def dfs(problem):
"""
Depth first graph search algorithm - implemented for you
returns a solution for the given search problem
:param
problem (a Problem object) representing the quest
see Problem class definition in spartanquest.py)
:return: list of actions representing the solution to the quest
or None if there is no solution
"""
closed = set() # keep track of our explored states
fringe = data_structures.Stack() # for dfs, the fringe is a stack
state = problem.start_state()
root = data_structures.Node(state)
fringe.push(root)
while True:
if fringe.is_empty():
return None # Failure - fringe is empty and no solution was found
node = fringe.pop()
if problem.is_goal(node.state):
return node.solution()
if node.state not in closed: # we are implementing graph search
closed.add(node.state)
for child_state, action, action_cost in problem.successors(
node.state):
child_node = data_structures.Node(child_state, node, action)
fringe.push(child_node)
def test_pop_empty(self):
test_stack = data_structures.Stack()
try:
popped = test_stack.pop()
except:
pass
else:
assert False, "Expected an exception; instead got a Node with value '{}'.".format(
popped.data)
def test_stack(self):
x = data_structures.Stack()
x.push('lorem')
x.push('dim')
x.push('sum')
x.push('Cha')
x.push('siu')
x.push('bao')
return x
import data_structures as ds
#==================================
# STACK TESTS
#==================================
# test initialisation conditions
stack = ds.Stack()
assert stack.size() == 0
assert stack.isEmpty()
# test push() conditions
stack.push('abc')
assert stack.size() == 1
assert not stack.isEmpty()
# test pop() conditions
assert stack.pop() == 'abc'
assert stack.size() == 0
assert stack.isEmpty()
# test null cases
assert stack.pop() == None
assert stack.peek() == None
# test correct execution
stackwithwrapper = ds.Stack([0, 1, 2, 3], )
assert stackwithwrapper.pop() == 3
assert stackwithwrapper.peek() == 2
assert stackwithwrapper.size() == 3
