616 lines
19 KiB
Python
616 lines
19 KiB
Python
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from functools import lru_cache
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from logging import getLogger
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from typing import List, Optional
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from .constant import (
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COMMON_SAFE_ASCII_CHARACTERS,
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TRACE,
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UNICODE_SECONDARY_RANGE_KEYWORD,
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)
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from .utils import (
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is_accentuated,
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is_arabic,
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is_arabic_isolated_form,
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is_case_variable,
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is_cjk,
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is_emoticon,
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is_hangul,
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is_hiragana,
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is_katakana,
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is_latin,
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is_punctuation,
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is_separator,
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is_symbol,
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is_thai,
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is_unprintable,
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remove_accent,
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unicode_range,
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)
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class MessDetectorPlugin:
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"""
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Base abstract class used for mess detection plugins.
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All detectors MUST extend and implement given methods.
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"""
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def eligible(self, character: str) -> bool:
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"""
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Determine if given character should be fed in.
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"""
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raise NotImplementedError # pragma: nocover
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def feed(self, character: str) -> None:
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"""
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The main routine to be executed upon character.
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Insert the logic in witch the text would be considered chaotic.
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"""
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raise NotImplementedError # pragma: nocover
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def reset(self) -> None: # pragma: no cover
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"""
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Permit to reset the plugin to the initial state.
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"""
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raise NotImplementedError
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@property
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def ratio(self) -> float:
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"""
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Compute the chaos ratio based on what your feed() has seen.
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Must NOT be lower than 0.; No restriction gt 0.
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"""
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raise NotImplementedError # pragma: nocover
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class TooManySymbolOrPunctuationPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._punctuation_count: int = 0
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self._symbol_count: int = 0
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self._character_count: int = 0
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self._last_printable_char: Optional[str] = None
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self._frenzy_symbol_in_word: bool = False
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def eligible(self, character: str) -> bool:
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return character.isprintable()
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def feed(self, character: str) -> None:
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self._character_count += 1
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if (
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character != self._last_printable_char
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and character not in COMMON_SAFE_ASCII_CHARACTERS
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):
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if is_punctuation(character):
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self._punctuation_count += 1
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elif (
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character.isdigit() is False
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and is_symbol(character)
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and is_emoticon(character) is False
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):
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self._symbol_count += 2
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self._last_printable_char = character
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def reset(self) -> None: # pragma: no cover
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self._punctuation_count = 0
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self._character_count = 0
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self._symbol_count = 0
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@property
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def ratio(self) -> float:
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if self._character_count == 0:
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return 0.0
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ratio_of_punctuation: float = (
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self._punctuation_count + self._symbol_count
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) / self._character_count
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return ratio_of_punctuation if ratio_of_punctuation >= 0.3 else 0.0
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class TooManyAccentuatedPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._character_count: int = 0
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self._accentuated_count: int = 0
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def eligible(self, character: str) -> bool:
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return character.isalpha()
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def feed(self, character: str) -> None:
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self._character_count += 1
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if is_accentuated(character):
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self._accentuated_count += 1
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def reset(self) -> None: # pragma: no cover
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self._character_count = 0
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self._accentuated_count = 0
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@property
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def ratio(self) -> float:
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if self._character_count < 8:
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return 0.0
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ratio_of_accentuation: float = self._accentuated_count / self._character_count
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return ratio_of_accentuation if ratio_of_accentuation >= 0.35 else 0.0
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class UnprintablePlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._unprintable_count: int = 0
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self._character_count: int = 0
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def eligible(self, character: str) -> bool:
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return True
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def feed(self, character: str) -> None:
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if is_unprintable(character):
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self._unprintable_count += 1
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self._character_count += 1
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def reset(self) -> None: # pragma: no cover
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self._unprintable_count = 0
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@property
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def ratio(self) -> float:
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if self._character_count == 0:
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return 0.0
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return (self._unprintable_count * 8) / self._character_count
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class SuspiciousDuplicateAccentPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._successive_count: int = 0
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self._character_count: int = 0
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self._last_latin_character: Optional[str] = None
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def eligible(self, character: str) -> bool:
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return character.isalpha() and is_latin(character)
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def feed(self, character: str) -> None:
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self._character_count += 1
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if (
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self._last_latin_character is not None
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and is_accentuated(character)
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and is_accentuated(self._last_latin_character)
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):
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if character.isupper() and self._last_latin_character.isupper():
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self._successive_count += 1
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# Worse if its the same char duplicated with different accent.
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if remove_accent(character) == remove_accent(self._last_latin_character):
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self._successive_count += 1
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self._last_latin_character = character
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def reset(self) -> None: # pragma: no cover
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self._successive_count = 0
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self._character_count = 0
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self._last_latin_character = None
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@property
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def ratio(self) -> float:
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if self._character_count == 0:
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return 0.0
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return (self._successive_count * 2) / self._character_count
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class SuspiciousRange(MessDetectorPlugin):
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def __init__(self) -> None:
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self._suspicious_successive_range_count: int = 0
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self._character_count: int = 0
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self._last_printable_seen: Optional[str] = None
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def eligible(self, character: str) -> bool:
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return character.isprintable()
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def feed(self, character: str) -> None:
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self._character_count += 1
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if (
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character.isspace()
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or is_punctuation(character)
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or character in COMMON_SAFE_ASCII_CHARACTERS
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):
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self._last_printable_seen = None
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return
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if self._last_printable_seen is None:
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self._last_printable_seen = character
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return
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unicode_range_a: Optional[str] = unicode_range(self._last_printable_seen)
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unicode_range_b: Optional[str] = unicode_range(character)
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if is_suspiciously_successive_range(unicode_range_a, unicode_range_b):
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self._suspicious_successive_range_count += 1
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self._last_printable_seen = character
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def reset(self) -> None: # pragma: no cover
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self._character_count = 0
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self._suspicious_successive_range_count = 0
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self._last_printable_seen = None
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@property
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def ratio(self) -> float:
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if self._character_count <= 24:
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return 0.0
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ratio_of_suspicious_range_usage: float = (
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self._suspicious_successive_range_count * 2
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) / self._character_count
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return ratio_of_suspicious_range_usage
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class SuperWeirdWordPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._word_count: int = 0
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self._bad_word_count: int = 0
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self._foreign_long_count: int = 0
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self._is_current_word_bad: bool = False
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self._foreign_long_watch: bool = False
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self._character_count: int = 0
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self._bad_character_count: int = 0
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self._buffer: str = ""
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self._buffer_accent_count: int = 0
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def eligible(self, character: str) -> bool:
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return True
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def feed(self, character: str) -> None:
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if character.isalpha():
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self._buffer += character
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if is_accentuated(character):
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self._buffer_accent_count += 1
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if (
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self._foreign_long_watch is False
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and (is_latin(character) is False or is_accentuated(character))
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and is_cjk(character) is False
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and is_hangul(character) is False
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and is_katakana(character) is False
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and is_hiragana(character) is False
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and is_thai(character) is False
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):
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self._foreign_long_watch = True
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return
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if not self._buffer:
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return
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if (
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character.isspace() or is_punctuation(character) or is_separator(character)
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) and self._buffer:
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self._word_count += 1
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buffer_length: int = len(self._buffer)
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self._character_count += buffer_length
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if buffer_length >= 4:
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if self._buffer_accent_count / buffer_length > 0.34:
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self._is_current_word_bad = True
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# Word/Buffer ending with an upper case accentuated letter are so rare,
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# that we will consider them all as suspicious. Same weight as foreign_long suspicious.
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if (
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is_accentuated(self._buffer[-1])
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and self._buffer[-1].isupper()
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and all(_.isupper() for _ in self._buffer) is False
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):
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self._foreign_long_count += 1
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self._is_current_word_bad = True
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if buffer_length >= 24 and self._foreign_long_watch:
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camel_case_dst = [
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i
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for c, i in zip(self._buffer, range(0, buffer_length))
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if c.isupper()
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]
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probable_camel_cased: bool = False
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if camel_case_dst and (len(camel_case_dst) / buffer_length <= 0.3):
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probable_camel_cased = True
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if not probable_camel_cased:
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self._foreign_long_count += 1
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self._is_current_word_bad = True
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if self._is_current_word_bad:
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self._bad_word_count += 1
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self._bad_character_count += len(self._buffer)
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self._is_current_word_bad = False
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self._foreign_long_watch = False
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self._buffer = ""
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self._buffer_accent_count = 0
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elif (
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character not in {"<", ">", "-", "=", "~", "|", "_"}
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and character.isdigit() is False
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and is_symbol(character)
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):
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self._is_current_word_bad = True
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self._buffer += character
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def reset(self) -> None: # pragma: no cover
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self._buffer = ""
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self._is_current_word_bad = False
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self._foreign_long_watch = False
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self._bad_word_count = 0
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self._word_count = 0
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self._character_count = 0
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self._bad_character_count = 0
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self._foreign_long_count = 0
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@property
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def ratio(self) -> float:
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if self._word_count <= 10 and self._foreign_long_count == 0:
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return 0.0
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return self._bad_character_count / self._character_count
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class CjkInvalidStopPlugin(MessDetectorPlugin):
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"""
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GB(Chinese) based encoding often render the stop incorrectly when the content does not fit and
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can be easily detected. Searching for the overuse of '丅' and '丄'.
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"""
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def __init__(self) -> None:
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self._wrong_stop_count: int = 0
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self._cjk_character_count: int = 0
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def eligible(self, character: str) -> bool:
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return True
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def feed(self, character: str) -> None:
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if character in {"丅", "丄"}:
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self._wrong_stop_count += 1
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return
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if is_cjk(character):
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self._cjk_character_count += 1
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def reset(self) -> None: # pragma: no cover
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self._wrong_stop_count = 0
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self._cjk_character_count = 0
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@property
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def ratio(self) -> float:
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if self._cjk_character_count < 16:
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return 0.0
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return self._wrong_stop_count / self._cjk_character_count
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class ArchaicUpperLowerPlugin(MessDetectorPlugin):
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def __init__(self) -> None:
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self._buf: bool = False
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self._character_count_since_last_sep: int = 0
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self._successive_upper_lower_count: int = 0
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self._successive_upper_lower_count_final: int = 0
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|
|
self._character_count: int = 0
|
||
|
|
|
||
|
|
self._last_alpha_seen: Optional[str] = None
|
||
|
|
self._current_ascii_only: bool = True
|
||
|
|
|
||
|
|
def eligible(self, character: str) -> bool:
|
||
|
|
return True
|
||
|
|
|
||
|
|
def feed(self, character: str) -> None:
|
||
|
|
is_concerned = character.isalpha() and is_case_variable(character)
|
||
|
|
chunk_sep = is_concerned is False
|
||
|
|
|
||
|
|
if chunk_sep and self._character_count_since_last_sep > 0:
|
||
|
|
if (
|
||
|
|
self._character_count_since_last_sep <= 64
|
||
|
|
and character.isdigit() is False
|
||
|
|
and self._current_ascii_only is False
|
||
|
|
):
|
||
|
|
self._successive_upper_lower_count_final += (
|
||
|
|
self._successive_upper_lower_count
|
||
|
|
)
|
||
|
|
|
||
|
|
self._successive_upper_lower_count = 0
|
||
|
|
self._character_count_since_last_sep = 0
|
||
|
|
self._last_alpha_seen = None
|
||
|
|
self._buf = False
|
||
|
|
self._character_count += 1
|
||
|
|
self._current_ascii_only = True
|
||
|
|
|
||
|
|
return
|
||
|
|
|
||
|
|
if self._current_ascii_only is True and character.isascii() is False:
|
||
|
|
self._current_ascii_only = False
|
||
|
|
|
||
|
|
if self._last_alpha_seen is not None:
|
||
|
|
if (character.isupper() and self._last_alpha_seen.islower()) or (
|
||
|
|
character.islower() and self._last_alpha_seen.isupper()
|
||
|
|
):
|
||
|
|
if self._buf is True:
|
||
|
|
self._successive_upper_lower_count += 2
|
||
|
|
self._buf = False
|
||
|
|
else:
|
||
|
|
self._buf = True
|
||
|
|
else:
|
||
|
|
self._buf = False
|
||
|
|
|
||
|
|
self._character_count += 1
|
||
|
|
self._character_count_since_last_sep += 1
|
||
|
|
self._last_alpha_seen = character
|
||
|
|
|
||
|
|
def reset(self) -> None: # pragma: no cover
|
||
|
|
self._character_count = 0
|
||
|
|
self._character_count_since_last_sep = 0
|
||
|
|
self._successive_upper_lower_count = 0
|
||
|
|
self._successive_upper_lower_count_final = 0
|
||
|
|
self._last_alpha_seen = None
|
||
|
|
self._buf = False
|
||
|
|
self._current_ascii_only = True
|
||
|
|
|
||
|
|
@property
|
||
|
|
def ratio(self) -> float:
|
||
|
|
if self._character_count == 0:
|
||
|
|
return 0.0
|
||
|
|
|
||
|
|
return self._successive_upper_lower_count_final / self._character_count
|
||
|
|
|
||
|
|
|
||
|
|
class ArabicIsolatedFormPlugin(MessDetectorPlugin):
|
||
|
|
def __init__(self) -> None:
|
||
|
|
self._character_count: int = 0
|
||
|
|
self._isolated_form_count: int = 0
|
||
|
|
|
||
|
|
def reset(self) -> None: # pragma: no cover
|
||
|
|
self._character_count = 0
|
||
|
|
self._isolated_form_count = 0
|
||
|
|
|
||
|
|
def eligible(self, character: str) -> bool:
|
||
|
|
return is_arabic(character)
|
||
|
|
|
||
|
|
def feed(self, character: str) -> None:
|
||
|
|
self._character_count += 1
|
||
|
|
|
||
|
|
if is_arabic_isolated_form(character):
|
||
|
|
self._isolated_form_count += 1
|
||
|
|
|
||
|
|
@property
|
||
|
|
def ratio(self) -> float:
|
||
|
|
if self._character_count < 8:
|
||
|
|
return 0.0
|
||
|
|
|
||
|
|
isolated_form_usage: float = self._isolated_form_count / self._character_count
|
||
|
|
|
||
|
|
return isolated_form_usage
|
||
|
|
|
||
|
|
|
||
|
|
@lru_cache(maxsize=1024)
|
||
|
|
def is_suspiciously_successive_range(
|
||
|
|
unicode_range_a: Optional[str], unicode_range_b: Optional[str]
|
||
|
|
) -> bool:
|
||
|
|
"""
|
||
|
|
Determine if two Unicode range seen next to each other can be considered as suspicious.
|
||
|
|
"""
|
||
|
|
if unicode_range_a is None or unicode_range_b is None:
|
||
|
|
return True
|
||
|
|
|
||
|
|
if unicode_range_a == unicode_range_b:
|
||
|
|
return False
|
||
|
|
|
||
|
|
if "Latin" in unicode_range_a and "Latin" in unicode_range_b:
|
||
|
|
return False
|
||
|
|
|
||
|
|
if "Emoticons" in unicode_range_a or "Emoticons" in unicode_range_b:
|
||
|
|
return False
|
||
|
|
|
||
|
|
# Latin characters can be accompanied with a combining diacritical mark
|
||
|
|
# eg. Vietnamese.
|
||
|
|
if ("Latin" in unicode_range_a or "Latin" in unicode_range_b) and (
|
||
|
|
"Combining" in unicode_range_a or "Combining" in unicode_range_b
|
||
|
|
):
|
||
|
|
return False
|
||
|
|
|
||
|
|
keywords_range_a, keywords_range_b = unicode_range_a.split(
|
||
|
|
" "
|
||
|
|
), unicode_range_b.split(" ")
|
||
|
|
|
||
|
|
for el in keywords_range_a:
|
||
|
|
if el in UNICODE_SECONDARY_RANGE_KEYWORD:
|
||
|
|
continue
|
||
|
|
if el in keywords_range_b:
|
||
|
|
return False
|
||
|
|
|
||
|
|
# Japanese Exception
|
||
|
|
range_a_jp_chars, range_b_jp_chars = (
|
||
|
|
unicode_range_a
|
||
|
|
in (
|
||
|
|
"Hiragana",
|
||
|
|
"Katakana",
|
||
|
|
),
|
||
|
|
unicode_range_b in ("Hiragana", "Katakana"),
|
||
|
|
)
|
||
|
|
if (range_a_jp_chars or range_b_jp_chars) and (
|
||
|
|
"CJK" in unicode_range_a or "CJK" in unicode_range_b
|
||
|
|
):
|
||
|
|
return False
|
||
|
|
if range_a_jp_chars and range_b_jp_chars:
|
||
|
|
return False
|
||
|
|
|
||
|
|
if "Hangul" in unicode_range_a or "Hangul" in unicode_range_b:
|
||
|
|
if "CJK" in unicode_range_a or "CJK" in unicode_range_b:
|
||
|
|
return False
|
||
|
|
if unicode_range_a == "Basic Latin" or unicode_range_b == "Basic Latin":
|
||
|
|
return False
|
||
|
|
|
||
|
|
# Chinese/Japanese use dedicated range for punctuation and/or separators.
|
||
|
|
if ("CJK" in unicode_range_a or "CJK" in unicode_range_b) or (
|
||
|
|
unicode_range_a in ["Katakana", "Hiragana"]
|
||
|
|
and unicode_range_b in ["Katakana", "Hiragana"]
|
||
|
|
):
|
||
|
|
if "Punctuation" in unicode_range_a or "Punctuation" in unicode_range_b:
|
||
|
|
return False
|
||
|
|
if "Forms" in unicode_range_a or "Forms" in unicode_range_b:
|
||
|
|
return False
|
||
|
|
if unicode_range_a == "Basic Latin" or unicode_range_b == "Basic Latin":
|
||
|
|
return False
|
||
|
|
|
||
|
|
return True
|
||
|
|
|
||
|
|
|
||
|
|
@lru_cache(maxsize=2048)
|
||
|
|
def mess_ratio(
|
||
|
|
decoded_sequence: str, maximum_threshold: float = 0.2, debug: bool = False
|
||
|
|
) -> float:
|
||
|
|
"""
|
||
|
|
Compute a mess ratio given a decoded bytes sequence. The maximum threshold does stop the computation earlier.
|
||
|
|
"""
|
||
|
|
|
||
|
|
detectors: List[MessDetectorPlugin] = [
|
||
|
|
md_class() for md_class in MessDetectorPlugin.__subclasses__()
|
||
|
|
]
|
||
|
|
|
||
|
|
length: int = len(decoded_sequence) + 1
|
||
|
|
|
||
|
|
mean_mess_ratio: float = 0.0
|
||
|
|
|
||
|
|
if length < 512:
|
||
|
|
intermediary_mean_mess_ratio_calc: int = 32
|
||
|
|
elif length <= 1024:
|
||
|
|
intermediary_mean_mess_ratio_calc = 64
|
||
|
|
else:
|
||
|
|
intermediary_mean_mess_ratio_calc = 128
|
||
|
|
|
||
|
|
for character, index in zip(decoded_sequence + "\n", range(length)):
|
||
|
|
for detector in detectors:
|
||
|
|
if detector.eligible(character):
|
||
|
|
detector.feed(character)
|
||
|
|
|
||
|
|
if (
|
||
|
|
index > 0 and index % intermediary_mean_mess_ratio_calc == 0
|
||
|
|
) or index == length - 1:
|
||
|
|
mean_mess_ratio = sum(dt.ratio for dt in detectors)
|
||
|
|
|
||
|
|
if mean_mess_ratio >= maximum_threshold:
|
||
|
|
break
|
||
|
|
|
||
|
|
if debug:
|
||
|
|
logger = getLogger("charset_normalizer")
|
||
|
|
|
||
|
|
logger.log(
|
||
|
|
TRACE,
|
||
|
|
"Mess-detector extended-analysis start. "
|
||
|
|
f"intermediary_mean_mess_ratio_calc={intermediary_mean_mess_ratio_calc} mean_mess_ratio={mean_mess_ratio} "
|
||
|
|
f"maximum_threshold={maximum_threshold}",
|
||
|
|
)
|
||
|
|
|
||
|
|
if len(decoded_sequence) > 16:
|
||
|
|
logger.log(TRACE, f"Starting with: {decoded_sequence[:16]}")
|
||
|
|
logger.log(TRACE, f"Ending with: {decoded_sequence[-16::]}")
|
||
|
|
|
||
|
|
for dt in detectors: # pragma: nocover
|
||
|
|
logger.log(TRACE, f"{dt.__class__}: {dt.ratio}")
|
||
|
|
|
||
|
|
return round(mean_mess_ratio, 3)
|