 from poodle import Object, schedule
from typing import Set

class Position(Object):
    def __str__(self):
        if not hasattr(self, "locname"): return "unknown"
        return self.locname
class HasHeight(Object):
    height: int
class HasPosition(Object):
    at: Position
class Monkey(HasHeight, HasPosition): pass
class PalmTree(HasHeight, HasPosition): 
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.height = 2
class Box(HasHeight, HasPosition): pass
class Banana(HasHeight, HasPosition): 
    owner: Monkey
    attached: PalmTree 
class World(Object):
    locations: Set[Position]


p1 = Position()
p1.locname = "Position A"
p2 = Position()
p2.locname = "Position B"
p3 = Position()
p3.locname = "Position C"

w = World()
w.locations.add(p1)
w.locations.add(p2)
w.locations.add(p3)

m = Monkey()
m.height = 0 # ground
m.at = p1

box = Box()
box.height = 2
box.at = p2

p = PalmTree()
p.at = p3

b = Banana()
b.attached = p

def go(monkey: Monkey, where: Position):
    assert where in w.locations
    assert monkey.height < 1, "Monkey can only move while on the ground"
    monkey.at = where
    return f"Monkey moved to {where}"

def push(monkey: Monkey, box: Box, where: Position):
    assert monkey.at == box.at
    assert where in w.locations
    assert monkey.height < 1, "Monkey can only move the box while on the ground"
    monkey.at = where
    box.at = where
    return f"Monkey moved box to {where}"

def climb_up(monkey: Monkey, box: Box):
    assert monkey.at == box.at
    monkey.height += box.height
    return "Monkey climbs the box"

def grasp(monkey: Monkey, banana: Banana):
    assert monkey.height == banana.height
    assert monkey.at == banana.at
    banana.owner = monkey
    return "Monkey takes the banana"

def infer_owner_at(palmtree: PalmTree, banana: Banana):
    assert banana.attached == palmtree
    banana.at = palmtree.at
    return "Remembered that if banana is on palm tree, its location is where palm tree is"

def infer_banana_height(palmtree: PalmTree, banana: Banana):
    assert banana.attached == palmtree
    banana.height = palmtree.height
    return "Remembered that if banana is on the tree, its height equals tree's height"

print('\n'.join(x() for x in schedule(
          [go, push, climb_up, grasp, infer_banana_height, infer_owner_at],
          [w,p1,p2,p3,m,box,p,b],
          goal=lambda: b.owner == m)))

created 3 years ago by Siddhant Jain

Python Online Compiler

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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

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