3 d: @sdZddlZddlmZddlZddlmZdZdZdZ eedd d d d d df Z e de fe ddZ ej dZ ej eejejBejBZej dZej dZd#ddZfddfddZGdddeZddZddZd$d!d"ZdS)%a Twitter-aware tokenizer, designed to be flexible and easy to adapt to new domains and tasks. The basic logic is this: 1. The tuple REGEXPS defines a list of regular expression strings. 2. The REGEXPS strings are put, in order, into a compiled regular expression object called WORD_RE, under the TweetTokenizer class. 3. The tokenization is done by WORD_RE.findall(s), where s is the user-supplied string, inside the tokenize() method of the class TweetTokenizer. 4. When instantiating Tokenizer objects, there are several options: * preserve_case. By default, it is set to True. If it is set to False, then the tokenizer will downcase everything except for emoticons. * reduce_len. By default, it is set to False. It specifies whether to replace repeated character sequences of length 3 or greater with sequences of length 3. * strip_handles. By default, it is set to False. It specifies whether to remove Twitter handles of text used in the `tokenize` method. * match_phone_numbers. By default, it is set to True. It indicates whether the `tokenize` method should look for phone numbers. N)List) TokenizerIac (?: [<>]? [:;=8] # eyes [\-o\*\']? # optional nose [\)\]\(\[dDpP/\:\}\{@\|\\] # mouth | [\)\]\(\[dDpP/\:\}\{@\|\\] # mouth [\-o\*\']? # optional nose [:;=8] # eyes [<>]? | {}\[\]]+ # Run of non-space, non-()<>{}[] | # or \([^\s()]*?\([^\s()]+\)[^\s()]*?\) # balanced parens, one level deep: (...(...)...) | \([^\s]+?\) # balanced parens, non-recursive: (...) )+ (?: # End with: \([^\s()]*?\([^\s()]+\)[^\s()]*?\) # balanced parens, one level deep: (...(...)...) | \([^\s]+?\) # balanced parens, non-recursive: (...) | # or [^\s`!()\[\]{};:'".,<>?«»“”‘’] # not a space or one of these punct chars ) | # OR, the following to match naked domains: (?: (?\s]+>z [\-]+>|<[\-]+z (?:@[\w_]+)z(?:\#+[\w_]+[\w\'_\-]*[\w_]+)z#[\w.+-]+@[\w-]+\.(?:[\w-]\.?)+[\w-]uR.(?: [🏻-🏿]?(?:‍.[🏻-🏿]?)+ | [🏻-🏿] )a (?:[^\W\d_](?:[^\W\d_]|['\-_])+[^\W\d_]) # Words with apostrophes or dashes. | (?:[+\-]?\d+[,/.:-]\d+[+\-]?) # Numbers, including fractions, decimals. | (?:[\w_]+) # Words without apostrophes or dashes. | (?:\.(?:\s*\.){1,}) # Ellipsis dots. | (?:\S) # Everything else that isn't whitespace. z([^a-zA-Z0-9])\1{3,}z&(#?(x?))([^&;\s]+);zZ(?>> from nltk.tokenize.casual import _replace_html_entities >>> _replace_html_entities(b'Price: £100') 'Price: \xa3100' >>> print(_replace_html_entities(b'Price: £100')) Price: £100 >>> cs|jd}|jdr|yL|jdr,t|d}n t|d}d|koHdknr^t|fjdSWqtk rxd}YqXn |kr|jd Stjjj|}|dk ryt |Stt fk rYnXrd S|jd S) Nr cp1252r) groupintrr ValueErrorhtmlentitiesname2codepointgetchr OverflowError)matchZ entity_bodynumber)keepremove_illegalr r _convert_entitys&       z/_replace_html_entities.._convert_entity)ENT_REsubr)r r"r#r r$r )r"r#r _replace_html_entitiessr'c@sZeZdZdZdZdZdddZeeeddd Z e d d d d Z e d d ddZ dS)TweetTokenizera Tokenizer for tweets. >>> from nltk.tokenize import TweetTokenizer >>> tknzr = TweetTokenizer() >>> s0 = "This is a cooool #dummysmiley: :-) :-P <3 and some arrows < > -> <--" >>> tknzr.tokenize(s0) ['This', 'is', 'a', 'cooool', '#dummysmiley', ':', ':-)', ':-P', '<3' , 'and', 'some', 'arrows', '<', '>', '->', '<--'] Examples using `strip_handles` and `reduce_len parameters`: >>> tknzr = TweetTokenizer(strip_handles=True, reduce_len=True) >>> s1 = '@remy: This is waaaaayyyy too much for you!!!!!!' >>> tknzr.tokenize(s1) [':', 'This', 'is', 'waaayyy', 'too', 'much', 'for', 'you', '!', '!', '!'] NTFcCs||_||_||_||_dS)ae Create a `TweetTokenizer` instance with settings for use in the `tokenize` method. :param preserve_case: Flag indicating whether to preserve the casing (capitalisation) of text used in the `tokenize` method. Defaults to True. :type preserve_case: bool :param reduce_len: Flag indicating whether to replace repeated character sequences of length 3 or greater with sequences of length 3. Defaults to False. :type reduce_len: bool :param strip_handles: Flag indicating whether to remove Twitter handles of text used in the `tokenize` method. Defaults to False. :type strip_handles: bool :param match_phone_numbers: Flag indicating whether the `tokenize` method should look for phone numbers. Defaults to True. :type match_phone_numbers: bool N) preserve_case reduce_len strip_handlesmatch_phone_numbers)selfr)r*r+r,r r r __init__3szTweetTokenizer.__init__)r returncCslt|}|jrt|}|jr$t|}tjd|}|jrD|jj |}n |j j |}|j sht t dd|}|S)zTokenize the input text. :param text: str :rtype: list(str) :return: a tokenized list of strings; joining this list returns the original string if `preserve_case=False`. z\1\1\1cSstj|r|S|jS)N) EMOTICON_REsearchlower)xr r r isz)TweetTokenizer.tokenize..)r'r+remove_handlesr*reduce_lengtheningHANG_REr&r, PHONE_WORD_REfindallWORD_REr)listmap)r-r Z safe_textwordsr r r tokenizeOs   zTweetTokenizer.tokenizez regex.Pattern)r/cCsBt|js8tjddjtdtjtjBtjBt|_t|jS)zCore TweetTokenizer regex(|)) type_WORD_REregexcompilejoinREGEXPSVERBOSEIUNICODE)r-r r r r:ms  zTweetTokenizer.WORD_REcCsBt|js8tjddjtdtjtjBtjBt|_t|jS)z#Secondary core TweetTokenizer regexr?r@rA) rB_PHONE_WORD_RErDrErF REGEXPS_PHONErHrIrJ)r-r r r r8xs  zTweetTokenizer.PHONE_WORD_RE)TFFT) __name__ __module__ __qualname____doc__rCrKr.strrr>propertyr:r8r r r r r(s  r(cCstjd}|jd|S)ze Replace repeated character sequences of length 3 or greater with sequences of length 3. z (.)\1{2,}z\1\1\1)rDrEr&)r patternr r r r6s r6cCs tjd|S)z4 Remove Twitter username handles from text.  ) HANDLES_REr&)r r r r r5sr5FcCst||||dj|S)z: Convenience function for wrapping the tokenizer. )r)r*r+r,)r(r>)r r)r*r+r,r r r casual_tokenizes rV)Nr)TFFT)rPrZtypingrrDZnltk.tokenize.apirZ EMOTICONSZURLSZ PHONE_REGEXrGrLrEr7rHrIrJr0r%rUrr'r(r6r5rVr r r r )s>  .    >p