def __init__(self, state_machine, meta=None, load_meta_data=True):
"""Constructor
"""
MetaModel.__init__(self) # pass columns as separate parameters
assert isinstance(state_machine, StateMachine)
self.state_machine = state_machine
self.state_machine_id = state_machine.state_machine_id
root_state = self.state_machine.root_state
if isinstance(root_state, ContainerState):
self.root_state = ContainerStateModel(
root_state, parent=self, load_meta_data=load_meta_data)
else:
self.root_state = StateModel(root_state,
parent=self,
load_meta_data=load_meta_data)
if isinstance(meta, Vividict):
self.meta = meta
else:
self.meta = Vividict()
# ongoing_complex_actions is updated by ComplexActionObserver -> secure encapsulated observation
# and made observable by state machine model here
self.ongoing_complex_actions = {}
self.complex_action_observer = ComplexActionObserver(self)
self.meta_signal = Signal()
self.state_meta_signal = Signal()
self.action_signal = Signal()
self.state_action_signal = Signal()
self.sm_selection_changed_signal = Signal()
self.destruction_signal = Signal()
self.temp = Vividict()
if load_meta_data:
self.load_meta_data(recursively=False)
self.selection = Selection(self.sm_selection_changed_signal)
self.storage_lock = threading.Lock(
) # lock can not be substituted by the state machine lock -> maybe because it is a RLock
self.history = None
if global_gui_config.get_config_value('HISTORY_ENABLED'):
from rafcon.gui.models.modification_history import ModificationsHistoryModel
self.history = ModificationsHistoryModel(self)
else:
logger.info("The modification history is disabled")
self.auto_backup = None
if global_gui_config.get_config_value('AUTO_BACKUP_ENABLED'):
from rafcon.gui.models.auto_backup import AutoBackupModel
self.auto_backup = AutoBackupModel(self)
self.root_state.register_observer(self)
self.register_observer(self)
def load_meta_data(self, path=None):
"""Load meta data of state model from the file system
The meta data of the state model is loaded from the file system and stored in the meta property of the model.
Existing meta data is removed. Also the meta data of all state elements (data ports, outcomes,
etc) are loaded, as those stored in the same file as the meta data of the state.
This is either called on the __init__ of a new state model or if a state model for a container state is created,
which then calls load_meta_data for all its children.
:param str path: Optional file system path to the meta data file. If not given, the path will be derived from
the state's path on the filesystem
:return: if meta data file was loaded True otherwise False
:rtype: bool
"""
# TODO: for an Execution state this method is called for each hierarchy level again and again, still?? check it!
# print("1AbstractState_load_meta_data: ", path, not path)
if not path:
path = self.state.file_system_path
# print("2AbstractState_load_meta_data: ", path)
if path is None:
self.meta = Vividict({})
return False
path_meta_data = os.path.join(path, storage.FILE_NAME_META_DATA)
# TODO: Should be removed with next minor release
if not os.path.exists(path_meta_data):
logger.debug("Because meta data was not found in {0} use backup option {1}"
"".format(path_meta_data, os.path.join(path, storage.FILE_NAME_META_DATA_OLD)))
path_meta_data = os.path.join(path, storage.FILE_NAME_META_DATA_OLD)
# TODO use the following logger message to debug meta data load process and to avoid maybe repetitive loads
# if not os.path.exists(path_meta_data):
# logger.info("path not found {0}".format(path_meta_data))
try:
# print("try to load meta data from {0} for state {1}".format(path_meta_data, self.state))
tmp_meta = storage.load_data_file(path_meta_data)
except ValueError as e:
# if no element which is newly generated log a warning
# if os.path.exists(os.path.dirname(path)):
# logger.debug("Because '{1}' meta data of {0} was not loaded properly.".format(self, e))
if not path.startswith(constants.RAFCON_TEMP_PATH_STORAGE) and not os.path.exists(os.path.dirname(path)):
logger.debug("Because '{1}' meta data of {0} was not loaded properly.".format(self, e))
tmp_meta = {}
# JSON returns a dict, which must be converted to a Vividict
tmp_meta = Vividict(tmp_meta)
if tmp_meta:
self._parse_for_element_meta_data(tmp_meta)
# assign the meta data to the state
self.meta = tmp_meta
self.meta_signal.emit(MetaSignalMsg("load_meta_data", "all", True))
return True
else:
# print("nothing to parse", tmp_meta)
return False
def __init__(self, meta=None):
ModelMT.__init__(self)
if isinstance(meta, dict):
self.meta = Vividict(meta)
else:
self.meta = Vividict()
self.temp = Vividict()
self.meta_signal = Signal()
def load_meta_data(self, path=None, recursively=True):
"""Load meta data of state machine model from the file system
The meta data of the state machine model is loaded from the file system and stored in the meta property of the
model. Existing meta data is removed. Also the meta data of root state and children is loaded.
:param str path: Optional path to the meta data file. If not given, the path will be derived from the state
machine's path on the filesystem
"""
meta_data_path = path if path is not None else self.state_machine.file_system_path
if meta_data_path:
path_meta_data = os.path.join(meta_data_path,
storage.FILE_NAME_META_DATA)
try:
tmp_meta = storage.load_data_file(path_meta_data)
except ValueError:
tmp_meta = {}
else:
tmp_meta = {}
# JSON returns a dict, which must be converted to a Vividict
tmp_meta = Vividict(tmp_meta)
if recursively:
root_state_path = None if not path else os.path.join(
path, self.root_state.state.state_id)
self.root_state.load_meta_data(root_state_path)
if tmp_meta:
# assign the meta data to the state
self.meta = tmp_meta
self.meta_signal.emit(MetaSignalMsg("load_meta_data", "all", True))
def __init__(self, state_machine_manager, meta=None):
"""Constructor"""
ModelMT.__init__(self) # pass columns as separate parameters
self.register_observer(self)
assert isinstance(state_machine_manager, StateMachineManager)
self.state_machine_manager = state_machine_manager
self.state_machines = {}
for sm_id, sm in state_machine_manager.state_machines.items():
self.state_machines[sm_id] = StateMachineModel(sm)
self._selected_state_machine_id = None
if len(self.state_machines) > 0:
self.selected_state_machine_id = list(
self.state_machines.keys())[0]
if isinstance(meta, Vividict):
self.meta = meta
else:
self.meta = Vividict()
# check if the sm_manager_model exists several times
self.__class__.__sm_manager_creation_counter += 1
if self.__class__.__sm_manager_creation_counter == 2:
logger.error("Sm_manager_model exists several times!")
os._exit(0)
def __init__(self, meta=None):
"""Constructor"""
ModelMT.__init__(self) # pass columns as separate parameters
if isinstance(meta, Vividict):
self.meta = meta
else:
self.meta = Vividict()
def __init__(self, state_machine_model):
ModelMT.__init__(self)
assert isinstance(state_machine_model, StateMachineModel)
self.state_machine_model = state_machine_model
# variables used for lock files
# TODO reduce those variables
self.__destroyed = False
self.AUTO_RECOVERY_LOCK_ENABLED = False
if os.path.exists(os.path.join(RAFCON_TEMP_PATH_BASE, 'lock')) and \
global_gui_config.get_config_value('AUTO_RECOVERY_LOCK_ENABLED'):
self.AUTO_RECOVERY_LOCK_ENABLED = True
self.lock_file_lock = threading.Lock()
self.lock_file = None
self.last_lock_file_name = None
# general auto-backup variable
self.timed_temp_storage_enabled = global_gui_config.get_config_value(
'AUTO_BACKUP_ENABLED')
self.only_fix_interval = global_gui_config.get_config_value(
'AUTO_BACKUP_ONLY_FIX_FORCED_INTERVAL')
self.force_temp_storage_interval = global_gui_config.get_config_value(
'AUTO_BACKUP_FORCED_STORAGE_INTERVAL')
self.timed_temp_storage_interval = global_gui_config.get_config_value(
'AUTO_BACKUP_DYNAMIC_STORAGE_INTERVAL')
self.last_backup_time = time.time(
) # used as 'last-backup' and 'last-modification-not-backup-ed' time
self.marked_dirty = False
self.__perform_storage = False
self._timer_request_time = None
self.timer_request_lock = threading.Lock()
self.tmp_timed_storage_thread = None
self.meta = Vividict()
if state_machine_model.state_machine.file_system_path is not None:
# logger.info("store meta data of {0} to {1}".format(self, meta_data_path))
# data used for restore tabs -> (having the information to load state machines without loading them)
self.meta['last_saved'][
'time'] = state_machine_model.state_machine.last_update
self.meta['last_saved'][
'file_system_path'] = state_machine_model.state_machine.file_system_path
logger.debug(
"The auto-backup for state-machine {2} is {0} and set to '{1}'"
"".format(
'ENABLED' if self.timed_temp_storage_enabled else 'DISABLED',
'fix interval mode'
if self.only_fix_interval else 'dynamic interval mode',
self.state_machine_model.state_machine.state_machine_id))
# register observer before initializing check loop
self.observe_model(self.state_machine_model)
# initializing check loop to fully initialize the model
if not self.only_fix_interval:
self.perform_temp_storage()
else:
self.check_for_auto_backup(force=True)
def load_meta_data(self, path=None):
"""Load meta data of state model from the file system
The meta data of the state model is loaded from the file system and stored in the meta property of the model.
Existing meta data is removed. Also the meta data of all state elements (data ports, outcomes,
etc) are loaded, as those stored in the same file as the meta data of the state.
This is either called on the __init__ of a new state model or if a state model for a container state is created,
which then calls load_meta_data for all its children.
:param str path: Optional file system path to the meta data file. If not given, the path will be derived from
the state's path on the filesystem
:return: if meta data file was loaded True otherwise False
:rtype: bool
"""
if not path:
path = self.state.file_system_path
if path is None:
self.meta = Vividict({})
return False
path_meta_data = os.path.join(path, storage.FILE_NAME_META_DATA)
try:
tmp_meta = storage.load_data_file(path_meta_data)
except ValueError as e:
if not path.startswith(
constants.RAFCON_TEMP_PATH_STORAGE) and not os.path.exists(
os.path.dirname(path)):
logger.debug(
"Because '{1}' meta data of {0} was not loaded properly.".
format(self, e))
tmp_meta = {}
# JSON returns a dict, which must be converted to a Vividict
tmp_meta = Vividict(tmp_meta)
if tmp_meta:
self._parse_for_element_meta_data(tmp_meta)
# assign the meta data to the state
self.meta = tmp_meta
self.meta_signal.emit(MetaSignalMsg("load_meta_data", "all", True))
return True
else:
return False
def __init__(self, execution_engine, meta=None):
"""Constructor"""
ModelMT.__init__(self) # pass columns as separate parameters
self.register_observer(self)
assert isinstance(execution_engine, ExecutionEngine)
self.execution_engine = execution_engine
if isinstance(meta, Vividict):
self.meta = meta
else:
self.meta = Vividict()
def __init__(self, library_manager, meta=None):
"""Constructor
"""
ModelMT.__init__(self) # pass columns as separate parameters
assert isinstance(library_manager, LibraryManager)
self.library_manager = library_manager
if isinstance(meta, Vividict):
self.meta = meta
else:
self.meta = Vividict()
# this class is an observer of its own properties:
self.register_observer(self)
def create_new_state_from_state_with_type(source_state, target_state_class):
"""The function duplicates/transforms a state to a new state type. If the source state type and the new state
type both are ContainerStates the new state will have not transitions to force the user to explicitly re-order
the logical flow according the paradigm of the new state type.
:param source_state: previous/original state that is to transform into a new state type (target_state_class)
:param target_state_class: the final state class type
:return:
"""
current_state_is_container = isinstance(source_state, ContainerState)
new_state_is_container = issubclass(target_state_class, ContainerState)
if current_state_is_container and new_state_is_container: # TRANSFORM from CONTAINER- TO CONTAINER-STATE
# by default all transitions are left out if the new and original state are container states
# -> because switch from Barrier, Preemptive or Hierarchy has always different rules
state_transitions = {}
state_start_state_id = None
logger.info("Type change from %s to %s" %
(type(source_state).__name__, target_state_class.__name__))
# decider state is removed because it is unique for BarrierConcurrencyState
if isinstance(source_state, BarrierConcurrencyState):
source_state.remove_state(UNIQUE_DECIDER_STATE_ID, force=True)
assert UNIQUE_DECIDER_STATE_ID not in source_state.states
# separate state-elements from source state
data_flows = dict(source_state.data_flows)
source_state.data_flows = {}
input_data_ports = dict(source_state.input_data_ports)
output_data_ports = dict(source_state.output_data_ports)
scoped_variables = dict(source_state.scoped_variables)
income = source_state.income
outcomes = dict(source_state.outcomes)
source_state.input_data_ports = {}
source_state.output_data_ports = {}
source_state.scoped_variables = {}
source_state.transitions = {
} # before remove of outcomes related transitions should be gone
source_state.income = Income()
source_state.outcomes = {}
states = dict(source_state.states)
# TODO check why next line can not be performed
# source_state.states = {}
new_state = target_state_class(name=source_state.name,
state_id=source_state.state_id,
input_data_ports=input_data_ports,
output_data_ports=output_data_ports,
scoped_variables=scoped_variables,
income=income,
outcomes=outcomes,
transitions=state_transitions,
data_flows=data_flows,
states=states,
start_state_id=state_start_state_id)
else: # TRANSFORM from EXECUTION- TO CONTAINER-STATE or FROM CONTAINER- TO EXECUTION-STATE
# in case the new state is an execution state remove of child states (for observable notifications)
if current_state_is_container and issubclass(target_state_class,
ExecutionState):
if isinstance(source_state, BarrierConcurrencyState):
source_state.remove_state(UNIQUE_DECIDER_STATE_ID, force=True)
assert UNIQUE_DECIDER_STATE_ID not in source_state.states
for state_id in list(source_state.states.keys()):
source_state.remove_state(state_id)
# separate state-elements from source state
input_data_ports = dict(source_state.input_data_ports)
output_data_ports = dict(source_state.output_data_ports)
income = source_state.income
outcomes = dict(source_state.outcomes)
source_state.input_data_ports = {}
source_state.output_data_ports = {}
source_state.income = Income()
source_state.outcomes = {}
new_state = target_state_class(name=source_state.name,
state_id=source_state.state_id,
input_data_ports=input_data_ports,
output_data_ports=output_data_ports,
income=income,
outcomes=outcomes)
if source_state.description is not None and len(
source_state.description) > 0:
new_state.description = source_state.description
new_state.semantic_data = Vividict(source_state.semantic_data)
return new_state
def load_state_recursively(parent, state_path=None, dirty_states=[]):
"""Recursively loads the state
It calls this method on each sub-state of a container state.
:param parent: the root state of the last load call to which the loaded state will be added
:param state_path: the path on the filesystem where to find the meta file for the state
:param dirty_states: a dict of states which changed during loading
:return:
"""
from rafcon.core.states.execution_state import ExecutionState
from rafcon.core.states.container_state import ContainerState
from rafcon.core.states.hierarchy_state import HierarchyState
from rafcon.core.singleton import library_manager
path_core_data = get_core_data_path(state_path)
path_meta_data = get_meta_data_path(state_path)
logger.debug("Load state recursively: {0}".format(str(state_path)))
try:
state_info = load_data_file(path_core_data)
except ValueError as e:
logger.exception("Error while loading state data: {0}".format(e))
return
except LibraryNotFoundException as e:
if global_config.get_config_value(
"RAISE_ERROR_ON_MISSING_LIBRARY_STATES",
False) or not library_manager.show_dialog:
raise
logger.error(
"Library could not be loaded: {0}\n"
"Skipping library and continuing loading the state machine".format(
e))
state_info = storage_utils.load_objects_from_json(path_core_data,
as_dict=True)
missing_library_meta_data = None
if os.path.exists(path_meta_data):
missing_library_meta_data = Vividict(
storage_utils.load_objects_from_json(path_meta_data))
state_id = state_info["state_id"]
outcomes = {
outcome['outcome_id']: Outcome(outcome['outcome_id'],
outcome['name'])
for outcome in state_info["outcomes"].values()
}
dummy_state = HierarchyState(
LIBRARY_NOT_FOUND_DUMMY_STATE_NAME,
state_id=state_id,
outcomes=outcomes,
is_dummy=True,
missing_library_meta_data=missing_library_meta_data)
library_name = state_info['library_name']
path_parts = os.path.join(state_info['library_path'],
library_name).split(os.sep)
dummy_state.description = 'The Missing Library Path: %s\nThe Missing Library Name: %s\n\n' % (
state_info['library_path'], library_name)
from rafcon.core.singleton import library_manager
if path_parts[0] in library_manager.library_root_paths:
dummy_state.description += 'The Missing Library OS Path: %s' % os.path.join(
library_manager.library_root_paths[path_parts[0]], *
path_parts[1:])
else:
dummy_state.description += 'The missing library was located in the missing library root "%s"' % path_parts[
0]
# set parent of dummy state
if isinstance(parent, ContainerState):
parent.add_state(dummy_state, storage_load=True)
else:
dummy_state.parent = parent
return dummy_state
except LibraryNotFoundSkipException:
return None
# Transitions and data flows are not added when loading a state, as also states are not added.
# We have to wait until the child states are loaded, before adding transitions and data flows, as otherwise the
# validity checks for transitions and data flows would fail
if not isinstance(state_info, tuple):
state = state_info
else:
state = state_info[0]
transitions = state_info[1]
data_flows = state_info[2]
# set parent of state
if parent is not None and isinstance(parent, ContainerState):
parent.add_state(state, storage_load=True)
else:
state.parent = parent
# read script file if state is an ExecutionState
if isinstance(state, ExecutionState):
script_text = read_file(state_path, state.script.filename)
state.script.set_script_without_compilation(script_text)
# load semantic data
try:
semantic_data = load_data_file(
os.path.join(state_path, SEMANTIC_DATA_FILE))
state.semantic_data = semantic_data
except Exception as e:
# semantic data file does not have to be there
pass
# load child states
for p in os.listdir(state_path):
child_state_path = os.path.join(state_path, p)
if os.path.isdir(child_state_path):
if not os.path.exists(
os.path.join(child_state_path, FILE_NAME_CORE_DATA)):
# this means that child_state_path is a folder, not containing a valid state
# this also happens when pip creates __pycache__ folders for the script.py files upon installing rafcon
continue
child_state = load_state_recursively(state, child_state_path,
dirty_states)
if not child_state:
return None
# Now we can add transitions and data flows, as all child states were added
if isinstance(state_info, tuple):
safe_init = global_config.get_config_value("LOAD_SM_WITH_CHECKS", True)
if safe_init:
# this will trigger all validity checks the state machine
state.transitions = transitions
else:
state._transitions = transitions
state._data_flows = data_flows
for _, transition in state.transitions.items():
transition._parent = ref(state)
state._data_flows = data_flows
for _, data_flow in state.data_flows.items():
data_flow._parent = ref(state)
state.file_system_path = state_path
if state.marked_dirty:
dirty_states.append(state)
return state
