Python defaultdict(list)de/serialization性能

Deu*_*ius 6 python performance serialization

我正在编写一个脚本,需要在启动时处理一个相当大(62万字)的词典.输入词典逐字处理成a defaultdict(list),键为字母bi和trigrams,值为包含关键字母n-gram的单词列表

for word in lexicon_file:
    word = word.lower()
    for letter n-gram in word:
        lexicon[n-gram].append(word)
Run Code Online (Sandbox Code Playgroud)

> lexicon["ab"]
["abracadabra", "abbey", "abnormal"]
Run Code Online (Sandbox Code Playgroud)

得到的结构包含25 000个键,每个键包含一个列表,其中包含1到133 000个字符串(平均值为500,中位数为20).所有字符串都在windows-1250编码中.

这种处理需要大量的时间(可忽略考虑到脚本的预期实际运行,但测试时一般征税),并且由于词汇本身永远不会改变,我想它可能会更快序列化所产生的defaultdict(list),然后反序列化在随后每次启动.

我发现即使在使用时cPickle,反序列化过程的速度也只是简单处理词典的两倍,平均值接近:

> normal lexicon creation
45 seconds
> cPickle deserialization
80 seconds
Run Code Online (Sandbox Code Playgroud)

我没有任何序列化的经验,但我期望反序列化比正常处理更快,至少对于cPickle模块而言.

我的问题是,这个结果可以预期吗?为什么?有没有办法更快地存储/加载我的结构?

Rya*_*n P 2

解决此类问题的最佳方法是编写一堆测试并使用timeit来查看哪个更快。我在下面进行了一些测试,但您应该用您的词典字典尝试一下,因为您的结果可能会有所不同。

如果您希望时间更加稳定(准确),您可以增加参数number-timeit它只会使测试花费更长的时间。另请注意,返回的值timeit是总执行时间,而不是每次运行的时间。

testing with 10 keys...
serialize flat: 2.97198390961
serialize eval: 4.60271120071
serialize defaultdict: 20.3057091236
serialize dict: 20.2011070251
serialize defaultdict new pickle: 14.5152060986
serialize dict new pickle: 14.7755970955
serialize json: 13.5039670467
serialize cjson: 4.0456969738
unserialize flat: 1.29577493668
unserialize eval: 25.6548647881
unserialize defaultdict: 10.2215960026
unserialize dict: 10.208122015
unserialize defaultdict new pickle: 5.70747089386
unserialize dict new pickle: 5.69750404358
unserialize json: 5.34811091423
unserialize cjson: 1.50241613388
testing with 100 keys...
serialize flat: 2.91076397896
serialize eval: 4.72978711128
serialize defaultdict: 21.331786871
serialize dict: 21.3218340874
serialize defaultdict new pickle: 15.7140991688
serialize dict new pickle: 15.6440980434
serialize json: 14.3557379246
serialize cjson: 5.00576901436
unserialize flat: 1.6677339077
unserialize eval: 22.9142649174
unserialize defaultdict: 10.7773029804
unserialize dict: 10.7524499893
unserialize defaultdict new pickle: 6.13370203972
unserialize dict new pickle: 6.18057107925
unserialize json: 5.92281794548
unserialize cjson: 1.91151690483
Run Code Online (Sandbox Code Playgroud)

代码:

import cPickle
import json
try:
    import cjson  # not Python standard library
except ImportError:
    cjson = False
from collections import defaultdict

dd1 = defaultdict(list)
dd2 = defaultdict(list)

for i in xrange(1000000):
    dd1[str(i % 10)].append(str(i))  
    dd2[str(i % 100)].append(str(i))

dt1 = dict(dd1)
dt2 = dict(dd2)

from timeit import timeit

def testdict(dd, dt):
    def serialize_defaultdict():
        with open('defaultdict.pickle', 'w') as f:
            cPickle.dump(dd, f)

    def serialize_p2_defaultdict():
        with open('defaultdict.pickle2', 'w') as f:
            cPickle.dump(dd, f, -1)

    def serialize_dict():
        with open('dict.pickle', 'w') as f:
            cPickle.dump(dt, f)

    def serialize_p2_dict():
        with open('dict.pickle2', 'w') as f:
            cPickle.dump(dt, f, -1)

    def serialize_json():
        with open('dict.json', 'w') as f:
            json.dump(dt, f)

    if cjson:
        def serialize_cjson():
            with open('dict.cjson', 'w') as f:
                f.write(cjson.encode(dt))

    def serialize_flat():
        with open('dict.flat', 'w') as f:
            f.write('\n'.join([' '.join([k] + v) for k, v in dt.iteritems()]))

    def serialize_eval():
        with open('dict.eval', 'w') as f:
            f.write('\n'.join([k + '\t' + repr(v) for k, v in dt.iteritems()]))

    def unserialize_defaultdict():
        with open('defaultdict.pickle') as f:
            assert cPickle.load(f) == dd

    def unserialize_p2_defaultdict():
        with open('defaultdict.pickle2') as f:
            assert cPickle.load(f) == dd

    def unserialize_dict():
        with open('dict.pickle') as f:
            assert cPickle.load(f) == dt

    def unserialize_p2_dict():
        with open('dict.pickle2') as f:
            assert cPickle.load(f) == dt

    def unserialize_json():
        with open('dict.json') as f:
            assert json.load(f) == dt

    if cjson:
        def unserialize_cjson():
            with open('dict.cjson') as f:
                assert cjson.decode(f.read()) == dt

    def unserialize_flat():
        with open('dict.flat') as f:
            dtx = {}
            for line in f:                                                                                                                                                                                                                                
                vals = line.split()
                dtx[vals[0]] = vals[1:]
            assert dtx == dt

    def unserialize_eval():
        with open('dict.eval') as f:
            dtx = {}
            for line in f:                                                                                                                                                                                                                                       
                vals = line.split('\t')
                dtx[vals[0]] = eval(vals[1])
            assert dtx == dt

    print 'serialize flat:', timeit(serialize_flat, number=10)
    print 'serialize eval:', timeit(serialize_eval, number=10)
    print 'serialize defaultdict:', timeit(serialize_defaultdict, number=10)
    print 'serialize dict:', timeit(serialize_dict, number=10)
    print 'serialize defaultdict new pickle:', timeit(serialize_p2_defaultdict, number=10)
    print 'serialize dict new pickle:', timeit(serialize_p2_dict, number=10)
    print 'serialize json:', timeit(serialize_json, number=10)
    if cjson:
        print 'serialize cjson:', timeit(serialize_cjson, number=10)
    print 'unserialize flat:', timeit(unserialize_flat, number=10)
    print 'unserialize eval:', timeit(unserialize_eval, number=10)
    print 'unserialize defaultdict:', timeit(unserialize_defaultdict, number=10)
    print 'unserialize dict:', timeit(unserialize_dict, number=10)
    print 'unserialize defaultdict new pickle:', timeit(unserialize_p2_defaultdict, number=10)
    print 'unserialize dict new pickle:', timeit(unserialize_p2_dict, number=10)
    print 'unserialize json:', timeit(unserialize_json, number=10)
    if cjson:
        print 'unserialize cjson:', timeit(unserialize_cjson, number=10)

print 'testing with 10 keys...'
testdict(dd1, dt1)

print 'testing with 100 keys...'
testdict(dd2, dt2)
Run Code Online (Sandbox Code Playgroud)