利用python贪心法求解哈夫曼编码问题。 设要编码的字符集为{d1， d2， …， dn}，它们出现的频率为{w1， w2， …， wn}，应用哈夫曼树构造最优的不等长的由0、1构成的编码方案，并输出哈夫曼树

好的，下面是 Python 代码实现：

class Node:
    def __init__(self, freq, symbol, left=None, right=None):
        self.freq = freq
        self.symbol = symbol
        self.left = left
        self.right = right

    def __lt__(self, other):
        return self.freq < other.freq

    def __eq__(self, other):
        if(other == None):
            return False
        if(not isinstance(other, Node)):
            return False
        return self.freq == other.freq


def buildHuffmanTree(freq_dict):
    pq = []
    for key in freq_dict:
        pq.append(Node(freq_dict[key], key))

    while(len(pq) > 1):
        node1 = heappop(pq)
        node2 = heappop(pq)
        merged_node = Node(node1.freq + node2.freq, None, node1, node2)
        heappush(pq, merged_node)

    return heappop(pq)


def huffman_encoding(root, current_code, codes):
    if(root == None):
        return

    if(root.symbol != None):
        codes[root.symbol] = current_code
        return

    huffman_encoding(root.left, current_code + "0", codes)
    huffman_encoding(root.right, current_code + "1", codes)


def huffman_encoding_helper(data):
    freq_dict = {}
    for char in data:
        if char in freq_dict:
            freq_dict[char] += 1
        else:
            freq_dict[char] = 1

    root = buildHuffmanTree(freq_dict)
    codes = {}
    huffman_encoding(root, "", codes)
    return codes, root


def huffman_encoding(data):
    if(len(data) == 0):
        return "", None
    codes, root = huffman_encoding_helper(data)
    encoded_data = ""
    for char in data:
        encoded_data += codes[char]
    return encoded_data, root


def huffman_decoding(encoded_data, root):
    decoded_data = ""
    current_node = root
    for bit in encoded_data:
        if(bit == '0'):
            current_node = current_node.left
        else:
            current_node = current_node.right

        if(current_node.symbol != None):
            decoded_data += current_node.symbol
            current_node = root

    return decoded_data

其中，`buildHuffmanTree()` 函数用于构建哈夫曼树，`huffman_encoding()` 函数用于对数据进行编码，`huffman_decoding()` 函数用于对编码后的数据进行解码。