Question

这是我在python中实现的MinHeap和MaxHeap。这使用比较器来反转MaxHeap中的存储顺序

import heapq


class MinHeap:
    def __init__(self):
        self.heap = []

    def push(self, item):
        heapq.heappush(self.heap, item)

    def pop(self):
        return heapq.heappop(self.heap)

    def peek(self):
        return self.heap[0]

    def __getitem__(self, item):
        return self.heap[item]

    def __len__(self):
        return len(self.heap)


class MaxHeap(MinHeap):
    def push(self, item):
        heapq.heappush(self.heap, Comparator(item))

    def pop(self):
        return heapq.heappop(self.heap)

    def peek(self):
        return self.heap[0]

    def __getitem__(self, i):
        return self.heap[i].val


class Comparator:
    def __init__(self, val):
        self.val = val

    def __lt__(self, other):
        return self.val > other

    def __eq__(self, other):
        return self.val == other




if __name__ == '__main__':
    max_heap = MaxHeap()
    max_heap.push(12)
    max_heap.push(3)
    max_heap.push(17)
    print(max_heap.pop())

MinHeap似乎工作正常，但是MaxHeap会抛出以下错误。

<__main__.Comparator object at 0x10a5c1080>

我似乎很难理解我在这里做错了什么。有人可以帮我这个。

Answer 1

我已将__repr__和__gt__方法添加到您的Comparator类，因此代码现已运行，Comparator个实例会在val个实例显示Comparator时打印。

重要的是让这些比较方法在两个MaxHeap个实例之间正确进行比较。

您会注意到我已从MinHeap中删除了大部分方法。它们不是必需的，因为从MaxHeap继承的方法可以正常工作。您可能希望将此版本恢复为def __getitem__(self, i): return self.heap[i].val

MaxHeap

取决于您打算如何使用import heapq class MinHeap: def __init__(self): self.heap = [] def push(self, item): heapq.heappush(self.heap, item) def pop(self): return heapq.heappop(self.heap) def peek(self): return self.heap[0] def __getitem__(self, item): return self.heap[item] def __len__(self): return len(self.heap) class MaxHeap(MinHeap): def push(self, item): heapq.heappush(self.heap, Comparator(item)) class Comparator: def __init__(self, val): self.val = val def __lt__(self, other): return self.val > other.val def __eq__(self, other): return self.val == other.val def __repr__(self): return repr(self.val) if __name__ == '__main__': max_heap = MaxHeap() max_heap.push(12) max_heap.push(3) max_heap.push(17) while True: try: print(max_heap.pop()) except IndexError: # The heap's empty, bail out break。

17
12
3

<强>输出

Comparator

给Comparator全套丰富的比较方法可能是一个好主意。它们不需要使上述代码有效，但它们将使def __lt__(self, other): return self.val > other.val def __le__(self, other): return self.val >= other.val def __gt__(self, other): return self.val < other.val def __ge__(self, other): return self.val <= other.val def __eq__(self, other): return self.val == other.val def __ne__(self, other): return self.val != other.val实例更加灵活。所以如果你想要它们，这里它们是：

const express = require('express');
const mongoose = require('mongoose');
const Post = require('./models/Post');
const keys = require('./config/keys');
const path = require('path');

mongoose.connect(keys.mongoURI);

const app = express();

app.use(express.static(path.join(__dirname, '../react-app/build')));

app.get('/', (req, res) => {
   res.sendFile(path.join(__dirname, '../react-app/build', 
 'index.html'));
});

app.get('/posts', (req, res) => {
   Post.find({}, (err, posts) => {
     if(err) {
       console.log(err);
       res.sendStatus(500);
     } else {
       res.send(posts)
     }  

   })
 });

 const PORT = process.env.PORT || 5000;
 app.listen(PORT, () => console.log(`App listening on port ${PORT}`));

Python中的最小/最大堆实现

1 个答案: