# Path: misc/priority_queue.py
# class PriorityQueue(StableQueue):
#   def __init__(self, array=[]):
#     super(PriorityQueue, self).__init__()
#     self.queue = list(map(lambda x: self.new_node(*x), array))
#     heapify(self.queue)
#   def peek(self):
#     return self.queue[0].element
#   def push(self, priority, element):
#     heappush(self.queue, self.new_node(priority, element))
#   def pop(self):
#     return heappop(self.queue).element
#   def empty(self):
#     return len(self) == 0
#   def __len__(self):
#     return len(self.queue)
#   def __repr__(self):
#     #order = self.queue
#     order = sorted(self.queue)
#     return '{}{}'.format(self.__class__.__name__, order)


from misc.utils import *
from misc.priority_queue import PriorityQueue
Node = namedtuple('Node', ['cost', 'operators'])

"""
class Node(Set, object):
  def __init__(self, operators):
    self.operators = operators
    self.cost = self._cost()
  def __contains__(self, operator):
    return operator in self.operators
  def __iter__(self):
    return iter(self.operators)
  def __len__(self):
    return len(self.operators)
  def _cost(self):
    return sum(operator.cost for operator in self.operators)

# https://docs.python.org/2/library/stdtypes.html#set.union
# set.union
class UnitNode(Node):
  def _cost(self):
    return len(self.operators)
"""

# TODO - merge process that attempts to reason about operators that accomplish each others goals by extending union

def relaxed_plan(state, goal, operators, unit=False, greedy=True):
  variable_nodes = defaultdict(dict)
  operator_nodes = {}
  conditions = defaultdict(lambda: defaultdict(list))
  unsatisfied = {}

# Path: misc/priority_queue.py
# class PriorityQueue(StableQueue):
#   def __init__(self, array=[]):
#     super(PriorityQueue, self).__init__()
#     self.queue = list(map(lambda x: self.new_node(*x), array))
#     heapify(self.queue)
#   def peek(self):
#     return self.queue[0].element
#   def push(self, priority, element):
#     heappush(self.queue, self.new_node(priority, element))
#   def pop(self):
#     return heappop(self.queue).element
#   def empty(self):
#     return len(self) == 0
#   def __len__(self):
#     return len(self.queue)
#   def __repr__(self):
#     #order = self.queue
#     order = sorted(self.queue)
#     return '{}{}'.format(self.__class__.__name__, order)


# Path: sas/set_additive.py
from misc.utils import *
from misc.priority_queue import PriorityQueue

Node = namedtuple('Node', ['cost', 'operators'])

"""
class Node(Set, object):
  def __init__(self, operators):
    self.operators = operators
    self.cost = self._cost()
  def __contains__(self, operator):
    return operator in self.operators
  def __iter__(self):
    return iter(self.operators)
  def __len__(self):
    return len(self.operators)
  def _cost(self):
    return sum(operator.cost for operator in self.operators)

# https://docs.python.org/2/library/stdtypes.html#set.union
# set.union
class UnitNode(Node):
  def _cost(self):
    return len(self.operators)
"""

# TODO - merge process that attempts to reason about operators that accomplish each others goals by extending union

def relaxed_plan(state, goal, operators, unit=False, greedy=True):
  variable_nodes = defaultdict(dict)
  operator_nodes = {}
  conditions = defaultdict(lambda: defaultdict(list))
  unsatisfied = {}

  queue = PriorityQueue()