hafuman编码python

很抱歉，作为AI语言模型，我不能调用第三方库来实现哈夫曼编码。不过，下面的代码可以帮助你理解哈夫曼编码的实现过程：

from queue import PriorityQueue  
#优先队列用于实现哈夫曼树的构建

class Node:  
    def __init__(self, value):  
        self.left = None  
        self.right = None  
        self.value = value  
        self.frequency = 1  

    def __lt__(self, other):  
        return self.frequency < other.frequency  
    #用于比较节点的频率

def build_huffman_tree(data):  
    q = PriorityQueue()  
    freq_dict = {}  #建立字符和频率的映射

    for term in data:  
        if term in freq_dict:  
            freq_dict[term] += 1  
        else:  
            freq_dict[term] = 1  

    for key in freq_dict:  
        q.put(Node(key))  

    while q.qsize() > 1:  
        node1 = q.get()  
        node2 = q.get()  
        new_node = Node(None)  
        new_node.left = node1  
        new_node.right = node2  
        new_node.frequency = node1.frequency + node2.frequency  
        q.put(new_node)  

    return q.get()  
    #返回根节点

def encode_data(root, data):  
    encoding_dict = {}  #建立字符和编码的映射
    get_encoding(root, encoding_dict, "")  
    encoded_data = ""  

    for term in data:  
        encoded_data += encoding_dict[term]  

    return encoded_data  

def get_encoding(node, encoding_dict, code):  
    if node is None:  
        return  

    if node.value is not None:  
        encoding_dict[node.value] = code  

    get_encoding(node.left, encoding_dict, code + "0")  
    get_encoding(node.right, encoding_dict, code + "1")  
    #递归获得字符对应的编码

def decode_data(root, encoded_data):  
    original_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.value is not None:  
            original_data += current_node.value  
            current_node = root  

    return original_data  
    #根据编码还原原始数据