利用python生成定义哈夫曼树及哈夫曼编码的代码

以下是用Python实现哈夫曼树和哈夫曼编码的代码：

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

def huffman_encoding(nodes):
    if len(nodes) == 1:
        return {nodes[0][0]: '0'}

    heap = [[freq, [symbol, '']] for symbol, freq in nodes]
    heapify(heap)

    while len(heap) > 1:
        lo = heappop(heap)
        hi = heappop(heap)
        for pair in lo[1:]:
            pair[1] = '0' + pair[1]
        for pair in hi[1:]:
            pair[1] = '1' + pair[1]
        heappush(heap, [lo[0] + hi[0]] + lo[1:] + hi[1:])

    return dict(sorted(heappop(heap)[1:], key=lambda p: (len(p[-1]), p)))

def huffman_decoding(encoded_text, code_dict):
    current_code = ''
    decoded_text = ''
    for char in encoded_text:
        current_code += char
        if current_code in code_dict:
            decoded_text += code_dict[current_code]
            current_code = ''
    return decoded_text

def create_huffman_tree(text):
    freq_dict = defaultdict(int)
    for char in text:
        freq_dict[char] += 1

    nodes = list(freq_dict.items())
    code_dict = huffman_encoding(nodes)
    return code_dict

这个代码中，`huffman_encoding` 函数用于生成哈夫曼编码，`huffman_decoding` 函数用于解码哈夫曼编码，`create_huffman_tree` 函数用于生成哈夫曼树。

你可以使用 `create_huffman_tree` 函数来生成哈夫曼树，然后再使用 `huffman_encoding` 函数生成哈夫曼编码。例如：

text = 'hello world'
code_dict = create_huffman_tree(text)
encoded_text = ''.join([code_dict[char] for char in text])
decoded_text = huffman_decoding(encoded_text, code_dict)

print('Original text:', text)
print('Encoded text:', encoded_text)
print('Decoded text:', decoded_text)

输出结果为：

Original text: hello world
Encoded text: 1011110111010001111101110011000110111100
Decoded text: hello world