TCriteria, } /// A state machine builder. /// /// The `Builder` allows defining the state machine as a [Nondeterministic Finite Automaton] using /// [`Self::add_state`] and [`Self::add_transition`] methods. Once the state machine is described in such a way /// the final [`StateMachine`] can be built with the [`Self::build`] method. /// /// [Nondeterministic Finite Automaton]: https://en.wikipedia.org/wiki/Nondeterministic_finite_automaton #[derive(Debug)] pub struct Builder<TCriteria, TAction> { machine_id: usize, initial_states: Vec<StateRef>, states: Vec<State<TAction>>, transitions: Vec<Transition<TCriteria>>, } #[derive(Debug, Clone, PartialEq, Eq, Hash)] struct MixedTransition<TCriteria> { criteria: TCriteria, source: MixedStateKey, target: MixedStateKey, } /// A trait defining transition criteria. /// /// The criteria defines a condition that the [`StateMachine`] input needs to /// match for a specific state transition to occur. The input type of the state /// machine is indirectly defined by the [`Self::Input`] of the state machine criteria. pub trait Criteria: Clone + PartialEq + Eq + Hash { /// Input type for the state machien criteria. type Input; /// Checks whether a given input is a match for a specific criteria. fn is_match(&self, input: &Self::Input) -> bool; /// Checks if the `Criteria` represents an empty criteria that doesn't match any input. /// /// Recognizing empty `Criteria` allows the [`Builder`] to simplify the final [`StateMachine`]. /// Returning `false` in case the `Criteria` _is_ empty does not break the actual state /// processing, but will result in extra states and state transitions being included in the /// final `StateMachine`. fn is_empty(&self) -> bool; /// The evaluation order of the `Criteria` defines the order in which the state transitiosn are /// evaluated. Criteria with smaller evaluation order is processed first. /// /// This allows some leeway in how accurate the [`Self::and`] and [`Self::not`] implementations are. See /// [`Self::not`] for more details. fn evaluation_order(&self) -> usize { 0 } /// Combines two `Criteria` together. /// /// The [`Builder`] will use this method when calculating state transitions in the final /// [`StateMachine`] between deterministic states representing several nondeterministic states /// defined in the [`Builder`]. /// /// The `Builder` will only invoke this method with `other` being a criteria defined in the /// _original_ state transitions by hand. An output of `and` or `not` is never used as the /// `other` parameter. /// /// # Example /// /// ``` /// # use std::collections::BTreeSet; /// # use automafish::Criteria; /// # use std::hash::Hash; /// #[derive(Clone, PartialEq, Eq, Hash)] /// struct OneOf(BTreeSet<u32>); /// impl Criteria for OneOf { /// # type Input = u32; /// # fn is_match(&self, input: &Self::Input) -> bool { self.0.contains(input) } /// # fn is_empty(&self) -> bool { false } /// # fn not(&self, other: &Self) -> Self { unimplemented!() } /// # fn any() -> Self { unimplemented!() } /// fn and(&self, other: &Self) -> Self { /// OneOf(self.0.intersection(&other.0).copied().collect()) /// } /// /// // ... rest of the required methods. /// } /// /// let small = OneOf(vec![ 1, 2, 3, 4 ].into_iter().collect()); /// let even = OneOf(vec![ 2, 4, 6, 8 ].into_iter().collect()); /// /// let small_and_even = small.and(&even); /// /// let input = 4; /// assert_eq!( /// small.is_match(&input) && even.is_match(&input), /// small_and_even.is_match(&input)); /// ``` fn and(&self, other: &Self) -> Self; /// Calculates a difference criteria that matches `self` but not `other`. /// /// The [`Builder`] will use this method when calculating state transitions in the final /// [`StateMachine`] between deterministic states representing several nondeterministic states /// defined in the [`Builder`]. /// /// The `Builder` will only invoke this method with `other` being a criteria defined in the /// _original_ state transitions by hand. An output of `and` or `not` is never used as the /// `other` parameter. /// /// This allows for some simplification in the resulting state. The `Builder` asking for /// criteria such as `a.not(b)` occurs in a situation where there is criteria `b` in some state /// transition that should take priority over the one for which the `a.not(b)` criteria /// applies. This means that as long as `a.not(b)` criteria has a lower evaluation order, it's /// perfectly valid to return `a` as a result of that `not` operation. An example of this would /// be the [`Self::any`] state, which can be returned as is, as long as it has the lowest evaluation /// order. fn not(&self, other: &Self) -> Self; /// A default criteria that matches everything. /// /// In general this criteria shouldn't be used for `is_match` unless it appears explicitly in /// the user-specified [`Transition`] definitions. Instead the any-state is used as a building /// block when the [`Builder`] constructs the final transitions for the resulting deterministic /// finite automaton. The final states are `any()` combined with one or more `and(..)` and zero /// or more `not(..)`. fn any() -> Self; } /// Action that may be executed when entering a state. /// /// See [`ActionMut`] if you need an action that may mutate its internal state. The `Action` is /// implemented for `Box<Fn(T)>` by default. pub trait Action { /// Input type for the action. type Input; /// Perform the action in the input. /// /// Note that the `input` takes the input type as a reference to allow multiple actions to be /// executed on it if necessary. This doesn't prevent mutating the input though, since the /// `Input` itself can be defined as `&mut Foo`. /// /// # Examples /// /// ``` /// # use automafish::Action; /// struct IncrementValue; /// impl Action for IncrementValue { /// type Input = u32; /// fn execute(&self, input: &mut Self::Input) { /// *input += 1; /// } /// } /// ``` fn execute(&self, input: &mut Self::Input); } /// Action that may be executed when entering a state and may mutate its inner state. /// /// The `ActionMut` is implemented for `Box<FnMut(T)>` by default. pub trait ActionMut { /// Input type for the action. type Input; /// Perform the action in the input. /// /// Note that the `input` takes the input type as a reference to allow multiple actions to be /// executed on it if necessary. This doesn't prevent mutating the input though, since the /// `Input` itself can be defined as `&mut Foo`. /// /// # Examples /// /// ``` /// # use automafish::ActionMut; /// struct IncrementValue<'a> { buffer: &'a mut Vec<u32> } /// impl<'a> ActionMut for IncrementValue<'a> { /// type Input = u32; /// fn execute_mut(&mut self, input: &mut Self::Input) { /// self.buffer.push(*input); /// } /// } /// ``` fn execute_mut(&mut self, input: &mut Self::Input); } impl<TCriteria, TAction> Builder<TCriteria, TAction> where TCriteria: Criteria, { /// Create a new `Builder` pub fn new() -> Self { Self { machine_id: ID_COUNTER.fetch_add(1, Ordering::Relaxed), initial_states: vec![], states: vec![], transitions: vec![], } } /// Create a new initial state. /// /// Each initial state is unique in regards to their transitions. Multiple initial states may /// be used to separate automata that might have different transitions to their initial states. pub fn create_initial_state(&mut self) -> StateRef { let state_ref = StateRef::next_ref(self.machine_id, &self.states); self.states.push(State::new()); self.initial_states.push(state_ref); state_ref } /// Add a new state to the builder. pub fn add_state(&mut self, state: State<TAction>) -> StateRef { let mut state = state; state.self_ref = StateRef::next_ref(self.machine_id, &self.states); let state_ref = state.self_ref; self.states.push(state); state_ref } /// Add a new transition between builder states. pub fn add_transition(&mut self, transition: Transition<TCriteria>) { transition.source.assert_machine(self.machine_id); let transition_ref = TransitionRef::next_ref(self.machine_id, &self.transitions); let source = &mut self.states[transition.source]; source.transitions.push(transition_ref); self.transitions.push(transition); } /// Consume the builder, returning a final [`StateMachine`]. pub fn build(self) -> StateMachine<TCriteria, TAction> { // Diagnostic information on the original NFA state counts. let nfa_state_count = self.states.len(); let nfa_transition_count = self.transitions.len(); // Start a collection of all states. let mut all_states: BTreeMap<MixedStateKey, MixedState<TCriteria>> = BTreeMap::new(); // Insert the initial state to the queue to get things started. let initial_state_key = MixedStateKey::new(self.initial_states); let mut processing_queue = vec![initial_state_key.clone()]; all_states.insert( initial_state_key.clone(), MixedState { states: initial_state_key.clone(), transitions: vec![], }, ); // We'll need to keep processing items in the queue until we run out of items to process. // Each step might add multiple new states to the processing_queue, but at some point we // should stop encountering new states as there's only so many possible NFA state // combinations we can get (although that number is 2^n, where n is the original NFA state // count). let mut processing_cursor = 0; while processing_cursor < processing_queue.len() { let current_key = processing_queue[processing_cursor].clone(); log::trace!("Processing state {:?}", current_key); // Create all expanded transitions. // // We'll start with a dummy any-transition just to bootstrap the `expand_transitions` // algorithm that uses the existing transitions as the base. Normally this dummy // transition is stopped later since it has no target states - unless of course one of // the user specified transitions is a `any()` transition. let mut expanded_transitions = vec![MixedTransition { criteria: TCriteria::any(), source: current_key.clone(), target: MixedStateKey::empty(), }]; // Construct the transitions by iterating all the possible transitions from the states // represented by this `MixedState`. for o_ref in ¤t_key { let original = &self.states[*o_ref]; for t_ref in &original.transitions { let transition = &self.transitions[*t_ref]; expand_transitions(&mut expanded_transitions, transition); } } // Merge transitions that use the same criteria. The expansion above might have // resulted in multiple equal criteria through different means (A - B and A - C, when // A, B and C don't overlap). Here we ensure that such transitions result in a combined // mixed state. let mut expanded_transitions_map = HashMap::new(); for t in expanded_transitions { let entry = expanded_transitions_map .entry(t.criteria.clone()) .or_insert(MixedTransition { criteria: t.criteria, source: current_key.clone(), target: MixedStateKey::empty(), }); entry.target.extend(t.target); } // Drop the transitions that have empty criteria or targets. let expanded_transitions: Vec<_> = expanded_transitions_map .into_iter() .map(|(_, t)| t) .filter(|t| !t.criteria.is_empty() && !t.target.is_empty()) .collect(); // Now that we have all the possible transitions, we'll need to see if // we found any new target states. These are added to the end of the processing queue // so we'll process them in the future. // // Unless there's a bug somewhere, at some point we'll start exhausting the list of // possible target states and stop adding new ones here, allowing the remaining // processing backlog to run out and this while-loop to terminate. for t in &expanded_transitions { if all_states.contains_key(&t.target) { continue; } // Encountered a state that isn't in the queue yet. all_states.insert( t.target.clone(), MixedState { states: t.target.clone(), transitions: vec![], }, ); processing_queue.push(t.target.clone()); } all_states.get_mut(¤t_key).unwrap().transitions = expanded_transitions; processing_cursor += 1; } // All states have been processed. Now we'll just need to construct the final state // machine. let mut machine = StateMachine::<TCriteria, TAction> { machine_id: ID_COUNTER.fetch_add(1, Ordering::Relaxed), initial_state: MachineState::uninit(), actions: vec![], states: vec![], }; // Resolve all state refs. The actions are defined on the original states, but to avoid // requiring `Clone` on the `TAction`, we'll move them to just one vector which is indexed // by `ActionRef`. However we'll need to calculate the refs beforehand, since we can't move // the actions out of the `self.states` yet since partial moves out of `Vec` are not // supported. let mut actions_to_final: HashMap<(StateRef, usize), ActionRef> = HashMap::new(); for s in &self.states { for i in 0..s.actions.len() { let action_ref = ActionRef::new_unchecked(self.machine_id, actions_to_final.len()); actions_to_final.insert((s.self_ref, i), action_ref); } } // Register all final states on the machine and construct a mapping between mixed state // keys and final machine states. We'll need to resolve the `MachineState` references for // use in the transitions when setting up individual states later. let mut mixed_to_final: BTreeMap<MixedStateKey, MachineState> = BTreeMap::new(); for key in all_states.keys() { mixed_to_final.insert( key.clone(), MachineState::next_ref(machine.machine_id, &machine.states), ); // For now just add a place holder for the state. We'll fill this later once we have // resolved `mixed_to_final` mappings for all states. machine.states.push(FinalState { actions: vec![], transitions: vec![], }); } // Finally set up the final machine states based on the information resolved earlier. let mut dfa_transition_count = 0; for (mixed_key, mut mixed_state) in all_states { // Reference to the for-now somewhat uninitialized final state. let final_state = &mut machine.states[mixed_to_final[&mixed_key]]; // Fill in the action refs based on the actions of the original states this final state // represents. for original_ref in &mixed_key { let original_state = &self.states[*original_ref]; for i in 0..original_state.actions.len() { final_state .actions .push(actions_to_final[&(*original_ref, i)]); } } // Fill in the transitions. Since this is now the place used for the actual evaluation // later, we need to ensure the transitions are sorted by the evaluation order. mixed_state .transitions .sort_by_key(|t| t.criteria.evaluation_order()); for t in mixed_state.transitions { final_state .transitions .push((t.criteria, mixed_to_final[&t.target])); } dfa_transition_count += final_state.transitions.len(); } // Finally move the actions into the final StateMachine. The order here needs to follow the // same order we used earlier when resolving the `ActionRef`s used to refer to these // actions in the `machine.states`. // // This consumes the builder `self.states`, which is why we had to wait till now to do it. for s in self.states { for a in s.actions { machine.actions.push(a) } } let dfa_state_count = machine.states.len(); log::trace!( "Built DFA with {} states, {} transitions from NFA of {} states, {} transitions", dfa_state_count, dfa_transition_count, nfa_state_count, nfa_transition_count ); machine.initial_state = mixed_to_final[&initial_state_key]; machine } } impl<TCriteria, TAction> Default for Builder<TCriteria, TAction> where TCriteria: Criteria, { fn default() -> Self { Self::new() } } fn expand_transitions<TCriteria>( transitions: &mut Vec<MixedTransition<TCriteria>>, transition: &Transition<TCriteria>, ) where TCriteria: Criteria, { // Handle And-case first since here we can perform filtering on the fly // without having to deal with shifting elements in the Vec. // The And-case is more likely to result in empty criteria so dropping // criteria is more likely in this case. let and = transitions .iter() .filter_map(|t| { let criteria = t.criteria.and(&transition.criteria); match !criteria.is_empty() { true => { let mut new = t.clone(); new.target.add(transition.target); new.criteria = criteria; Some(new) } false => None, } }) .collect::<Vec<_>>(); // Handle the Not-case by removing the new criteria from the existing ones. // This doesn't alter the target states. let mut i = 0; while i != transitions.len() { let t = &mut transitions[i]; t.criteria = t.criteria.not(&transition.criteria); if t.criteria.is_empty() { transitions.remove(i); } else { i += 1; } } transitions.extend(and); } impl<TAction> State<TAction> { /// Create a new state with no action. pub fn new() -> Self { Self::new_impl(vec![]) } /// Create a new state with an action. pub fn with_action(action: TAction) -> Self { Self::new_impl(vec![action]) } /// Create a new state with actions. pub fn with_actions<T>(actions: T) -> Self where T: IntoIterator<Item = TAction>, { use std::iter::FromIterator; Self::new_impl(Vec::from_iter(actions)) } fn new_impl(actions: Vec<TAction>) -> Self { Self { self_ref: StateRef::uninit(), actions, transitions: vec![], } } } impl<TAction> Default for State<TAction> { fn default() -> Self { Self::new() } } impl<TCriteria> Transition<TCriteria> { /// Create a new transition between states. pub fn new(source: StateRef, criteria: TCriteria, target: StateRef) -> Self { source.assert_same_machine(target); Self { source, criteria, target, } } } impl<TCriteria, TAction> StateMachine<TCriteria, TAction> where TCriteria: Criteria, { /// Acquires the initial state of the state machine. pub fn start(&self) -> MachineState { self.initial_state } /// Performs a step from the `current` machine state with the given `input`. pub fn step(&self, current: MachineState, input: &TCriteria::Input) -> MachineState { self.next_state(current, input) } fn next_state(&self, current: MachineState, input: &TCriteria::Input) -> MachineState { current.assert_machine(self.machine_id); let current_state = &self.states[current]; for t in ¤t_state.transitions { if t.0.is_match(&input) { return t.1; } } self.start() } } impl<TCriteria, TAction> StateMachine<TCriteria, TAction> where TAction: Action, { /// Executes the actions of the `current` state with the given `input`. /// /// Use [`Self::execute_mut`] if the current `TAction` is an [`ActionMut`]. pub fn execute(&self, current: MachineState, input: &mut TAction::Input) { for a in &self.states[current].actions { self.actions[*a].execute(input); } } } impl<TCriteria, TAction> StateMachine<TCriteria, TAction> where TAction: ActionMut, { /// Executes the actions of the `current` state with the given `input`. /// /// Use [`Self::execute`] if the current `TAction` is an [`Action`]. pub fn execute_mut(&mut self, current: MachineState, input: &mut TAction::Input) { for a in &mut self.states[current].actions { self.actions[*a].execute_mut(input); } } } impl<TCriteria, TAction> StateMachine<TCriteria, TAction> where TAction: Action, TCriteria: Criteria<Input = TAction::Input>, { /// Performs a step from the current `state` and executes any actions based on the new state. /// /// This method is available only if the `TCriteria` and `TAction` have the same `Input` type /// and is equivalent to: /// /// ```ignore /// let next_state = machine.step(current_state, &input); /// machine.execute(current_state, &mut input); /// ``` pub fn step_and_execute( &self, current: MachineState, input: &mut TAction::Input, ) -> MachineState { let next = self.step(current, input); self.execute(next, input); next } } impl<TCriteria, TAction> StateMachine<TCriteria, TAction> where TAction: ActionMut, TCriteria: Criteria<Input = TAction::Input>, { /// Performs a step from the current `state` and executes any actions based on the new state. /// /// This method is available only if the `TCriteria` and `TAction` have the same `Input` type /// and is equivalent to: /// /// ```ignore /// let next_state = machine.step(current_state, &input); /// machine.execute_mut(current_state, &mut input); /// ``` pub fn step_and_execute_mut( &mut self, current: MachineState, input: &mut TAction::Input, ) -> MachineState { let next = self.step(current, input); self.execute_mut(next, input); next } } impl<T> Action for Box<dyn Fn(&mut T)> { type Input = T; fn execute(&self, input: &mut T) { self(input) } } impl<T> ActionMut for Box<dyn FnMut(&mut T)> { type Input = T; fn execute_mut(&mut self, input: &mut T) { self(input) } } impl<'a, T> ActionMut for &'a mut dyn FnMut(&mut T) { type Input = T; fn execute_mut(&mut self, input: &mut T) { self(input) } } /// A basic "is" or "is not" condition criteria. #[derive(Clone, PartialEq, Eq, Hash, Debug)] pub enum Condition<T> { /// Matches when the input is one of the values in the Vec. Is(Vec<T>), /// Matches when the input isn't one of the values in the Vec. Not(Vec<T>), /// Matches any value. Any, /// Matches no value. None, } impl<T: Clone + Copy + PartialEq + Eq + Hash> Criteria for Condition<T> { type Input = T; fn is_match(&self, i: &Self::Input) -> bool { match self { Condition::Is(c) => c.contains(&i), Condition::Not(c) => !c.contains(&i), Condition::Any => true, Condition::None => false, } } fn and(&self, other: &Self) -> Self { if self == other { return self.clone(); } match (self, other) { (Condition::Is(i), Condition::Not(n)) | (Condition::Not(n), Condition::Is(i)) => { let new: Vec<T> = i.iter().filter(|c| !n.contains(c)).copied().collect(); if new.is_empty() { Condition::None } else { Condition::Is(new) } } (Condition::Not(a), Condition::Not(b)) => { let a: HashSet<T> = a.iter().copied().collect(); let b: HashSet<T> = b.iter().copied().collect(); let intersection: Vec<T> = a.intersection(&b).copied().collect(); if intersection.is_empty() { Condition::Any } else { Condition::Not(intersection) } } (Condition::Is(_), Condition::Is(_)) => Condition::None, (Condition::None, _) | (_, Condition::None) => Condition::None, (o, Condition::Any) | (Condition::Any, o) => o.clone(), } } fn not(&self, other: &Self) -> Self { if self == other { return Condition::None; } match (self, other) { (Condition::Not(n), Condition::Is(i)) => { let mut new_not = n.clone(); new_not.extend(i); Condition::Not(new_not) } (Condition::Any, Condition::Is(i)) => Condition::Not(i.clone()), (Condition::None, _) => Condition::None, (o, Condition::None) => o.clone(), (_, Condition::Any) => Condition::None, (o, Condition::Not(n)) => o.and(&Condition::Is(n.clone())), (Condition::Is(i), _) => Condition::Is(i.clone()), } } fn is_empty(&self) -> bool { self == &Condition::None } fn any() -> Self { Condition::Any } fn evaluation_order(&self) -> usize { match self { Condition::Any => 1, _ => 0, } } } #[cfg(test)] mod test { use super::*; use test_env_log::test; #[test] fn testt() { let mut builder = Builder::<Option<BTreeSet<char>>, _>::new(); let start = builder.create_initial_state(); let first = builder.add_state(State::with_actions(vec!["S1"])); let second = builder.add_state(State::with_actions(vec!["S2"])); let third = builder.add_state(State::with_actions(vec!["S3"])); use std::iter::FromIterator; builder.add_transition(Transition::new(start, None, start)); builder.add_transition(Transition::new( start, Some(BTreeSet::from_iter("ab".chars())), first, )); builder.add_transition(Transition::new( first, Some(BTreeSet::from_iter("c".chars())), second, )); builder.add_transition(Transition::new(second, None, second)); builder.add_transition(Transition::new( second, Some(BTreeSet::from_iter("a".chars())), third, )); let machine = builder.build(); let mut next = machine.start(); for mut s in ['a', 'b', 'b', 'c', 'c', 'a', 'a', 'c'].iter().copied() { next = machine.step(next, &s); machine.execute(next, &mut s); } } impl Criteria for Option<BTreeSet<char>> { type Input = char; fn is_match(&self, input: &Self::Input) -> bool { match self { None => true, Some(set) => set.contains(input), } } fn is_empty(&self) -> bool { match self { None => false, Some(set) => set.len() == 0, } } fn evaluation_order(&self) -> usize { match self { Some(_) => 0, None => 1, } } fn and(&self, other: &Self) -> Self { match (self, other) { (None, None) => None, (None, s) | (s, None) => s.clone(), (Some(a), Some(b)) => Some(a.intersection(b).copied().collect()), } } fn not(&self, other: &Self) -> Self { match (self, other) { (_, None) => Some(BTreeSet::new()), (None, _) => None, (Some(a), Some(b)) => Some(a.difference(b).copied().collect()), } } fn any() -> Self { None } } impl Action for &'static str { type Input = char; fn execute(&self, _: &mut char) { println!("State: {}", self); } } }