刚刚实现一个初始版本
1.TODO 仅仅能处理英文,下一步考虑unicode
似乎考虑多了,当前的程序处理中文文本是一样可以的。
2.TODO enocde ,decode,文本读写多重转换 int -> chr chr -> int -> bin
下一步直接读写int,能否直接读写bit?
3.TODO 其它方面考虑速度的优化,比如垃圾回收机制是否影响了速度等等,
和c/c++比python肯定没有速度优势,不过代码写起来比c/c++舒服多了,感觉python非常接近写伪码的感觉了,所想即所得,
一个问题只有一个解法,真正让你能够专注与算法与框架流程设计而不被语言本身所束缚。
5.TODO 设计成可以对一些文本一起压缩,全部解压缩或者对指定文本解压缩。
5.特别利用pygraphivz对huffman tree 进行了绘制,有利于调试。见前一篇随笔。
6.TODO 考虑其它压缩方法,如范式huffman 的实现。分词后对词编码而不是对字母编码的方法。
7.压缩过程中写文件遇到的一个问题,因为我只有到扫描处理完所有文件的字符a,b,c...才能计算出最后一个字节剩余了多少个bit,它们被补0,而计算好之后我希望把这个信息写到前面,即压缩文档开头序列化之后马上先记录最后一个byte补了多少个0,然后记录最后一个byte,然后从头到尾顺序记录所有其它被encode translate的byte,所以我先保持了原来的需要写的位置,当写到最后的时候,再把写指针指回,写那个位置,但是我在解压缩过程再读那个位置的时候发现最后的写操作并没有写成功。
self.infile.seek(0)
#save this pos we will write here later
pos = self.outfile.tell()
self.outfile.write(chr(0)) #store left bit
self.outfile.write(chr(0)) #if left bit !=0 this is the last byte
#.... translate other bytes
#just after the huffman tree sotre how many bits are left for last
#byte that is not used and filled with 0
self.outfile.seek(pos)
self.outfile.write(chr(leftBit)) #still wrong can't not read well
self.outfile.write(chr(num))
后来发现要再最后加一句self.outfile.flush()将内容写回硬盘,问题似乎是回写前面的位置,仅仅写到了cache中,最后file.close()的时候该cache的新内容也未被写回硬盘,不知道是不是python2.6的一个bug
反正最后加file.flush()就ok了。
当前流程
压缩过程:
读文本
计算各个字符的出现频率
建立huffman tree (二叉连表树实现,不需要parent域)
通过huffman tree 为每个字符编码(深度优先遍历huffman tree,即可得到所以字符编码)
将huffman tree 序列化写到输出文本(以便解压缩时恢复huffman tree,这里采用存储huffman tree 的前序序列,根据huffman tree的特性,每个内部节点均2度,可恢复)
再读文本,为每个字符通过dict 取出它的编码并且写到输出文本。
(注意写的时候集齐8个字符为一组,输出,但是最后一个byte可能不够8位,要用0补齐空位。
为了处理方便,我将在序列化的二叉树后面首先记录最后一个byte需要用0补齐的位数,如果需要补齐的位 数不为0,则接下来输出最后一个byte,然后再从输入文件内部头开始
编码输出到输出文件。这里的技巧就是把最后一个byte放到了前面,便于处理,否则解码可能最后文件尾部 会有多余字符被译出。)
解压缩过程:
读压缩好的文本
先读文件头部,根据huffman tree前序序列,恢复建立huffman tree,二叉链表树
继续读文本,根据huffman tree 进行解码,0向左,1向右,到叶节点,解码一个字符。
解码输出完成即完成解压缩。(注意我压缩的时候最后一个byte放到前面了,如果需要要
将其最后输出。)
当前程序用法
python2.6 huffman.py input.txt
输出
input.txt.compress 压缩文件
input.txt.compress.de 解压缩后的,内容应与input.txt一致。
allen:~/study/data_structure/huffman$ time python2.6 huffman.py C00-1052.txt
real
0m0.607s
user
0m0.536s
sys
0m0.060s
allen:~/study/data_structure/huffman$ diff C00-1052.txt C00-1052.txt.compress.de
allen:~/study/data_structure/huffman$ du -h C00-1052.txt
36K
C00-1052.txt
allen:~/study/data_structure/huffman$ du -h C00-1052.txt.compress.de
36K
C00-1052.txt.compress.de
allen:~/study/data_structure/huffman$ du -h C00-1052.txt.compress
24K
C00-1052.txt.compress
网上有不少关于huffman的实现,和我这里一样都是采用最简单的基本huffman算法。
做了下对比,采用《平凡的世界》1.7M, 似乎python的效率还不错,不过应该用更大
的压缩比率更大呢,应该压缩率一样的啊。
allen:~/study/data_structure/huffman$ time python2.6 huffman.py normal_world.log
real
0m32.236s
user
0m31.298s
sys
0m0.732s
allen:~/study/data_structure/huffman$ du -h normal_world.log
1.7M
normal_world.log
allen:~/study/data_structure/huffman$ du -h normal_world.log.compress
1.3M
normal_world.log.compress
allen:~/study/data_structure/huffman$ du -h normal_world.log.compress.de
1.7M
normal_world.log.compress.de
allen:~/study/data_structure/huffman$ diff normal_world.log normal_world.log.compress.de
原文件《平凡的世界》,大小1.7M,压缩后1.3M,解压缩后与原文件完全相同,压缩和解压缩共耗时32s
压缩效果
使用本程序对《平凡的世界》做压缩测试,压缩前为文本文件,大小为1.7M,压缩后为二进制文件,大小接近1M(988,817byte),而zip压缩后体积为920,997byte,比zip差,压缩文件存储格式待改善。另外,因为从Huffman压缩算法的原理可知,该算法对字符重复率高的文本最有效,比如长篇小说或者英文小说。
作者提到:
l 略大文件
test3.txt 《平凡的世界》
压缩前:1.62M
压缩后:1.39M
压缩率:86%
压缩时间14.23秒
解压时间 16.85秒
测试结果:压缩,解压成功!
压缩解压时间在可接受范围之内
1
'''
2
Create a huffman tree from
3
the input is a list like
4
[('a',3), ('b',2)]
5
frequnce of 'a' appeard is stored as it's weight
6
'''
7
from
Queue
import
PriorityQueue
8
#
if do not use treeWiter so not include pygraphviz than can use py3.0
9
from
treeWriter
import
TreeWriter
10
from
copy
import
copy
11
12
class
NodeBase():
13
def
__init__
(self):
14
self.weight
=
0
15
16
def
elem(self):
17
return
self.weight
18
19
class
Node(NodeBase):
20
def
__init__
(self, weight
=
0, left
=
None, right
=
None):
21
self.weight
=
weight
22
self.left
=
left
23
self.right
=
right
24
25
def
__str__
(self):
26
return
str(self.weight)
27
28
class
Leaf(NodeBase):
29
def
__init__
(self, key
=
''
, weight
=
0):
30
self.key
=
key
31
self.weight
=
weight
32
33
def
__str__
(self):
34
return
str(self.key)
35
36
37
def
convert(c):
38
'''
39
input c = 'a' ord(a) = 97
40
bin(97) = '0b1100001'
41
return ['0', '1', '1', '0', '0', '0', '0', '1']
42
'''
43
l1
=
list(bin(ord(c)))
#
like 0b11101
44
l2
=
[
'
0
'
]
*
(
10
-
len(l1))
45
l2.extend(l1[
2
:])
46
return
l2
47
48
class
HuffmanTree():
49
'''
50
base class for HuffmanTreeForCompress and HuffmanTreeForDecompress
51
'''
52
def
__init__
(self):
53
self.root
=
None
54
55
class
HuffmanTreeForCompress(HuffmanTree):
56
'''
57
create a huffman tree for the compressing process
58
here self.list like [('a',3),('b',4)] where 'a' is key, 3 is weight
59
or say frequence of 'a' appear in the text
60
'''
61
def
__init__
(self, list):
62
HuffmanTree.
__init__
(self)
63
self.list
=
list
#
like [('a',3),('b',4)]
64
self.dict
=
{}
#
like {'a':[0,1,1,0] , .}
65
66
self.
__buildTree
()
67
self.
__genEncode
()
68
69
def
__initPriorityQueue
(self, queue):
70
'''
71
init priority queue let lowest weight at top
72
'''
73
for
key, weight
in
self.list:
74
leaf
=
Leaf(key, weight)
75
queue.put((weight,leaf))
76
77
def
__buildTree
(self):
78
'''
79
build the huffman tree from the list of weight using prority queue
80
greedy alogrithm,choose two least frequence node first
81
'''
82
length
=
len(self.list)
83
queue
=
PriorityQueue(length)
84
self.
__initPriorityQueue
(queue)
85
#
while queue.qsize() > 1:
86
#
do len(self.list) - 1 times same as while queue.qsize() > 1
87
for
i
in
range(length
-
1
):
88
left
=
queue.get()[
1
]
89
right
=
queue.get()[
1
]
90
weight
=
left.weight
+
right.weight
91
node
=
Node(weight, left, right)
92
queue.put((weight,node))
93
self.root
=
queue.get()[
1
]
94
95
def
__genEncode
(self):
96
'''
97
get huffman encode for each key using depth first travel of tree
98
'''
99
def
genEncodeHelp(root, encode
=
[]):
100
if
isinstance(root, Leaf):
101
#
TODO notice need copy content here,why can't list(encode)?
102
self.dict[root.key]
=
copy(encode)
103
#
print self.dict[root.key]
104
return
105
encode.append(0)
106
genEncodeHelp(root.left, encode)
107
encode[len(encode)
-
1
]
=
1
108
genEncodeHelp(root.right, encode)
109
encode.pop()
110
genEncodeHelp(self.root)
111
112
113
class
HuffmanTreeForDecompress(HuffmanTree):
114
'''
115
rebuild of huffman tree for the decompressing process
116
'''
117
def
__init__
(self, infile):
118
HuffmanTree.
__init__
(self)
119
self.
__buildTree
(infile)
120
121
def
__buildTree
(self, infile):
122
def
buildTreeHelp(infile):
123
first
=
infile.read(
1
)
124
second
=
infile.read(
1
)
125
#
if not (first == '\xff' and second == '\xfe'): #is leaf
126
if
first
==
'
\x00
'
:
#
is leaf, not consider unicode now
127
return
Leaf(second)
128
node
=
Node()
129
node.left
=
buildTreeHelp(infile)
130
node.right
=
buildTreeHelp(infile)
131
return
node
132
infile.read(
2
)
133
self.root
=
Node()
134
self.root.left
=
buildTreeHelp(infile)
135
self.root.right
=
buildTreeHelp(infile)
136
137
class
Decompress():
138
def
__init__
(self, infileName, outfileName
=
''
):
139
#
TODO better name, expection of opening file
140
self.infile
=
open(infileName,
'
rb
'
)
141
if
outfileName
==
''
:
142
outfileName
=
infileName
+
'
.de
'
143
self.outfile
=
open(outfileName,
'
wb
'
)
144
self.tree
=
None
145
146
def
__del__
(self):
147
self.infile.close()
148
self.outfile.close()
149
150
def
decompress(self):
151
self.
__rebuildHuffmanTree
()
152
self.
__decodeFile
()
153
154
def
__rebuildHuffmanTree
(self):
155
self.infile.seek(0)
156
self.tree
=
HuffmanTreeForDecompress(self.infile)
157
#
HuffmanTreeWriter(self.tree).write('tree2.png') #for debug
158
159
def
__decodeFile
(self):
160
#
right now do not consier speed up using table
161
#
do not consider the last byte since it's wrong right now
162
163
#
TODO use a table as 0x00 -> 0000 0000 will speed up?
164
self.outfile.seek(0)
165
leftBit
=
ord(self.infile.read(
1
))
166
lastByte
=
self.infile.read(
1
)
#
it is the last byte if leftBit != 0
167
curNode
=
self.tree.root
168
#
import gc
169
#
gc.disable()
170
while
1
:
171
c
=
self.infile.read(
1
)
#
how about Chinese caracter? 2 bytes?
172
if
c
==
''
:
173
break
174
li
=
convert(c)
#
in c++ you can not return refernce to local in func here ok? yes
175
for
x
in
li:
176
if
x
==
'
0
'
:
177
curNode
=
curNode.left
178
else
:
179
curNode
=
curNode.right
180
if
isinstance(curNode, Leaf):
#
the cost of isinstance is higer than lkie root.left == None ?
181
self.outfile.write(curNode.key)
182
curNode
=
self.tree.root
183
184
185
#
deal with the last bye if leftBit != 0
186
#
TODO notcice code repeate can we improve?
187
if
leftBit:
188
li
=
convert(lastByte)
189
for
x
in
li:
190
if
x
==
'
0
'
:
191
curNode
=
curNode.left
192
else
:
193
curNode
=
curNode.right
194
if
isinstance(curNode, Leaf):
#
the cost of isinstance is higer than lkie root.left == None ?
195
self.outfile.write(curNode.key)
196
curNode
=
self.tree.root
197
break
#
for the last byte if we find one than it's over,the other bits are useless
198
199
self.outfile.flush()
200
#
gc.enable()
201
202
203
204
class
Compress():
205
def
__init__
(self, infileName, outfileName
=
''
):
206
self.infile
=
open(infileName,
'
rb
'
)
207
if
outfileName
==
''
:
208
outfileName
=
infileName
+
'
.compress
'
209
self.outfile
=
open(outfileName,
'
wb
'
)
210
self.dict
=
{}
211
self.tree
=
None
212
213
def
__del__
(self):
214
self.infile.close()
215
self.outfile.close()
216
217
def
compress(self):
218
self.
__caculateFrequence
()
219
self.
__createHuffmanTree
()
220
self.
__writeCompressedFile
()
221
222
def
__caculateFrequence
(self):
223
'''
224
The first time of reading the input file and caculate each
225
character frequence store in self.dict
226
'''
227
self.infile.seek(0)
228
while
1
:
229
c
=
self.infile.read(
1
)
#
how about Chinese caracter? 2 bytes?
230
if
c
==
''
:
231
break
232
#
print c
233
if
c
in
self.dict:
234
self.dict[c]
+=
1
235
else
:
236
self.dict[c]
=
0
237
238
def
__createHuffmanTree
(self):
239
'''
240
Build a huffman tree from self.dict.items()
241
'''
242
#
TODO for py 3.0 need list(self.dict.items()) instead
243
self.tree
=
HuffmanTreeForCompress(list(self.dict.items()))
244
#
HuffmanTreeWriter(self.tree).write('tree1.png') #for debug
245
246
def
__writeCompressedFile
(self):
247
'''
248
Create the compressed file
249
First write the huffman tree to the head of outfile
250
than translate the input file with encode and write the result to
251
outfile
252
'''
253
self.outfile.seek(0)
254
self.
__serializeTree
()
255
self.
__encodeFile
()
256
257
def
__serializeTree
(self):
258
'''
259
In order to write the tree like node node leaf node .
260
in pre order sequence to the compressed file head
261
here will return the sequence list
262
TODO reuse pre order and using decorator technic!!
263
list like [(0,0), (0,0), (1,'c')],
264
(0,0) the first 0 means internal node
265
(1,'c') the first 1 means leaf and 'c' is the key
266
'''
267
def
serializeTreeHelp(root, mfile):
268
if
isinstance(root, Leaf):
269
mfile.write(
'
\x00
'
)
#
0x0
270
mfile.write(root.key)
271
return
272
mfile.write(
'
\xff
'
)
#
'\xff' is one character representing 0xff
273
mfile.write(
'
\xfe
'
)
#
0xfe
274
serializeTreeHelp(root.left, mfile)
275
serializeTreeHelp(root.right, mfile)
276
serializeTreeHelp(self.tree.root, self.outfile)
277
278
279
def
__encodeFile
(self):
280
'''
281
The second time of reading input file
282
translate the input file with encode and write the result to outfile
283
TODO can this be improved speed up?
284
just write \xff as \b 1111 1111 ? can this be possible so do not need
285
to caculate 255 than translate to \xff and write?
286
'''
287
self.infile.seek(0)
288
#
save this pos we will write here later
289
pos
=
self.outfile.tell()
290
self.outfile.write(chr(0))
#
store left bit
291
self.outfile.write(chr(0))
#
if left bit !=0 this is the last byte
292
num
=
0
293
i
=
0;
294
while
1
:
295
c
=
self.infile.read(
1
)
#
how about Chinese caracter? 2 bytes?
296
if
c
==
''
:
297
break
298
li
=
self.tree.dict[c]
299
for
x
in
li:
300
num
=
(num
<<
1
)
+
x
301
i
+=
1
302
if
(i
==
8
):
303
self.outfile.write(chr(num))
304
num
=
0
305
i
=
0
306
#
for all left bit we will fill with 0,and fil finally save left bit
307
#
like the last is 11 wich has 6 bits left than will store the last
308
#
byte as 1100,0000
309
leftBit
=
(
8
-
i)
%
8
310
if
leftBit:
311
for
j
in
range(i,
8
):
312
num
=
(num
<<
1
)
313
314
#
just after the huffman tree sotre how many bits are left for last
315
#
byte that is not used and filled with 0
316
self.outfile.seek(pos)
317
self.outfile.write(chr(leftBit))
#
still wrong can't not read well
318
self.outfile.write(chr(num))
319
self.outfile.flush()
#
well need this, why? remember !!!!
320
#
self.outfile.seek(0,2) #will not write success without this a bug???
321
#
print self.outfile.read(1)
322
323
324
325
#
def test(self):
326
#
for k, v in self.dict.items():
327
#
print k
328
#
print v
329
330
331
class
HuffmanTreeWriter(TreeWriter):
332
'''
333
draw a huffman tree to tree.png or user spcified file
334
For huffman debug only
335
'''
336
def
writeHelp(self, root, A):
337
p
=
str(self.num)
338
self.num
+=
1
339
340
if
isinstance(root, Leaf):
341
key
=
root.key
#
TODO '\n' wrong to fix
342
#
key.replace('\n', '\\n')
343
#
A.add_node(p, label = str(root.elem()) + r'\n' + key, shape = 'rect')
344
A.add_node(p, label
=
str(root.elem())
+
r
'
\n
'
, shape
=
'
rect
'
)
345
return
p
346
347
#
if not a leaf for huffman tree it must both have left and right child
348
A.add_node(p, label
=
str(root.elem()))
349
350
q
=
self.writeHelp(root.left, A)
351
A.add_node(q, label
=
str(root.left.elem()))
352
A.add_edge(p, q, label
=
'
0
'
)
353
354
r
=
self.writeHelp(root.right, A)
355
A.add_node(r, label
=
str(root.right.elem()))
356
A.add_edge(p, r, label
=
'
1
'
)
357
358
l
=
str(self.num2)
359
self.num2
-=
1
360
A.add_node(l, style
=
'
invis
'
)
361
A.add_edge(p, l, style
=
'
invis
'
)
362
B
=
A.add_subgraph([q, l, r], rank
=
'
same
'
)
363
B.add_edge(q, l, style
=
'
invis
'
)
364
B.add_edge(l, r, style
=
'
invis
'
)
365
366
return
p
#
return key root node
367
368
369
370
371
if
__name__
==
'
__main__
'
:
372
#
d = [chr(ord('a')+i) for i in range(13)]
373
#
w = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
374
#
list = []
375
#
for i in range(13):
376
#
list.append((d[i], w[i]))
377
#
print(list)
378
#
tree = HuffmanTreeForCompress(list)
379
#
writer = HuffmanTreeWriter(tree)
380
#
writer.write()
381
#
tree.test()
382
import
sys
383
if
len(sys.argv)
==
1
:
384
inputFileName
=
'
test.log
'
385
else
:
386
inputFileName
=
sys.argv[
1
]
387
compress
=
Compress(inputFileName)
388
compress.compress()
389
390
decompress
=
Decompress(inputFileName
+
'
.compress
'
)
391
decompress.decompress()
392
393
#
compress.test()
394