哈夫曼树python实现

哈夫曼树是一种用于数据压缩的树形结构，它通过将出现频率较高的字符用较短的编码表示，从而实现数据的高效压缩。下面是哈夫曼树的Python实现示例：

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

def build_huffman_tree(data):
    # 统计字符频率
    freq_map = {}
    for char in data:
        if char in freq_map:
            freq_map[char] += 1
        else:
            freq_map[char] = 1

    # 构建叶子节点列表
    nodes = []
    for char, freq in freq_map.items():
        nodes.append(Node(freq, char))

    # 构建哈夫曼树
    while len(nodes) > 1:
        nodes.sort(key=lambda x: x.freq)
        left = nodes.pop(0)
        right = nodes.pop(0)
        parent = Node(left.freq + right.freq)
        parent.left = left
        parent.right = right
        nodes.append(parent)

    return nodes[0]

def encode_huffman_tree(root, prefix="", code_map={}):
    if root.char is not None:
        code_map[root.char] = prefix
    else:
        encode_huffman_tree(root.left, prefix + "0", code_map)
        encode_huffman_tree(root.right, prefix + "1", code_map)

    return code_map

def huffman_encoding(data):
    root = build_huffman_tree(data)
    code_map = encode_huffman_tree(root)
    encoded_data = ""
    for char in data:
        encoded_data += code_map[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.char is not None:
            decoded_data += current_node.char
            current_node = root

    return decoded_data

以上是一个简单的哈夫曼树的Python实现。你可以使用`huffman_encoding`函数对数据进行编码，使用`huffman_decoding`函数对编码后的数据进行解码。