python 霍夫曼编码的代码，最好是可以import的

霍夫曼编码是一种基于字符频率自适应的前缀编码算法，常用于数据压缩。在Python中，我们可以使用`collections`模块结合字典和堆来实现霍夫曼树及其编码过程。下面是一个简单的霍夫曼编码生成器的例子：

from heapq import heapify, heappush, heappop
import collections

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

def build_huffman_tree(freqs):
    huffman_tree = []
    for char, freq in freqs.items():
        node = Node(char, freq)
        heapify(huffman_tree)
        heappush(huffman_tree, node)

    while len(huffman_tree) > 1:
        left = heappop(huffman_tree)
        right = heappop(huffman_tree)
        
        combined = Node(None, left.freq + right.freq)
        combined.left, combined.right = left, right
        
        heappush(huffman_tree, combined)
    
    return heappop(huffman_tree)

def generate_code(node, code='', codes={}):
    if node is None or node.char is not None:
        codes[node.char] = code
        return
    
    generate_code(node.left, code + '0', codes)
    generate_code(node.right, code + '1', codes)

def huffman_encoding(data, tree):
    encoded_data = ''
    for char in data:
        encoded_data += tree[char]
    return encoded_data, codes

# 示例用法
freq_dict = {'a': 45, 'b': 15, 'c': 20}  # 假设这是输入文本的字符频率
huff_tree = build_huffman_tree(freq_dict)
encoded_data, codes = huffman_encoding('abcabcc', huff_tree)

print(f"Huffman Codes: {codes}")
print(f"Encoded Data: {encoded_data}")