ai-content-maker/.venv/Lib/site-packages/pip/_vendor/chardet/macromanprober.py

163 lines
5.9 KiB
Python

######################## 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