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https://github.com/rspeer/wordfreq.git
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parent
cb4e444723
commit
a87d84b796
@ -4,8 +4,10 @@ from ftfy import chardata
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import pathlib
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from pkg_resources import resource_filename
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DATA_PATH = pathlib.Path(resource_filename('wordfreq', 'data'))
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def _emoji_char_class():
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"""
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Build a regex for emoji substitution. First we create a regex character set
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@ -28,6 +30,7 @@ def _emoji_char_class():
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with emoji_file.open(mode='w') as file:
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file.write(out)
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def _non_punct_class():
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"""
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Builds a regex that matches anything that is not a one of the following
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@ -46,6 +49,7 @@ def _non_punct_class():
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with non_punct_file.open(mode='w') as file:
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file.write(out)
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def _combining_mark_class():
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"""
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Builds a regex that matches anything that is a combining mark
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@ -56,6 +60,7 @@ def _combining_mark_class():
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with combining_mark_file.open(mode='w') as file:
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file.write(out)
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def func_to_regex(accept):
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"""
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Converts a function that accepts a single unicode character into a regex.
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@ -85,6 +90,7 @@ def func_to_regex(accept):
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return '[%s]' % ''.join(ranges)
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if __name__ == '__main__':
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_combining_mark_class()
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_non_punct_class()
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@ -14,6 +14,7 @@ DATA_PATH = pathlib.Path(resource_filename('wordfreq', 'data'))
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CACHE_SIZE = 100000
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def _emoji_char_class():
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"""
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Build a regex for emoji substitution. First we create a regex character set
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@ -25,6 +26,7 @@ def _emoji_char_class():
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with non_punct_file.open() as file:
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return file.read()
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def _non_punct_class():
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"""
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Builds a regex that matches anything that is not a one of the following
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@ -40,6 +42,7 @@ def _non_punct_class():
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with non_punct_file.open() as file:
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return file.read()
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def _combining_mark_class():
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"""
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Builds a regex that matches anything that is a combining mark
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@ -55,6 +58,7 @@ NON_PUNCT_RANGE = _non_punct_class()
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TOKEN_RE = re.compile("{0}|{1}+(?:'{1}+)*".format(EMOJI_RANGE, NON_PUNCT_RANGE))
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def simple_tokenize(text):
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"""
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A simple tokenizer that can be applied to most languages.
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@ -71,6 +75,7 @@ def simple_tokenize(text):
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"""
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return [token.casefold() for token in TOKEN_RE.findall(text)]
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def tokenize(text, lang):
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"""
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Tokenize this text in a way that's straightforward but appropriate for
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