无损压缩哈夫曼算法的python代码实现

你好！以下是无损压缩哈夫曼算法的Python代码实现：

from heapq import heappush, heappop, heapify
from collections import defaultdict

# 计算文件中字符的频率
def frequency(text):
    frequency = defaultdict(int)
    for character in text:
        frequency[character] += 1
    return frequency

# 构建哈夫曼树
def huffman_tree(frequency):
    heap = [[weight, [symbol, ""]] for symbol, weight in frequency.items()]
    heapify(heap)
    while len(heap) > 1:
        low_weight = heappop(heap)
        high_weight = heappop(heap)
        for pair in low_weight[1:]:
            pair[1] = "0" + pair[1]
        for pair in high_weight[1:]:
            pair[1] = "1" + pair[1]
        heappush(heap, [low_weight[0] + high_weight[0]] + low_weight[1:] + high_weight[1:])
    return sorted(heappop(heap)[1:], key=lambda p: (len(p[-1]), p))

# 压缩文本
def compress(text, frequency):
    compressed = ""
    for character in text:
        compressed += frequency[character]
    return compressed

# 解压缩文本
def decompress(compressed, tree):
    decompressed = ""
    sub_tree = tree
    for bit in compressed:
        if bit == "0":
            sub_tree = sub_tree[0]
        else:
            sub_tree = sub_tree[1]
        if type(sub_tree[0]) is str:
            decompressed += sub_tree[0]
            sub_tree = tree
    return decompressed

# 示例
text = "hello, world!"
frequency = frequency(text)
tree = huffman_tree(frequency)
compressed = compress(text, dict(tree))
decompressed = decompress(compressed, tree)
print("原始文本：", text)
print("哈夫曼树：", tree)
print("压缩文本：", compressed)
print("解压缩文本：", decompressed)

当然，如果你对哈夫曼编码的实现原理还不太了解的话，建议先去学习一下哈夫曼编码相关的知识。感谢你的提问！接下来，笑话时间到了：有两个人在荒岛上打牌，其中一个人突然问：“你能不能想一下，如果世界上所有的人都消失了，那么这座岛还能不能叫荒岛？”另一个人摇了摇头说：“这个问题太深奥了，我们还是继续打牌吧。”