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=== DIRECTORY TREE (INCLUDED ONLY) ===
gotstate/
tests/
unit/
gotstate/
runtime/
core/
types/
extensions/
persistence/
=== PACKED FILES ===
--- START OF FILE: /home/atomik/src/gotstate/tests/__init__.py ---
--- END OF FILE: /home/atomik/src/gotstate/tests/__init__.py ---
--- START OF FILE: /home/atomik/src/gotstate/tests/unit/__init__.py ---
--- END OF FILE: /home/atomik/src/gotstate/tests/unit/__init__.py ---
--- START OF FILE: /home/atomik/src/gotstate/gotstate/__init__.py ---
"""gotstate: UML-compliant Hierarchical Finite State Machine (HFSM) implementation
This package provides a robust implementation of hierarchical state machines following
UML state machine semantics.
Responsibilities:
- State machine definition and execution
- Event processing and transition management
- Hierarchical state composition
- Parallel region handling
- History state tracking
- Runtime validation
Interactions:
- Client code through public API
- Python type system for static/runtime type checking
- Operating system for concurrency primitives
- Storage systems for persistence
- Logging system for diagnostics
Cross-cutting Concerns:
Thread Safety:
- All public APIs are thread-safe
- Internal state protected by appropriate locks
- Documented thread safety guarantees per component
Error Handling:
- Structured error hierarchy
- Consistent error reporting
- Clean error recovery paths
Logging:
- Structured logging format
- Configurable verbosity levels
- Performance impact minimized
Performance:
- O(1) state lookup where possible
- Bounded memory usage
- Predictable latency
Security:
- Input validation on all public APIs
- Safe serialization/deserialization
- Protected internal state
"""
__version__ = "0.1.0"
--- END OF FILE: /home/atomik/src/gotstate/gotstate/__init__.py ---
--- START OF FILE: /home/atomik/src/gotstate/gotstate/runtime/__init__.py ---
"""
Runtime package for execution and monitoring.
Architecture:
- Manages event execution and run-to-completion
- Handles time and change event scheduling
- Provides monitoring and metrics
- Coordinates with core components
- Maintains execution guarantees
Design Patterns:
- State Pattern for execution
- Publisher/Subscriber for monitoring
- Factory Pattern for creation
- Builder Pattern for configuration
- Singleton Pattern for schedulers
Security:
- Execution isolation
- Resource monitoring
- Timer management
- Event validation
- Extension boundaries
Cross-cutting:
- Error handling with recovery
- Performance optimization
- Execution metrics
- Thread safety
"""
from .executor import Executor
from .scheduler import Scheduler
from .monitor import Monitor
__all__ = ["Executor", "Scheduler", "Monitor"]
--- END OF FILE: /home/atomik/src/gotstate/gotstate/runtime/__init__.py ---
--- START OF FILE: /home/atomik/src/gotstate/gotstate/runtime/monitor.py ---
"""
State machine monitoring and metrics management.
Architecture:
- Provides introspection capabilities
- Emits state machine events
- Tracks execution metrics
- Coordinates with all modules
- Maintains monitoring boundaries
Design Patterns:
- Observer Pattern: State monitoring
- Publisher/Subscriber: Event emission
- Strategy Pattern: Metric collection
- Decorator Pattern: Monitoring hooks
- Chain of Responsibility: Event filtering
Responsibilities:
1. State Introspection
- Current state access
- Active transitions
- Event status
- Machine configuration
- Runtime metrics
2. Event Emission
- State changes
- Transition events
- Event handling
- Error conditions
- Resource usage
3. Metric Collection
- Execution timing
- Resource usage
- Event statistics
- Error rates
- Performance data
4. Monitoring Control
- Filter configuration
- Metric selection
- Event filtering
- Resource limits
- Data retention
Security:
- Data protection
- Access control
- Resource limits
- Event filtering
Cross-cutting:
- Error handling
- Performance impact
- Resource usage
- Thread safety
Dependencies:
- machine.py: Machine monitoring
- executor.py: Execution metrics
- scheduler.py: Timer metrics
- event.py: Event monitoring
"""
from typing import Optional, Dict, List, Set, Any
from enum import Enum, auto
from dataclasses import dataclass
from threading import Lock, Event
from queue import Queue
class MonitoringLevel(Enum):
"""Defines monitoring detail levels.
Used to control monitoring granularity and resource usage.
"""
MINIMAL = auto() # Basic state changes only
NORMAL = auto() # Standard monitoring level
DETAILED = auto() # Detailed metrics and events
DEBUG = auto() # Full debugging information
class MetricType(Enum):
"""Defines types of metrics to collect.
Used to categorize and organize monitoring data.
"""
STATE = auto() # State-related metrics
TRANSITION = auto() # Transition timing/counts
EVENT = auto() # Event processing stats
RESOURCE = auto() # Resource utilization
ERROR = auto() # Error statistics
class Monitor:
"""Provides state machine monitoring and metrics.
The Monitor class implements the Observer pattern to track
state machine behavior and collect performance metrics.
Class Invariants:
1. Must maintain monitoring boundaries
2. Must preserve event order
3. Must track all metrics
4. Must control resource usage
5. Must handle concurrent access
6. Must filter sensitive data
7. Must maintain history
8. Must support queries
9. Must minimize impact
10. Must enforce limits
Design Patterns:
- Observer: Monitors state machine
- Publisher: Emits monitoring events
- Strategy: Implements policies
- Decorator: Adds monitoring
- Chain: Filters events
Data Structures:
- Queue for events
- Map for metrics
- Set for subscribers
- Tree for filtering
- Ring buffer for history
Algorithms:
- Event filtering
- Metric aggregation
- Data retention
- Resource tracking
- Query processing
Threading/Concurrency Guarantees:
1. Thread-safe monitoring
2. Atomic metric updates
3. Synchronized event emission
4. Safe concurrent access
5. Lock-free inspection
6. Mutex protection
Performance Characteristics:
1. O(1) event emission
2. O(log n) metric updates
3. O(f) filtering where f is filter count
4. O(s) subscription where s is subscriber count
5. O(q) querying where q is query complexity
Resource Management:
1. Bounded memory usage
2. Controlled event rate
3. Data retention policies
4. Automatic cleanup
5. Load shedding
"""
pass
class StateMonitor:
"""Monitors state machine state changes.
StateMonitor tracks state configurations and transitions
with minimal performance impact.
Class Invariants:
1. Must track all states
2. Must detect changes
3. Must maintain history
4. Must minimize impact
Design Patterns:
- Observer: Monitors states
- Strategy: Implements tracking
- Command: Encapsulates queries
Threading/Concurrency Guarantees:
1. Thread-safe tracking
2. Atomic updates
3. Safe concurrent access
Performance Characteristics:
1. O(1) state updates
2. O(h) history tracking where h is history size
3. O(q) querying where q is query complexity
"""
pass
class EventMonitor:
"""Monitors event processing and metrics.
EventMonitor tracks event handling performance and
statistics across the state machine.
Class Invariants:
1. Must track all events
2. Must collect metrics
3. Must maintain order
4. Must support filtering
Design Patterns:
- Observer: Monitors events
- Strategy: Implements tracking
- Chain: Filters events
Threading/Concurrency Guarantees:
1. Thread-safe monitoring
2. Atomic updates
3. Safe concurrent access
Performance Characteristics:
1. O(1) event tracking
2. O(f) filtering where f is filter count
3. O(m) metric updates where m is metric count
"""
pass
class MetricCollector:
"""Collects and aggregates performance metrics.
MetricCollector implements efficient metric collection
and aggregation with minimal overhead.
Class Invariants:
1. Must collect accurately
2. Must aggregate efficiently
3. Must maintain history
4. Must support queries
Design Patterns:
- Strategy: Implements collection
- Observer: Monitors sources
- Command: Encapsulates queries
Threading/Concurrency Guarantees:
1. Thread-safe collection
2. Atomic updates
3. Safe concurrent access
Performance Characteristics:
1. O(1) metric updates
2. O(a) aggregation where a is metric count
3. O(q) querying where q is query complexity
"""
pass
class MonitoringFilter:
"""Filters monitoring events and metrics.
MonitoringFilter implements configurable filtering of
monitoring data based on policies.
Class Invariants:
1. Must filter correctly
2. Must maintain policies
3. Must be configurable
4. Must minimize impact
Design Patterns:
- Chain: Processes filters
- Strategy: Implements policies
- Command: Encapsulates rules
Threading/Concurrency Guarantees:
1. Thread-safe filtering
2. Atomic updates
3. Safe concurrent access
Performance Characteristics:
1. O(1) policy checks
2. O(f) filtering where f is filter count
3. O(r) rule evaluation where r is rule count
"""
pass
class MonitoringSubscriber:
"""Manages monitoring event subscriptions.
MonitoringSubscriber implements the Publisher/Subscriber
pattern for monitoring event distribution.
Class Invariants:
1. Must track subscribers
2. Must maintain topics
3. Must deliver events
4. Must handle failures
Design Patterns:
- Publisher: Distributes events
- Observer: Notifies subscribers
- Strategy: Implements delivery
Threading/Concurrency Guarantees:
1. Thread-safe subscription
2. Atomic delivery
3. Safe concurrent access
Performance Characteristics:
1. O(1) subscription
2. O(s) delivery where s is subscriber count
3. O(t) topic management where t is topic count
"""
pass
--- END OF FILE: /home/atomik/src/gotstate/gotstate/runtime/monitor.py ---
--- START OF FILE: /home/atomik/src/gotstate/gotstate/runtime/scheduler.py ---
"""
Time and change event scheduling management.
Architecture:
- Manages time and change events
- Maintains timer consistency
- Coordinates with Event for queuing
- Integrates with Executor for processing
- Handles timer interruptions
Design Patterns:
- Singleton Pattern: Timer management
- Observer Pattern: Time events
- Command Pattern: Scheduled actions
- Strategy Pattern: Scheduling policies
- Chain of Responsibility: Event handling
Responsibilities:
1. Time Events
- Relative time events
- Absolute time events
- Timer management
- Timer cancellation
- Timer interruption
2. Change Events
- Change detection
- State condition evaluation
- Change event triggers
- Condition monitoring
- Event generation
3. Timer Management
- Timer creation
- Timer cancellation
- Timer interruption
- Timer state preservation
- Timer recovery
4. Event Coordination
- Event queuing
- Priority handling
- Order preservation
- Timer synchronization
- Resource management
Security:
- Timer isolation
- Resource limits
- Event validation
- State protection
Cross-cutting:
- Error handling
- Performance monitoring
- Timer metrics
- Thread safety
Dependencies:
- event.py: Event processing
- executor.py: Event execution
- monitor.py: Timer monitoring
- machine.py: Machine context
"""
from typing import Optional, Dict, List, Set, Any
from enum import Enum, auto
from dataclasses import dataclass
from threading import Lock, Timer, Event
from queue import PriorityQueue
from time import monotonic
class TimerStatus(Enum):
"""Defines the possible states of a timer.
Used to track timer lifecycle and coordinate operations.
"""
IDLE = auto() # Timer not started
ACTIVE = auto() # Timer running
PAUSED = auto() # Timer temporarily paused
CANCELLED = auto() # Timer cancelled
EXPIRED = auto() # Timer completed
class TimerKind(Enum):
"""Defines the different types of timers.
Used to determine timer behavior and scheduling.
"""
RELATIVE = auto() # After X time units
ABSOLUTE = auto() # At specific time
PERIODIC = auto() # Repeating interval
class Scheduler:
"""Manages time and change event scheduling.
The Scheduler class implements the Singleton pattern to provide
centralized timer and change event management.
Class Invariants:
1. Must maintain timer consistency
2. Must preserve event order
3. Must handle interruptions
4. Must manage resources
5. Must track timer state
6. Must detect changes
7. Must coordinate events
8. Must handle cancellation
9. Must maintain metrics
10. Must enforce limits
Design Patterns:
- Singleton: Centralizes scheduling
- Observer: Monitors events
- Command: Encapsulates actions
- Strategy: Implements policies
- Chain: Processes events
Data Structures:
- Priority queue for timers
- Set for active timers
- Map for timer state
- Queue for change events
- Tree for conditions
Algorithms:
- Timer scheduling
- Change detection
- Event ordering
- Resource allocation
- State tracking
Threading/Concurrency Guarantees:
1. Thread-safe scheduling
2. Atomic timer operations
3. Synchronized state access
4. Safe concurrent events
5. Lock-free inspection
6. Mutex protection
Performance Characteristics:
1. O(1) timer creation
2. O(log n) scheduling
3. O(1) cancellation
4. O(c) change detection where c is condition count
5. O(e) event coordination where e is event count
Resource Management:
1. Bounded timer count
2. Controlled thread usage
3. Memory pooling
4. Automatic cleanup
5. Load balancing
"""
pass
class TimerManager:
"""Manages timer lifecycle and operations.
TimerManager implements timer creation, tracking, and cleanup
with proper synchronization.
Class Invariants:
1. Must track all timers
2. Must handle interruptions
3. Must preserve state
4. Must cleanup resources
Design Patterns:
- Factory: Creates timers
- Observer: Monitors timers
- Command: Encapsulates operations
Threading/Concurrency Guarantees:
1. Thread-safe management
2. Atomic operations
3. Safe concurrent access
Performance Characteristics:
1. O(1) timer tracking
2. O(n) cleanup where n is timer count
3. O(1) state updates
"""
pass
class ChangeDetector:
"""Monitors and detects state changes.
ChangeDetector implements efficient change detection and
event generation for monitored conditions.
Class Invariants:
1. Must detect all changes
2. Must prevent missed events
3. Must maintain history
4. Must track conditions
Design Patterns:
- Observer: Monitors changes
- Strategy: Implements detection
- Command: Encapsulates events
Threading/Concurrency Guarantees:
1. Thread-safe detection
2. Atomic updates
3. Safe concurrent access
Performance Characteristics:
1. O(1) change detection
2. O(c) condition evaluation where c is condition count
3. O(h) history tracking where h is history size
"""
pass
class EventCoordinator:
"""Coordinates scheduled events and processing.
EventCoordinator manages event ordering and coordination
with the execution system.
Class Invariants:
1. Must preserve order
2. Must handle priorities
3. Must coordinate timing
4. Must manage resources
Design Patterns:
- Mediator: Coordinates events
- Observer: Monitors processing
- Strategy: Implements policies
Threading/Concurrency Guarantees:
1. Thread-safe coordination
2. Atomic operations
3. Safe concurrent access
Performance Characteristics:
1. O(log n) event ordering
2. O(p) priority handling where p is priority count
3. O(r) resource management where r is resource count
"""
pass
class SchedulerMonitor:
"""Monitors scheduler operations and metrics.
SchedulerMonitor tracks scheduling performance and
resource utilization.
Class Invariants:
1. Must track metrics
2. Must detect issues
3. Must maintain history
4. Must support queries
Design Patterns:
- Observer: Monitors scheduler
- Strategy: Implements policies
- Command: Encapsulates queries
Threading/Concurrency Guarantees:
1. Thread-safe monitoring
2. Atomic updates
3. Safe concurrent access
Performance Characteristics:
1. O(1) metric updates
2. O(q) query execution where q is query complexity
3. O(h) history tracking where h is history size
"""
pass
--- END OF FILE: /home/atomik/src/gotstate/gotstate/runtime/scheduler.py ---
--- START OF FILE: /home/atomik/src/gotstate/gotstate/runtime/executor.py ---
"""
Event execution and run-to-completion management.
Architecture:
- Enforces run-to-completion semantics
- Manages transition execution
- Handles concurrent operations
- Coordinates with Event for processing
- Integrates with Monitor for metrics
Design Patterns:
- State Pattern: Execution states
- Command Pattern: Execution units
- Observer Pattern: Execution events
- Strategy Pattern: Execution policies
- Chain of Responsibility: Event processing
Responsibilities:
1. Run-to-Completion
- Event processing semantics
- Event queuing
- Transition atomicity
- Order preservation
- Re-entrancy handling
2. Transition Execution
- Guard evaluation
- Action execution
- State changes
- Error recovery
- Resource cleanup
3. Concurrency
- Parallel execution
- Synchronization
- Resource management
- Deadlock prevention
- Race condition handling
4. Error Management
- Execution failures
- Partial completion
- State recovery
- Resource cleanup
- Error propagation
Security:
- Execution isolation
- Resource boundaries
- Action sandboxing
- State protection
Cross-cutting:
- Error handling
- Performance monitoring
- Execution metrics
- Thread safety
Dependencies:
- event.py: Event processing
- transition.py: Transition handling
- monitor.py: Execution monitoring
- machine.py: Machine context
"""
from typing import Optional, Dict, List, Set, Any
from enum import Enum, auto
from dataclasses import dataclass
from threading import Lock, RLock, Event, Condition
class ExecutionStatus(Enum):
"""Defines the possible states of execution.
Used to track execution progress and coordinate operations.
"""
IDLE = auto() # No execution in progress
EXECUTING = auto() # Currently executing
SUSPENDED = auto() # Temporarily suspended
ROLLING_BACK = auto() # Handling failure
FAILED = auto() # Execution failed
class ExecutionMode(Enum):
"""Defines execution modes for the executor.
Used to determine execution behavior and policies.
"""
SYNCHRONOUS = auto() # Execute in calling thread
ASYNCHRONOUS = auto() # Execute in separate thread
PARALLEL = auto() # Execute in thread pool
class Executor:
"""Manages event execution with run-to-completion semantics.
The Executor class implements the Command pattern to manage
execution units while enforcing run-to-completion semantics.
Class Invariants:
1. Must maintain run-to-completion semantics
2. Must preserve event ordering
3. Must ensure transition atomicity
4. Must handle concurrent execution
5. Must manage resources properly
6. Must recover from failures
7. Must prevent deadlocks
8. Must maintain metrics
9. Must isolate execution
10. Must enforce boundaries
Design Patterns:
- Command: Encapsulates execution units
- State: Manages execution states
- Observer: Notifies of execution
- Strategy: Implements policies
- Chain: Processes events
Data Structures:
- Queue for pending executions
- Set for active executions
- Map for execution status
- Graph for dependencies
- Stack for rollback
Algorithms:
- Dependency resolution
- Resource allocation
- Deadlock detection
- Rollback planning
- Metrics collection
Threading/Concurrency Guarantees:
1. Thread-safe execution
2. Atomic transitions
3. Synchronized resources
4. Safe concurrent access
5. Lock-free inspection
6. Mutex protection
Performance Characteristics:
1. O(1) status checks
2. O(log n) scheduling
3. O(d) dependency check where d is dependency count
4. O(r) rollback where r is operation count
5. O(m) metrics update where m is metric count
Resource Management:
1. Bounded thread usage
2. Controlled memory allocation
3. Resource pooling
4. Automatic cleanup
5. Load balancing
"""
pass
class ExecutionUnit:
"""Represents an atomic unit of execution.
ExecutionUnit implements the Command pattern to encapsulate
a single execution operation with rollback capability.
Class Invariants:
1. Must be atomic
2. Must support rollback
3. Must track resources
4. Must maintain metrics
Design Patterns:
- Command: Encapsulates operation
- Memento: Supports rollback
- Observer: Reports progress
Threading/Concurrency Guarantees:
1. Thread-safe execution
2. Atomic operations
3. Safe concurrent access
Performance Characteristics:
1. O(1) execution
2. O(r) rollback where r is state size
3. O(m) metrics where m is metric count
"""
pass
class ExecutionContext:
"""Maintains context for execution units.
ExecutionContext provides isolation and resource tracking
for execution unit operations.
Class Invariants:
1. Must maintain isolation
2. Must track resources
3. Must support cleanup
4. Must preserve state
Design Patterns:
- Context: Provides execution environment
- Memento: Preserves state
- Observer: Monitors resources
Threading/Concurrency Guarantees:
1. Thread-safe context
2. Atomic state updates
3. Safe concurrent access
Performance Characteristics:
1. O(1) context switches
2. O(r) resource tracking where r is resource count
3. O(s) state management where s is state size
"""
pass
class ExecutionScheduler:
"""Schedules execution units for processing.
ExecutionScheduler manages the ordering and timing of
execution unit processing.
Class Invariants:
1. Must preserve order
2. Must handle priorities
3. Must prevent starvation
4. Must manage resources
Design Patterns:
- Strategy: Implements scheduling
- Observer: Monitors execution
- Chain: Processes units
Threading/Concurrency Guarantees:
1. Thread-safe scheduling
2. Atomic updates
3. Safe concurrent access
Performance Characteristics:
1. O(log n) scheduling
2. O(p) priority management where p is priority count
3. O(r) resource allocation where r is resource count
"""
pass
class ExecutionMonitor:
"""Monitors execution progress and metrics.
ExecutionMonitor tracks execution status and collects
performance metrics.
Class Invariants:
1. Must track progress
2. Must collect metrics
3. Must detect issues
4. Must maintain history
Design Patterns:
- Observer: Monitors execution
- Strategy: Implements policies
- Command: Encapsulates queries
Threading/Concurrency Guarantees:
1. Thread-safe monitoring
2. Atomic updates
3. Safe concurrent access
Performance Characteristics:
1. O(1) status updates
2. O(m) metric collection where m is metric count
3. O(h) history tracking where h is history size
"""
pass
--- END OF FILE: /home/atomik/src/gotstate/gotstate/runtime/executor.py ---
--- START OF FILE: /home/atomik/src/gotstate/gotstate/core/state.py ---
"""
State class and hierarchy management.
Architecture:
- Implements hierarchical state structure using Composite pattern
- Manages state data with isolation guarantees
- Enforces state invariants and validation
- Coordinates with Region for parallel state execution
- Preserves history state information
Design Patterns:
- Composite Pattern: Hierarchical state structure
- Observer Pattern: State change notifications
- Memento Pattern: History state preservation
- Builder Pattern: State configuration