Do this in python only, import the modules below first before doing anything Sorter.py: import random import enum from abc import ABC, abstractmethod from priorityqueue.HeapPriorityQueue import HeapPriorityQueue class SortingALgorithm(enum.Enum): PR_Queue = 1 SortedPriorityQueue = 2 UnSortedPriorityQueue =3 class Sorter(ABC): @abstractmethod def sort(self) -> list: """in strategy pattern naming, this is method execute""" pass class PR_queue_sorter(Sorter): """ Heap sort Sorting according to the algorithm on slide #10 using a heap implementation of priority queue""" def __init__(self): self._q = HeapPriorityQueue() def sort(self, seq:list): i = 0 while len(seq) > 0: self._q.add(seq[0], None) del seq[0] while not self._q.is_empty(): k,v =self._q.remove_min() seq.append(k) return seq class Context: def __init__(self, sorting_algo:SortingALgorithm): if sorting_algo == SortingALgorithm.PR_Queue: self._sorter = PR_queue_sorter() def strategy(self): """ The Context maintains a reference to one of the Strategy objects. The Context does not know the concrete class of a strategy. It should work with all strategies via the Strategy interface. In our example: Strategy interface: Sorter Strategy objects: PR_Queue, """ return self._strategy def strategy(self, sorter: Sorter) -> None: """ Usually, the Context allows replacing a Strategy object at runtime. """ self._sorter = sorter def sort(self, seq:list): return self._sorter.sort(seq) # delegation if __name__ == "__main__": l1 = [random.randint(0, 100) for i in range(5)] print(l1) c = Context(SortingALgorithm.PR_Queue) l1 = c.sort(l1) print(l1) #you can use the same strategy more than once l2 = [random.randint(0, 100) for i in range(10)] print(l2) c = Context(SortingALgorithm.PR_Queue) l2 = c.sort(l2) print(l2)
Do this in python only, import the modules below first before doing anything
Sorter.py:
import random
import enum
from abc import ABC, abstractmethod
from priorityqueue.HeapPriorityQueue import HeapPriorityQueue
class SortingALgorithm(enum.Enum):
PR_Queue = 1
SortedPriorityQueue = 2
UnSortedPriorityQueue =3
class Sorter(ABC):
@abstractmethod
def sort(self) -> list:
"""in strategy pattern naming, this is method execute"""
pass
class PR_queue_sorter(Sorter):
""" Heap sort Sorting according to the algorithm on slide #10 using a heap implementation
of priority queue"""
def __init__(self):
self._q = HeapPriorityQueue()
def sort(self, seq:list):
i = 0
while len(seq) > 0:
self._q.add(seq[0], None)
del seq[0]
while not self._q.is_empty():
k,v =self._q.remove_min()
seq.append(k)
return seq
class Context:
def __init__(self, sorting_algo:SortingALgorithm):
if sorting_algo == SortingALgorithm.PR_Queue:
self._sorter = PR_queue_sorter()
def strategy(self):
""" The Context maintains a reference to one of the Strategy objects. The
Context does not know the concrete class of a strategy. It should work
with all strategies via the Strategy interface.
In our example: Strategy interface: Sorter
Strategy objects: PR_Queue,
"""
return self._strategy
def strategy(self, sorter: Sorter) -> None:
"""
Usually, the Context allows replacing a Strategy object at runtime.
"""
self._sorter = sorter
def sort(self, seq:list):
return self._sorter.sort(seq) # delegation
if __name__ == "__main__":
l1 = [random.randint(0, 100) for i in range(5)]
print(l1)
c = Context(SortingALgorithm.PR_Queue)
l1 = c.sort(l1)
print(l1)
#you can use the same strategy more than once
l2 = [random.randint(0, 100) for i in range(10)]
print(l2)
c = Context(SortingALgorithm.PR_Queue)
l2 = c.sort(l2)
print(l2)
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