Edit File: macromanprober.py
######################## BEGIN LICENSE BLOCK ######################## # This code was modified from latin1prober.py by Rob Speer <rob@lumino.so>. # 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): # Rob Speer - adapt to MacRoman encoding # 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 typing import List, Union from .charsetprober import CharSetProber from .enums import ProbingState FREQ_CAT_NUM = 4 UDF = 0 # undefined OTH = 1 # other ASC = 2 # ascii capital letter ASS = 3 # ascii small letter ACV = 4 # accent capital vowel ACO = 5 # accent capital other ASV = 6 # accent small vowel ASO = 7 # accent small other ODD = 8 # character that is unlikely to appear CLASS_NUM = 9 # total classes # The change from Latin1 is that we explicitly look for extended characters # that are infrequently-occurring symbols, and consider them to always be # improbable. This should let MacRoman get out of the way of more likely # encodings in most situations. # fmt: off MacRoman_CharToClass = ( OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 00 - 07 OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 08 - 0F OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 10 - 17 OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 18 - 1F OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 20 - 27 OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 28 - 2F OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 30 - 37 OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # 38 - 3F OTH, ASC, ASC, ASC, ASC, ASC, ASC, ASC, # 40 - 47 ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC, # 48 - 4F ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC, # 50 - 57 ASC, ASC, ASC, OTH, OTH, OTH, OTH, OTH, # 58 - 5F OTH, ASS, ASS, ASS, ASS, ASS, ASS, ASS, # 60 - 67 ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS, # 68 - 6F ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS, # 70 - 77 ASS, ASS, ASS, OTH, OTH, OTH, OTH, OTH, # 78 - 7F ACV, ACV, ACO, ACV, ACO, ACV, ACV, ASV, # 80 - 87 ASV, ASV, ASV, ASV, ASV, ASO, ASV, ASV, # 88 - 8F ASV, ASV, ASV, ASV, ASV, ASV, ASO, ASV, # 90 - 97 ASV, ASV, ASV, ASV, ASV, ASV, ASV, ASV, # 98 - 9F OTH, OTH, OTH, OTH, OTH, OTH, OTH, ASO, # A0 - A7 OTH, OTH, ODD, ODD, OTH, OTH, ACV, ACV, # A8 - AF OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH, # B0 - B7 OTH, OTH, OTH, OTH, OTH, OTH, ASV, ASV, # B8 - BF OTH, OTH, ODD, OTH, ODD, OTH, OTH, OTH, # C0 - C7 OTH, OTH, OTH, ACV, ACV, ACV, ACV, ASV, # C8 - CF OTH, OTH, OTH, OTH, OTH, OTH, OTH, ODD, # D0 - D7 ASV, ACV, ODD, OTH, OTH, OTH, OTH, OTH, # D8 - DF OTH, OTH, OTH, OTH, OTH, ACV, ACV, ACV, # E0 - E7 ACV, ACV, ACV, ACV, ACV, ACV, ACV, ACV, # E8 - EF ODD, ACV, ACV, ACV, ACV, ASV, ODD, ODD, # F0 - F7 ODD, ODD, ODD, ODD, ODD, ODD, ODD, ODD, # F8 - FF ) # 0 : illegal # 1 : very unlikely # 2 : normal # 3 : very likely MacRomanClassModel = ( # UDF OTH ASC ASS ACV ACO ASV ASO ODD 0, 0, 0, 0, 0, 0, 0, 0, 0, # UDF 0, 3, 3, 3, 3, 3, 3, 3, 1, # OTH 0, 3, 3, 3, 3, 3, 3, 3, 1, # ASC 0, 3, 3, 3, 1, 1, 3, 3, 1, # ASS 0, 3, 3, 3, 1, 2, 1, 2, 1, # ACV 0, 3, 3, 3, 3, 3, 3, 3, 1, # ACO 0, 3, 1, 3, 1, 1, 1, 3, 1, # ASV 0, 3, 1, 3, 1, 1, 3, 3, 1, # ASO 0, 1, 1, 1, 1, 1, 1, 1, 1, # ODD ) # fmt: on class MacRomanProber(CharSetProber): def __init__(self) -> None: super().__init__() self._last_char_class = OTH self._freq_counter: List[int] = [] self.reset() def reset(self) -> None: self._last_char_class = OTH self._freq_counter = [0] * FREQ_CAT_NUM # express the prior that MacRoman is a somewhat rare encoding; # this can be done by starting out in a slightly improbable state # that must be overcome self._freq_counter[2] = 10 super().reset() @property def charset_name(self) -> str: return "MacRoman" @property def language(self) -> str: return "" def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState: byte_str = self.remove_xml_tags(byte_str) for c in byte_str: char_class = MacRoman_CharToClass[c] freq = MacRomanClassModel[(self._last_char_class * CLASS_NUM) + char_class] if freq == 0: self._state = ProbingState.NOT_ME break self._freq_counter[freq] += 1 self._last_char_class = char_class return self.state def get_confidence(self) -> float: if self.state == ProbingState.NOT_ME: return 0.01 total = sum(self._freq_counter) confidence = ( 0.0 if total < 0.01 else (self._freq_counter[3] - self._freq_counter[1] * 20.0) / total ) confidence = max(confidence, 0.0) # lower the confidence of MacRoman so that other more accurate # detector can take priority. confidence *= 0.73 return confidence