压缩此数据的更快方法是什么？

Question

我有一个程序可以计算大量数据并将其写入文件。我的数据只是一堆 0-16 的数字（17 个不同的值），我计算了每个数字在数据中出现的频率。我需要使用尽可能少的磁盘空间和尽可能少的 RAM，所以我在纯 python 中编写了一个小的 Huffman 编码/解码模块，它一次在内存中用尽可能少的编码符号写入/读取压缩数据。是否有 python 附带的模块可以做类似的事情？下面是代码以及如何使用它的一些示例（警告代码有点长得体面的评论）：

def makeTree(data):
    """data is a list of tuples, whos first entry is a priority/frequency
    number, and whos second entry is tuple containing the data to
    be encoded. The tree uses an internal tag system to tell where the
    branch ends. (End nodes are terminated with a False)"""
    def tag(data):
        taggedData = []
        for priority, datum in data:
            #all of the initial data is an end branch
            taggedData += [(priority, (datum, False))]
        return taggedData
    #get the tagged data into decending order of priority/frequency
    tree = sorted(tag(data), reverse=True)
    while len(tree)>1:
        #get the two lowest priority branches
        bottomR, bottomL = tree.pop(), tree.pop()
        #and stick them together into a new branch with combined priority
        new_elem = bottomR[0]+bottomL[0], ((bottomL, bottomR), True)
        #then add them back to the list of branches and sort
        tree += [new_elem]
        tree.sort(reverse=True)
    return tree[0]

def makeTable(tree, code=""):
    """Takes a tree such as generated by makeTree and returns a dictionary
    of code:value pairs."""
    #if this is an end branch, return code:value pair
    if tree[1][1]==False:
        return {code:tree[1][0]}
    #otherwise find the tables for the left and right branches
    #add them to the main table, and return
    table = {}
    table.update(makeTable(tree[1][0][0], code+'0')) #left
    table.update(makeTable(tree[1][0][1], code+'1')) #right
    return table

class Decoder:
    """this class creates a Decoder object which is used to decode a compressed
    file using the appropriate decoding table (duh). It used to be a function,
    but it was buggy and would also be ugly if I left it a function. (this
    class was written After the Encdoer class.)
    """
    def __init__(self, fname, table):
        self.file = open(fname)
        self.table = table
        self.byte = None
        self.bit = 7
        self.newByte = True

    def decode(self, size=1):
        """Decodes and yields size number of symbols from the file.
        Size defaults to 1"""
        #a counter for how many symbols were read
        read = 0
        code = ''
        while read<size:
            if self.newByte:
                self.byte = ord(self.file.read(1))
            for n in xrange(self.bit, -1, -1):
                code += str((self.byte & 1<<n) >> n)
                self.byte &= (1<<n)-1
                if code in self.table:
                    yield self.table[code]
                    read += 1
                    code = ''
                    if read==size:
                        self.bit = n-1
                        self.newByte = False
                        raise StopIteration
            self.bit = 7
            self.newByte = True

    def close(self):
        self.file.close()

class Encoder:
    """This class creates an encoder object, which is used to write encoded data
    to a file. It was initially going to be a function, but I couldn't
    accomplish that without code getting really ugly. :p """
    def __init__(self, fname, table):
        self.file = open(fname, 'w')
        self.table = table
        self.code = ''

    def encode(self, datum):
        """Attempts to write encoded datum to file. If their isn't enough
        code to write a whole number amount of bytes, then the code is saved up
        until there is."""
        self.code += self.table[datum]
        if len(self.code)%8==0:
            self.__write_code_chunk()
        return

    def end_encode(self):
        """Writes any remaining code to the file, appending the code with
        trailing zeros to fit within a byte, then closes the file."""
        #if the length of the code remaining isn't a multiple of 8 bits
        if len(self.code)%8:
            #then add zeros to the end so that it is
            self.code += "0"*(8 - len(self.code)%8)
        self.__write_code_chunk()
        self.file.close()
        return

    def __write_code_chunk(self):
        bytes = len(self.code)/8
        #for every byte (or every 8 bits)...
        for _ in xrange(bytes):
            #turn those bits into an number using int with base 2,
            #then turn the number into an ascii character,
            #and finally write the data to the file.
            self.file.write(chr(int(self.code[:8], 2)))
            #then get rid of the 8 bits just read
            self.code = self.code[8:]
        #make sure there is no code left over
        assert self.code==''
        return

if __name__=="__main__":
    import random

    mandelbrotData = [
        (0.10776733333333334, 0),
        (0.24859, 1),
        (0.12407666666666667, 2),
        (0.07718866666666667, 3),
        (0.04594733333333333, 4),
        (0.03356, 5),
        (0.023286666666666664, 6),
        (0.018338, 7),
        (0.014030666666666667, 8),
        (0.011918, 9),
        (0.009500666666666668, 10),
        (0.008396666666666667, 11),
        (0.006936, 12),
        (0.006365999999999999, 13),
        (0.005466, 14),
        (0.0048920000000000005, 15),
        (0.2537393333333333, 16)]
    decode_table = makeTable(makeTree(mandelbrotData))
    encode_table = {val:key for key, val in decode_table.iteritems()}
    approx_data = sum([[val]*int(round(freq*10**3/2)) for freq, val in mandelbrotData], [])
    random.shuffle(approx_data)

    testname = 'hufftest'
    encoder = Encoder(testname, encode_table)

    for val in approx_data:
        encoder.encode(val)
    encoder.end_encode()

    decoder = Decoder(testname, decode_table)
    decoded = list(decoder.decode(len(approx_data)/2))
    decoded += list(decoder.decode(len(approx_data)/2))
    print approx_data == decoded

有没有一个模块可以更快地完成类似的事情？如果没有，有什么方法可以更改我的代码以使其更快？

Answer 1

• 在内存中，相同值的不同出现只用完一个位置。但重复提及它们。
• 对于磁盘存储，我可能只是用zlib 压缩它。

Answer 2

如果您的数据明显重复，那么您可能只想尝试对它进行游程编码，这可能是一个相对较快的操作。这是一个作为生成器的实现，它可以帮助最小化其整体内存使用量。请注意，当运行时间很短时，它只输出值而不是 (repeat-count,value) 元组，以避免输出膨胀并可能使其比原来更长。

from itertools import groupby

def run_length_encode(data):
    for value, igroup in groupby(data):
        repeat_count = len(list(igroup))
        yield value if repeat_count == 1 else repeat_count, value

if __name__ == '__main__':
    """ generate some random data with repeats and encode it """
    import random

    DATA_SIZE = 20
    MAX_VAL = 16
    MAX_REPEAT = 5
    data = []
    while len(data) < DATA_SIZE:
        val = random.randint(0, MAX_VAL)
        repeat = min(DATA_SIZE-len(data), random.randint(0, MAX_REPEAT))
        for _ in xrange(repeat): data.append(val)

    print data
    print [item for item in run_length_encode(data)]

输出：

[5, 5, 5, 9, 8, 8, 7, 5, 5, 5, 5, 5, 1, 7, 9, 16, 16, 16, 16, 16]
[(3, 5), 9, (2, 8), 7, (5, 5), 1, 7, 9, (5, 16)]

如果运行时间很长，最好迭代地明确计算每个组中有多少个，而不是将它们变成一个列表并计算其长度：

def ilen(iterable):
    """ return the number of items in an iterable """
    return sum(1 for _ in iterable)

def run_length_encode(data):
    for value, igroup in groupby(data):
#        repeat_count = len(list(igroup))
        repeat_count = ilen(igroup)
        yield value if repeat_count == 1 else repeat_count, value

由于您的数据值范围相对较小，您可以（也）将它们编码为单字节字符值。