# MultiState
A Python library for managing multiple simultaneous active states with intelligent pathfinding and coordinated transitions.
## Overview
Unlike traditional FSM libraries that assume a single active state, MultiState handles:
- Multiple states active simultaneously
- State groups that activate/deactivate together
- Pathfinding to multiple target states
- Coordinated transition execution with phases
- Incoming transitions for newly activated states
## Installation
```bash
pip install multistate
```
## Quick Start
```python
from multistate import StateManager, State, StateGroup, Transition
# Create states
login = State("login")
dashboard = State("dashboard")
toolbar = State("toolbar")
sidebar = State("sidebar")
# Group related states
workspace = StateGroup("workspace", [dashboard, toolbar, sidebar])
# Setup manager
manager = StateManager()
manager.add_state(login)
manager.add_group(workspace)
# Define transition that activates multiple states
login_transition = Transition(
from_states={login},
activate_group=workspace # Activates all states in group
)
# Execute transition
manager.execute_transition(login_transition)
assert manager.get_active_states() == {dashboard, toolbar, sidebar}
```
## Documentation
Full documentation available at [https://jspinak.github.io/multistate/](https://jspinak.github.io/multistate/)
## Research
This library is based on research extending Model-based GUI Automation theory. See the `paper/` directory for:
- Formal mathematical model
- Related work analysis
- Implementation details
## Contributing
We welcome contributions! Please see CONTRIBUTING.md for guidelines.
## License
MIT License - See LICENSE file for details.
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"description": "# MultiState\n\nA Python library for managing multiple simultaneous active states with intelligent pathfinding and coordinated transitions.\n\n## Overview\n\nUnlike traditional FSM libraries that assume a single active state, MultiState handles:\n- Multiple states active simultaneously\n- State groups that activate/deactivate together\n- Pathfinding to multiple target states\n- Coordinated transition execution with phases\n- Incoming transitions for newly activated states\n\n## Installation\n\n```bash\npip install multistate\n```\n\n## Quick Start\n\n```python\nfrom multistate import StateManager, State, StateGroup, Transition\n\n# Create states\nlogin = State(\"login\")\ndashboard = State(\"dashboard\")\ntoolbar = State(\"toolbar\")\nsidebar = State(\"sidebar\")\n\n# Group related states\nworkspace = StateGroup(\"workspace\", [dashboard, toolbar, sidebar])\n\n# Setup manager\nmanager = StateManager()\nmanager.add_state(login)\nmanager.add_group(workspace)\n\n# Define transition that activates multiple states\nlogin_transition = Transition(\n from_states={login},\n activate_group=workspace # Activates all states in group\n)\n\n# Execute transition\nmanager.execute_transition(login_transition)\nassert manager.get_active_states() == {dashboard, toolbar, sidebar}\n```\n\n## Documentation\n\nFull documentation available at [https://jspinak.github.io/multistate/](https://jspinak.github.io/multistate/)\n\n## Research\n\nThis library is based on research extending Model-based GUI Automation theory. See the `paper/` directory for:\n- Formal mathematical model\n- Related work analysis\n- Implementation details\n\n## Contributing\n\nWe welcome contributions! Please see CONTRIBUTING.md for guidelines.\n\n## License\n\nMIT License - See LICENSE file for details.",
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