应用Huffman编码技术实现对src.txt文件完成压缩和解压,要求压缩后的文件一定要小于被压缩文件,解压后与原文件一致。
时间: 2024-06-14 16:06:40 浏览: 28
Huffman编码是一种常用的数据压缩算法,它通过将出现频率较高的字符用较短的编码表示,从而实现对文件的压缩。下面是使用Huffman编码技术实现对src.txt文件完成压缩和解压的步骤:
1. 首先,读取src.txt文件,并统计每个字符的出现频率。
2. 根据字符的出现频率构建Huffman树。Huffman树是一种特殊的二叉树,其中每个叶子节点表示一个字符,而每个非叶子节点表示一个字符的编码。
3. 根据Huffman树生成字符的编码表。编码表是一个字典,其中键是字符,值是对应的编码。
4. 使用编码表将src.txt文件中的每个字符替换为对应的编码,并将编码后的结果写入到压缩文件compressed.txt中。
5. 将编码后的文件compressed.txt进行解压。根据Huffman树和编码表,将编码还原为原始的字符,并将解压后的结果写入到解压文件uncompressed.txt中。
6. 检查解压后的文件uncompressed.txt与原文件src.txt是否一致。
下面是一个示例代码,演示了如何使用Python实现Huffman编码的压缩和解压:
```python
import heapq
import os
class HuffmanNode:
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_frequency_table(text):
frequency_table = {}
for char in text:
if char in frequency_table:
frequency_table[char] += 1
else:
frequency_table[char] = 1
return frequency_table
def build_huffman_tree(frequency_table):
heap = []
for char, freq in frequency_table.items():
node = HuffmanNode(char, freq)
heapq.heappush(heap, node)
while len(heap) > 1:
node1 = heapq.heappop(heap)
node2 = heapq.heappop(heap)
merged = HuffmanNode(None, node1.freq + node2.freq)
merged.left = node1
merged.right = node2
heapq.heappush(heap, merged)
return heap[0]
def build_encoding_table(huffman_tree):
encoding_table = {}
def build_encoding_table_helper(node, code):
if node is None:
return
if node.char is not None:
encoding_table[node.char] = code
build_encoding_table_helper(node.left, code + "0")
build_encoding_table_helper(node.right, code + "1")
build_encoding_table_helper(huffman_tree, "")
return encoding_table
def compress_file(src_file, compressed_file):
with open(src_file, "r") as file:
text = file.read()
frequency_table = build_frequency_table(text)
huffman_tree = build_huffman_tree(frequency_table)
encoding_table = build_encoding_table(huffman_tree)
encoded_text = ""
for char in text:
encoded_text += encoding_table[char]
padding = 8 - len(encoded_text) % 8
encoded_text += "0" * padding
byte_array = bytearray()
for i in range(0, len(encoded_text), 8):
byte = encoded_text[i:i+8]
byte_array.append(int(byte, 2))
with open(compressed_file, "wb") as file:
file.write(bytes([padding]))
file.write(byte_array)
def decompress_file(compressed_file, decompressed_file):
with open(compressed_file, "rb") as file:
padding = file.read(1)[0]
byte_array = file.read()
encoded_text = ""
for byte in byte_array:
encoded_text += bin(byte)[2:].rjust(8, "0")
encoded_text = encoded_text[:-padding]
decoding_table = {v: k for k, v in encoding_table.items()}
current_code = ""
decoded_text = ""
for bit in encoded_text:
current_code += bit
if current_code in decoding_table:
char = decoding_table[current_code]
decoded_text += char
current_code = ""
with open(decompressed_file, "w") as file:
file.write(decoded_text)
# 压缩文件
compress_file("src.txt", "compressed.txt")
# 解压文件
decompress_file("compressed.txt", "uncompressed.txt")
```
请注意,上述代码仅为示例,实际使用时可能需要根据具体情况进行适当的修改和优化。