class WumpusWorldScenario(object):
    """
    Construct a Wumpus World Scenario
    Objects that can be added to the environment:
        Wumpus()
        Pit()
        Gold()
        Wall()
        HybridWumpusAgent(heading)  # A propositional logic Wumpus World agent
        Explorer(program, heading)  # A non-logical Wumpus World agent (mostly for debugging)
    Provides methods to load layout from file
    Provides step and run methods to run the scenario
        with the provided agent's agent_program
    """
    
    def __init__(self, layout_file=None, agent=None, objects=None,
                 width=None, height=None, entrance=None, trace=True):
        """
        layout_file := (<string: layout_file_name>, <agent>)
        """
        if agent != None and not isinstance(agent, Explorer):
            raise Exception("agent must be type Explorer, got instance of class\n" \
                            + " {0}".format(agent.__class__))
        if layout_file:
            objects, width, height, entrance = self.load_layout(layout_file)
            
        self.width, self.height = width, height
        self.entrance = entrance
        self.agent = agent
        self.objects = objects
        self.trace = trace
        self.env = self.build_world(width, height, entrance, agent, objects)

    def build_world(self, width, height, entrance, agent, objects):
        """
        Create a WumpusEnvironment with dimensions width,height
        Set the environment entrance
        objects := [(<wumpus_environment_object>, <location: (<x>,<y>) >, ...]
        """
        env = WumpusEnvironment(width, height, entrance)
        if self.trace:
            agent = wumpus_environment.TraceAgent(agent)
        agent.register_environment(env)
        env.add_thing(agent, env.entrance)
        for (obj, loc) in objects:
            env.add_thing(obj, loc)
        return env

    def load_layout(self, layout_file):
        """
        Load text file specifying Wumpus Environment initial configuration
        Text file is N (rows) by M (columns) grid where each cell in a row
        consists of M comma-separated cells specs, where each cell contains
        either:
           '.' : space (really just a placeholder)
        or a one or more of (although typically just have one per cell):
           'W' : wumpus
           'P' : pit
           'G' : gold
           'A' : wumpus hunter agent (heading specified in agent object)
        """
        
        if layout_file.endswith('.lay'):
            layout = self.tryToLoad('layouts/' + layout_file)
            if not layout: layout = self.tryToLoad(layout_file)
        else:
            layout = self.tryToLoad('layouts/' + layout_file + '.lay')
            if not layout: layout = self.tryToLoad(layout_file + '.lay')

        if not layout:
            raise Exception("Could not find layout file: {0}".format(layout_file))

        print "Loaded layout '{0}'".format(layout_file)

        objects = []
        entrance = (1,1) # default entrance location
        
        ri = len(layout)
        largest_ci = 0
        for row in layout:
            ci = 0
            if row:
                ri -= 1
                row = row.split(',')
                for cell in row:
                    ci += 1
                    if ci > largest_ci: largest_ci = ci
                    for char in cell:
                        if char == 'W':
                            objects.append((Wumpus(),(ci,ri)))
                        elif char == 'P':
                            objects.append((Pit(),(ci,ri)))
                        elif char == 'G':
                            objects.append((Gold(),(ci,ri)))
                        elif char == 'A':
                            entrance = (ci,ri)

        return objects, largest_ci, len(layout)-ri, entrance

    def tryToLoad(self, fullname):
        if (not os.path.exists(fullname)): return None
        f = open(fullname)
        try: return [line.strip() for line in f]
        finally: f.close()

    def step(self):
        self.env.step()
        print
        print "Current Wumpus Environment:"
        print self.env.to_string()

    def run(self, steps = 1000):
        print self.env.to_string()
        for step in range(steps):
            if self.env.is_done():
                print "DONE."
                slist = []
                if len(self.env.agents) > 0:
                    slist += ['Final Scores:']
                for agent in self.env.agents:
                    slist.append(' {0}={1}'.format(agent, agent.performance_measure))
                    if agent.verbose:
                        if hasattr(agent, 'number_of_clauses_over_epochs'):
                            print "number_of_clauses_over_epochs:" \
                                  +" {0}".format(agent.number_of_clauses_over_epochs)
                        if hasattr(agent, 'belief_loc_query_times'):
                            print "belief_loc_query_times:" \
                                  +" {0}".format(agent.belief_loc_query_times)
                print ''.join(slist)
                return
            self.step()

    def to_string(self):
        s = "Environment width={0}, height={1}\n".format(self.width, self.height)
        s += "Initial Position: {0}\n".format(self.entrance)
        s += "Actions: {0}\n".format(self.actions)
        return s

    def pprint(self):
        print self.to_string()
        print self.env.to_string()



#-------------------------------------------------------------------------------

def world_scenario_hybrid_wumpus_agent_from_layout(layout_filename):
    """
    Create WumpusWorldScenario with an automated agent_program that will
        try to solve the Hunt The Wumpus game on its own.
    layout_filename := name of layout file to load
    """
    return WumpusWorldScenario(layout_file = layout_filename,
                               agent = HybridWumpusAgent('north', verbose=True),
                               trace=False)

#------------------------------------
# examples of constructing HybridWumpusAgent scenario
# specifying objects as list

def wscenario_4x4_HybridWumpusAgent():
    return WumpusWorldScenario(agent = HybridWumpusAgent('north', verbose=True),
                               objects = [(Wumpus(),(1,3)),
                                          (Pit(),(3,3)),
                                          (Pit(),(3,1)),
                                          (Gold(),(2,3))],
                               width = 4, height = 4, entrance = (1,1),
                               trace=True)

#-------------------------------------------------------------------------------

def world_scenario_manual_with_kb_from_layout(layout_filename):
    """
    Create WumpusWorldScenario with a manual agent_program and Knowledge Base
        (see with_manual_kb_program)
    layout_filename := name of layout file to load
    """
    return WumpusWorldScenario(layout_file = layout_filename,
                               agent = with_manual_kb_program(HybridWumpusAgent('north',
                                                                                verbose=True)),
                               trace=False)

#------------------------------------
# examples of constructing manual wumpus agent with KB scenario
# specifying objects as list

def wscenario_4x4_manual_HybridWumpusAgent():
    return WumpusWorldScenario(agent = with_manual_kb_program(HybridWumpusAgent('north', verbose=True)),
                               objects = [(Wumpus(),(1,3)),
                                          (Pit(),(3,3)),
                                          (Pit(),(3,1)),
                                          (Gold(),(2,3))],
                               width = 4, height = 4, entrance = (1,1),
                               trace=True) 

Python Online Compiler

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Taking inputs (stdin)

OneCompiler's python online editor supports stdin and users can give inputs to programs using the STDIN textbox under the I/O tab. Following is a sample python program which takes name as input and print your name with hello.

import sys
name = sys.stdin.readline()
print("Hello "+ name)

About Python

Python is a very popular general-purpose programming language which was created by Guido van Rossum, and released in 1991. It is very popular for web development and you can build almost anything like mobile apps, web apps, tools, data analytics, machine learning etc. It is designed to be simple and easy like english language. It's is highly productive and efficient making it a very popular language.

Tutorial & Syntax help

Loops

1. If-Else:

When ever you want to perform a set of operations based on a condition IF-ELSE is used.

if conditional-expression
    #code
elif conditional-expression
    #code
else:
    #code

Note:

Indentation is very important in Python, make sure the indentation is followed correctly

2. For:

For loop is used to iterate over arrays(list, tuple, set, dictionary) or strings.

Example:

mylist=("Iphone","Pixel","Samsung")
for i in mylist:
    print(i)

3. While:

While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.

while condition  
    #code 

Collections

There are four types of collections in Python.

1. List:

List is a collection which is ordered and can be changed. Lists are specified in square brackets.

Example:

mylist=["iPhone","Pixel","Samsung"]
print(mylist)

2. Tuple:

Tuple is a collection which is ordered and can not be changed. Tuples are specified in round brackets.

Example:

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)

Below throws an error if you assign another value to tuple again.

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
myTuple[1]="onePlus"
print(myTuple)

3. Set:

Set is a collection which is unordered and unindexed. Sets are specified in curly brackets.

Example:

myset = {"iPhone","Pixel","Samsung"}
print(myset)

4. Dictionary:

Dictionary is a collection of key value pairs which is unordered, can be changed, and indexed. They are written in curly brackets with key - value pairs.

Example:

mydict = {
    "brand" :"iPhone",
    "model": "iPhone 11"
}
print(mydict)

Supported Libraries

Following are the libraries supported by OneCompiler's Python compiler

NameDescription
NumPyNumPy python library helps users to work on arrays with ease
SciPySciPy is a scientific computation library which depends on NumPy for convenient and fast N-dimensional array manipulation
SKLearn/Scikit-learnScikit-learn or Scikit-learn is the most useful library for machine learning in Python
PandasPandas is the most efficient Python library for data manipulation and analysis
DOcplexDOcplex is IBM Decision Optimization CPLEX Modeling for Python, is a library composed of Mathematical Programming Modeling and Constraint Programming Modeling