什么是一个很好的Python亵渎过滤库?

时间:2010-08-20 14:20:37

标签: python nlp profanity

https://stackoverflow.com/questions/1521646/best-profanity-filter类似,但对于Python - 我正在寻找库,我可以在本地运行和控制自己,而不是Web服务。

(虽然听到你对亵渎过滤的原则的基本反对意见总是很好,但我并不是在这里专门寻找它们。我知道亵渎过滤不能发现所说的每一个有害的事情。我知道咒骂,在事情的宏伟计划,并不是一个特别大的问题。我知道你需要一些人力投入来处理内容问题。我只想找到一个好的图书馆,看看我能用它做什么用。)

6 个答案:

答案 0 :(得分:41)

我没有找到任何Python亵渎图书馆,所以我自己创建了一个。

参数


filterlist

与禁用词匹配的正则表达式列表。请不要使用\b,它会根据inside_words插入。

实施例:  ['bad', 'un\w+']

ignore_case

默认值:True

言自明的。

replacements

默认值:"$@%-?!"

包含字符的字符串,将从中随机生成替换字符串。

示例:"%&$?!""-"等。

complete

默认值:True

控制是否将替换整个字符串,或者是否保留第一个和最后一个字符。

inside_words

默认值:False

控制是否在其他单词中搜索单词。禁用此

模块来源


(最后的例子)

"""
Module that provides a class that filters profanities

"""

__author__ = "leoluk"
__version__ = '0.0.1'

import random
import re

class ProfanitiesFilter(object):
    def __init__(self, filterlist, ignore_case=True, replacements="$@%-?!", 
                 complete=True, inside_words=False):
        """
        Inits the profanity filter.

        filterlist -- a list of regular expressions that
        matches words that are forbidden
        ignore_case -- ignore capitalization
        replacements -- string with characters to replace the forbidden word
        complete -- completely remove the word or keep the first and last char?
        inside_words -- search inside other words?

        """

        self.badwords = filterlist
        self.ignore_case = ignore_case
        self.replacements = replacements
        self.complete = complete
        self.inside_words = inside_words

    def _make_clean_word(self, length):
        """
        Generates a random replacement string of a given length
        using the chars in self.replacements.

        """
        return ''.join([random.choice(self.replacements) for i in
                  range(length)])

    def __replacer(self, match):
        value = match.group()
        if self.complete:
            return self._make_clean_word(len(value))
        else:
            return value[0]+self._make_clean_word(len(value)-2)+value[-1]

    def clean(self, text):
        """Cleans a string from profanity."""

        regexp_insidewords = {
            True: r'(%s)',
            False: r'\b(%s)\b',
            }

        regexp = (regexp_insidewords[self.inside_words] % 
                  '|'.join(self.badwords))

        r = re.compile(regexp, re.IGNORECASE if self.ignore_case else 0)

        return r.sub(self.__replacer, text)


if __name__ == '__main__':

    f = ProfanitiesFilter(['bad', 'un\w+'], replacements="-")    
    example = "I am doing bad ungood badlike things."

    print f.clean(example)
    # Returns "I am doing --- ------ badlike things."

    f.inside_words = True    
    print f.clean(example)
    # Returns "I am doing --- ------ ---like things."

    f.complete = False    
    print f.clean(example)
    # Returns "I am doing b-d u----d b-dlike things."

答案 1 :(得分:20)

arrBad = [
'2g1c',
'2 girls 1 cup',
'acrotomophilia',
'anal',
'anilingus',
'anus',
'arsehole',
'ass',
'asshole',
'assmunch',
'auto erotic',
'autoerotic',
'babeland',
'baby batter',
'ball gag',
'ball gravy',
'ball kicking',
'ball licking',
'ball sack',
'ball sucking',
'bangbros',
'bareback',
'barely legal',
'barenaked',
'bastardo',
'bastinado',
'bbw',
'bdsm',
'beaver cleaver',
'beaver lips',
'bestiality',
'bi curious',
'big black',
'big breasts',
'big knockers',
'big tits',
'bimbos',
'birdlock',
'bitch',
'black cock',
'blonde action',
'blonde on blonde action',
'blow j',
'blow your l',
'blue waffle',
'blumpkin',
'bollocks',
'bondage',
'boner',
'boob',
'boobs',
'booty call',
'brown showers',
'brunette action',
'bukkake',
'bulldyke',
'bullet vibe',
'bung hole',
'bunghole',
'busty',
'butt',
'buttcheeks',
'butthole',
'camel toe',
'camgirl',
'camslut',
'camwhore',
'carpet muncher',
'carpetmuncher',
'chocolate rosebuds',
'circlejerk',
'cleveland steamer',
'clit',
'clitoris',
'clover clamps',
'clusterfuck',
'cock',
'cocks',
'coprolagnia',
'coprophilia',
'cornhole',
'cum',
'cumming',
'cunnilingus',
'cunt',
'darkie',
'date rape',
'daterape',
'deep throat',
'deepthroat',
'dick',
'dildo',
'dirty pillows',
'dirty sanchez',
'dog style',
'doggie style',
'doggiestyle',
'doggy style',
'doggystyle',
'dolcett',
'domination',
'dominatrix',
'dommes',
'donkey punch',
'double dong',
'double penetration',
'dp action',
'eat my ass',
'ecchi',
'ejaculation',
'erotic',
'erotism',
'escort',
'ethical slut',
'eunuch',
'faggot',
'fecal',
'felch',
'fellatio',
'feltch',
'female squirting',
'femdom',
'figging',
'fingering',
'fisting',
'foot fetish',
'footjob',
'frotting',
'fuck',
'fucking',
'fuck buttons',
'fudge packer',
'fudgepacker',
'futanari',
'g-spot',
'gang bang',
'gay sex',
'genitals',
'giant cock',
'girl on',
'girl on top',
'girls gone wild',
'goatcx',
'goatse',
'gokkun',
'golden shower',
'goo girl',
'goodpoop',
'goregasm',
'grope',
'group sex',
'guro',
'hand job',
'handjob',
'hard core',
'hardcore',
'hentai',
'homoerotic',
'honkey',
'hooker',
'hot chick',
'how to kill',
'how to murder',
'huge fat',
'humping',
'incest',
'intercourse',
'jack off',
'jail bait',
'jailbait',
'jerk off',
'jigaboo',
'jiggaboo',
'jiggerboo',
'jizz',
'juggs',
'kike',
'kinbaku',
'kinkster',
'kinky',
'knobbing',
'leather restraint',
'leather straight jacket',
'lemon party',
'lolita',
'lovemaking',
'make me come',
'male squirting',
'masturbate',
'menage a trois',
'milf',
'missionary position',
'motherfucker',
'mound of venus',
'mr hands',
'muff diver',
'muffdiving',
'nambla',
'nawashi',
'negro',
'neonazi',
'nig nog',
'nigga',
'nigger',
'nimphomania',
'nipple',
'nipples',
'nsfw images',
'nude',
'nudity',
'nympho',
'nymphomania',
'octopussy',
'omorashi',
'one cup two girls',
'one guy one jar',
'orgasm',
'orgy',
'paedophile',
'panties',
'panty',
'pedobear',
'pedophile',
'pegging',
'penis',
'phone sex',
'piece of shit',
'piss pig',
'pissing',
'pisspig',
'playboy',
'pleasure chest',
'pole smoker',
'ponyplay',
'poof',
'poop chute',
'poopchute',
'porn',
'porno',
'pornography',
'prince albert piercing',
'pthc',
'pubes',
'pussy',
'queaf',
'raghead',
'raging boner',
'rape',
'raping',
'rapist',
'rectum',
'reverse cowgirl',
'rimjob',
'rimming',
'rosy palm',
'rosy palm and her 5 sisters',
'rusty trombone',
's&m',
'sadism',
'scat',
'schlong',
'scissoring',
'semen',
'sex',
'sexo',
'sexy',
'shaved beaver',
'shaved pussy',
'shemale',
'shibari',
'shit',
'shota',
'shrimping',
'slanteye',
'slut',
'smut',
'snatch',
'snowballing',
'sodomize',
'sodomy',
'spic',
'spooge',
'spread legs',
'strap on',
'strapon',
'strappado',
'strip club',
'style doggy',
'suck',
'sucks',
'suicide girls',
'sultry women',
'swastika',
'swinger',
'tainted love',
'taste my',
'tea bagging',
'threesome',
'throating',
'tied up',
'tight white',
'tit',
'tits',
'titties',
'titty',
'tongue in a',
'topless',
'tosser',
'towelhead',
'tranny',
'tribadism',
'tub girl',
'tubgirl',
'tushy',
'twat',
'twink',
'twinkie',
'two girls one cup',
'undressing',
'upskirt',
'urethra play',
'urophilia',
'vagina',
'venus mound',
'vibrator',
'violet blue',
'violet wand',
'vorarephilia',
'voyeur',
'vulva',
'wank',
'wet dream',
'wetback',
'white power',
'women rapping',
'wrapping men',
'wrinkled starfish',
'xx',
'xxx',
'yaoi',
'yellow showers',
'yiffy',
'zoophilia']

def profanityFilter(text):
brokenStr1 = text.split()
badWordMask = '!@#$%!@#$%^~!@%^~@#$%!@#$%^~!'
new = ''
for word in brokenStr1:
    if word in arrBad:
        print word + ' <--Bad word!'
        text = text.replace(word,badWordMask[:len(word)])
        #print new

return text

print profanityFilter("this thing sucks sucks sucks fucking stuff")

您可以根据需要在坏词列表arrBad中添加或删除。

答案 2 :(得分:5)

WebPurify是Python的亵渎过滤器库

答案 3 :(得分:4)

答案 4 :(得分:1)

亵渎? f ***是什么? ; - )

计算机真的能够识别咒骂和诅咒还需要几年的时间,我真诚地希望人们能够理解亵渎是人类而不是“危险”。

而不是愚蠢的过滤器,有一个聪明的人类主持人,可以适当地平衡讨论的基调。可以检测滥用行为的主持人,如:

“如果你是我的丈夫,我会毒你的茶。” - “如果你是我的妻子,我会喝它。”

(来自温斯顿丘吉尔,顺便说一句。)

答案 5 :(得分:0)

当然,用户可以解决这个问题,但它应该做一个相当彻底的工作来消除亵渎:

import re
def remove_profanity(s):
    def repl(word):
        m = re.match(r"(\w+)(.*)", word)
        if not m:
            return word
        word = "Bork" if m.group(1)[0].isupper() else "bork"
        word += m.group(2)
        return word
    return " ".join([repl(w) for w in s.split(" ")])

print remove_profanity("You just come along with me and have a good time. The Galaxy's a fun place. You'll need to have this fish in your ear.")
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