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drwxr-xr-x
2024-02-12 23:52
__init__.py
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__init__.pyc
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__init__.pyo
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big5freq.py
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big5freq.pyc
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big5freq.pyo
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big5prober.py
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big5prober.pyc
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big5prober.pyo
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chardistribution.py
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chardistribution.pyc
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chardistribution.pyo
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charsetgroupprober.py
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2017-04-11 17:51
charsetgroupprober.pyc
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charsetgroupprober.pyo
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charsetprober.py
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charsetprober.pyc
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charsetprober.pyo
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codingstatemachine.py
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codingstatemachine.pyc
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codingstatemachine.pyo
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compat.py
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compat.pyc
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compat.pyo
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cp949prober.py
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cp949prober.pyc
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cp949prober.pyo
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enums.py
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enums.pyc
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enums.pyo
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escprober.py
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escprober.pyc
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escprober.pyo
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escsm.py
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escsm.pyc
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escsm.pyo
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eucjpprober.py
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eucjpprober.pyc
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eucjpprober.pyo
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euckrfreq.py
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euckrfreq.pyc
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euckrfreq.pyo
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euckrprober.py
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euckrprober.pyc
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euckrprober.pyo
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euctwfreq.py
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2017-04-11 20:48
euctwfreq.pyc
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euctwfreq.pyo
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euctwprober.py
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euctwprober.pyc
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euctwprober.pyo
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gb2312freq.py
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2017-04-11 17:51
gb2312freq.pyc
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gb2312freq.pyo
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gb2312prober.py
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2017-04-11 17:51
gb2312prober.pyc
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gb2312prober.pyo
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hebrewprober.py
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2017-06-08 14:21
hebrewprober.pyc
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hebrewprober.pyo
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jisfreq.py
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jisfreq.pyc
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jisfreq.pyo
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jpcntx.py
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jpcntx.pyc
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jpcntx.pyo
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langbulgarianmodel.py
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langbulgarianmodel.pyc
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langbulgarianmodel.pyo
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langcyrillicmodel.py
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2017-06-08 14:32
langcyrillicmodel.pyc
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langcyrillicmodel.pyo
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langgreekmodel.py
12.39
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langgreekmodel.pyc
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langgreekmodel.pyo
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langhebrewmodel.py
11.08
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2017-06-08 14:32
langhebrewmodel.pyc
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langhebrewmodel.pyo
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langhungarianmodel.py
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2017-06-08 14:32
langhungarianmodel.pyc
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langhungarianmodel.pyo
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langthaimodel.py
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langthaimodel.pyc
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langthaimodel.pyo
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langturkishmodel.py
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langturkishmodel.pyc
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langturkishmodel.pyo
22.88
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latin1prober.py
5.24
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2017-06-08 14:21
latin1prober.pyc
3.56
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latin1prober.pyo
3.56
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mbcharsetprober.py
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mbcharsetprober.pyc
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mbcharsetprober.pyo
2.64
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mbcsgroupprober.py
1.96
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2017-04-11 17:51
mbcsgroupprober.pyc
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mbcsgroupprober.pyo
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mbcssm.py
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mbcssm.pyc
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mbcssm.pyo
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sbcharsetprober.py
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sbcharsetprober.pyc
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sbcharsetprober.pyo
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sbcsgroupprober.py
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sbcsgroupprober.pyc
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sbcsgroupprober.pyo
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sjisprober.py
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sjisprober.pyc
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sjisprober.pyo
2.9
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universaldetector.py
12.19
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2017-06-08 14:32
universaldetector.pyc
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universaldetector.pyo
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utf8prober.py
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utf8prober.pyc
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utf8prober.pyo
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version.py
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version.pyc
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version.pyo
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Save
Rename
######################## BEGIN LICENSE BLOCK ######################## # The Original Code is Mozilla Universal charset detector code. # # The Initial Developer of the Original Code is # Netscape Communications Corporation. # Portions created by the Initial Developer are Copyright (C) 2001 # the Initial Developer. All Rights Reserved. # # Contributor(s): # Mark Pilgrim - port to Python # Shy Shalom - original C code # # This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2.1 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library; if not, write to the Free Software # Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA # 02110-1301 USA ######################### END LICENSE BLOCK ######################### from .charsetprober import CharSetProber from .enums import CharacterCategory, ProbingState, SequenceLikelihood class SingleByteCharSetProber(CharSetProber): SAMPLE_SIZE = 64 SB_ENOUGH_REL_THRESHOLD = 1024 # 0.25 * SAMPLE_SIZE^2 POSITIVE_SHORTCUT_THRESHOLD = 0.95 NEGATIVE_SHORTCUT_THRESHOLD = 0.05 def __init__(self, model, reversed=False, name_prober=None): super(SingleByteCharSetProber, self).__init__() self._model = model # TRUE if we need to reverse every pair in the model lookup self._reversed = reversed # Optional auxiliary prober for name decision self._name_prober = name_prober self._last_order = None self._seq_counters = None self._total_seqs = None self._total_char = None self._freq_char = None self.reset() def reset(self): super(SingleByteCharSetProber, self).reset() # char order of last character self._last_order = 255 self._seq_counters = [0] * SequenceLikelihood.get_num_categories() self._total_seqs = 0 self._total_char = 0 # characters that fall in our sampling range self._freq_char = 0 @property def charset_name(self): if self._name_prober: return self._name_prober.charset_name else: return self._model['charset_name'] @property def language(self): if self._name_prober: return self._name_prober.language else: return self._model.get('language') def feed(self, byte_str): if not self._model['keep_english_letter']: byte_str = self.filter_international_words(byte_str) if not byte_str: return self.state char_to_order_map = self._model['char_to_order_map'] for i, c in enumerate(byte_str): # XXX: Order is in range 1-64, so one would think we want 0-63 here, # but that leads to 27 more test failures than before. order = char_to_order_map[c] # XXX: This was SYMBOL_CAT_ORDER before, with a value of 250, but # CharacterCategory.SYMBOL is actually 253, so we use CONTROL # to make it closer to the original intent. The only difference # is whether or not we count digits and control characters for # _total_char purposes. if order < CharacterCategory.CONTROL: self._total_char += 1 if order < self.SAMPLE_SIZE: self._freq_char += 1 if self._last_order < self.SAMPLE_SIZE: self._total_seqs += 1 if not self._reversed: i = (self._last_order * self.SAMPLE_SIZE) + order model = self._model['precedence_matrix'][i] else: # reverse the order of the letters in the lookup i = (order * self.SAMPLE_SIZE) + self._last_order model = self._model['precedence_matrix'][i] self._seq_counters[model] += 1 self._last_order = order charset_name = self._model['charset_name'] if self.state == ProbingState.DETECTING: if self._total_seqs > self.SB_ENOUGH_REL_THRESHOLD: confidence = self.get_confidence() if confidence > self.POSITIVE_SHORTCUT_THRESHOLD: self.logger.debug('%s confidence = %s, we have a winner', charset_name, confidence) self._state = ProbingState.FOUND_IT elif confidence < self.NEGATIVE_SHORTCUT_THRESHOLD: self.logger.debug('%s confidence = %s, below negative ' 'shortcut threshhold %s', charset_name, confidence, self.NEGATIVE_SHORTCUT_THRESHOLD) self._state = ProbingState.NOT_ME return self.state def get_confidence(self): r = 0.01 if self._total_seqs > 0: r = ((1.0 * self._seq_counters[SequenceLikelihood.POSITIVE]) / self._total_seqs / self._model['typical_positive_ratio']) r = r * self._freq_char / self._total_char if r >= 1.0: r = 0.99 return r