Upload normalize.py
Browse files- normalize.py +44 -0
normalize.py
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import re
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import emoji
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def normalize(sentence: str) -> str:
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"""
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This function should be used before tokenizing the input string.
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Normalizes the input string in the following ways:
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-> Converts from ş to ș, ţ to ț, etc.
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-> Converts @mentions to USER, #hashtags to HASHTAG, http... and www... to HTTPURL
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-> Converts emoticons to emoji_with_long_name
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-> Replaces :emoji_with_long_name: with emoji_with_long_name and replaces _, : and - with empty string
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-> Removes multiple whitespaces with a single whitespace
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Args:
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`sentence` (str): The input string.
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Returns:
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str: The normalized string.
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"""
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# Make sure it's a string
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sentence = str(sentence)
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# Convert from ş to ș, ţ to ț, etc.
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sentence = re.sub(r'ş', 'ș', sentence)
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sentence = re.sub(r'Ş', 'Ș', sentence)
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sentence = re.sub(r'ţ', 'ț', sentence)
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sentence = re.sub(r'Ţ', 'Ț', sentence)
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# Convert @mentions to USER, #hashtags to HASHTAG, http... and www... to HTTPURL
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sentence = re.sub(r'@\S+', 'USER', sentence)
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sentence = re.sub(r'#\S+', 'HASHTAG', sentence)
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sentence = re.sub(r'http\S+', 'HTTPURL', sentence)
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sentence = re.sub(r'www\S+', 'HTTPURL', sentence)
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# Convert emoticons to emoji_with_long_name
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sentence = emoji.demojize(sentence, delimiters=(' :', ': '))
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# Replace :emoji_with_long_name: with emoji_with_long_name and replace _, : and - with empty string
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sentence = re.sub(r':\S+:', lambda x: x.group(0).replace('_', '').replace(':', '').replace('-', ''), sentence)
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# Remove multiple whitespaces with a single whitespace
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sentence = re.sub(r'\s+', ' ', sentence)
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return sentence
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