gtm/lib/python3.12/site-packages/charset_normalizer/md.py

from functools import lru_cache
from logging import getLogger
from typing import List, Optional

from .constant import (
    COMMON_SAFE_ASCII_CHARACTERS,
    TRACE,
    UNICODE_SECONDARY_RANGE_KEYWORD,
)
from .utils import (
    is_accentuated,
    is_arabic,
    is_arabic_isolated_form,
    is_case_variable,
    is_cjk,
    is_emoticon,
    is_hangul,
    is_hiragana,
    is_katakana,
    is_latin,
    is_punctuation,
    is_separator,
    is_symbol,
    is_thai,
    is_unprintable,
    remove_accent,
    unicode_range,
)


class MessDetectorPlugin:
    """
    Base abstract class used for mess detection plugins.
    All detectors MUST extend and implement given methods.
    """

    def eligible(self, character: str) -> bool:
        """
        Determine if given character should be fed in.
        """
        raise NotImplementedError  # pragma: nocover

    def feed(self, character: str) -> None:
        """
        The main routine to be executed upon character.
        Insert the logic in witch the text would be considered chaotic.
        """
        raise NotImplementedError  # pragma: nocover

    def reset(self) -> None:  # pragma: no cover
        """
        Permit to reset the plugin to the initial state.
        """
        raise NotImplementedError

    @property
    def ratio(self) -> float:
        """
        Compute the chaos ratio based on what your feed() has seen.
        Must NOT be lower than 0.; No restriction gt 0.
        """
        raise NotImplementedError  # pragma: nocover


class TooManySymbolOrPunctuationPlugin(MessDetectorPlugin):
    def __init__(self) -> None:
        self._punctuation_count: int = 0
        self._symbol_count: int = 0
        self._character_count: int = 0

        self._last_printable_char: Optional[str] = None
        self._frenzy_symbol_in_word: bool = False

    def eligible(self, character: str) -> bool:
        return character.isprintable()

    def feed(self, character: str) -> None:
        self._character_count += 1

        if (
            character != self._last_printable_char
            and character not in COMMON_SAFE_ASCII_CHARACTERS
        ):
            if is_punctuation(character):
                self._punctuation_count += 1
            elif (
                character.isdigit() is False
                and is_symbol(character)
                and is_emoticon(character) is False
            ):
                self._symbol_count += 2

        self._last_printable_char = character

    def reset(self) -> None:  # pragma: no cover
        self._punctuation_count = 0
        self._character_count = 0
        self._symbol_count = 0

    @property
    def ratio(self) -> float:
        if self._character_count == 0:
            return 0.0

        ratio_of_punctuation: float = (
            self._punctuation_count + self._symbol_count
        ) / self._character_count

        return ratio_of_punctuation if ratio_of_punctuation >= 0.3 else 0.0


class TooManyAccentuatedPlugin(MessDetectorPlugin):
    def __init__(self) -> None:
        self._character_count: int = 0
        self._accentuated_count: int = 0

    def eligible(self, character: str) -> bool:
        return character.isalpha()

    def feed(self, character: str) -> None:
        self._character_count += 1

        if is_accentuated(character):
            self._accentuated_count += 1

    def reset(self) -> None:  # pragma: no cover
        self._character_count = 0
        self._accentuated_count = 0

    @property
    def ratio(self) -> float:
        if self._character_count < 8:
            return 0.0

        ratio_of_accentuation: float = self._accentuated_count / self._character_count
        return ratio_of_accentuation if ratio_of_accentuation >= 0.35 else 0.0


class UnprintablePlugin(MessDetectorPlugin):
    def __init__(self) -> None:
        self._unprintable_count: int = 0
        self._character_count: int = 0

    def eligible(self, character: str) -> bool:
        return True

    def feed(self, character: str) -> None:
        if is_unprintable(character):
            self._unprintable_count += 1
        self._character_count += 1

    def reset(self) -> None:  # pragma: no cover
        self._unprintable_count = 0

    @property
    def ratio(self) -> float:
        if self._character_count == 0:
            return 0.0

        return (self._unprintable_count * 8) / self._character_count


class SuspiciousDuplicateAccentPlugin(MessDetectorPlugin):
    def __init__(self) -> None:
        self._successive_count: int = 0
        self._character_count: int = 0

        self._last_latin_character: Optional[str] = None

    def eligible(self, character: str) -> bool:
        return character.isalpha() and is_latin(character)

    def feed(self, character: str) -> None:
        self._character_count += 1
        if (
            self._last_latin_character is not None
            and is_accentuated(character)
            and is_accentuated(self._last_latin_character)
        ):
            if character.isupper() and self._last_latin_character.isupper():
                self._successive_count += 1
            # Worse if its the same char duplicated with different accent.
            if remove_accent(character) == remove_accent(self._last_latin_character):
                self._successive_count += 1
        self._last_latin_character = character

    def reset(self) -> None:  # pragma: no cover
        self._successive_count = 0
        self._character_count = 0
        self._last_latin_character = None

    @property
    def ratio(self) -> float:
        if self._character_count == 0:
            return 0.0

        return (self._successive_count * 2) / self._character_count


class SuspiciousRange(MessDetectorPlugin):
    def __init__(self) -> None:
        self._suspicious_successive_range_count: int = 0
        self._character_count: int = 0
        self._last_printable_seen: Optional[str] = None

    def eligible(self, character: str) -> bool:
        return character.isprintable()

    def feed(self, character: str) -> None:
        self._character_count += 1

        if (
            character.isspace()
            or is_punctuation(character)
            or character in COMMON_SAFE_ASCII_CHARACTERS
        ):
            self._last_printable_seen = None
            return

        if self._last_printable_seen is None:
            self._last_printable_seen = character
            return

        unicode_range_a: Optional[str] = unicode_range(self._last_printable_seen)
        unicode_range_b: Optional[str] = unicode_range(character)

        if is_suspiciously_successive_range(unicode_range_a, unicode_range_b):
            self._suspicious_successive_range_count += 1

        self._last_printable_seen = character

    def reset(self) -> None:  # pragma: no cover
        self._character_count = 0
        self._suspicious_successive_range_count = 0
        self._last_printable_seen = None

    @property
    def ratio(self) -> float:
        if self._character_count <= 24:
            return 0.0

        ratio_of_suspicious_range_usage: float = (
            self._suspicious_successive_range_count * 2
        ) / self._character_count

        return ratio_of_suspicious_range_usage


class SuperWeirdWordPlugin(MessDetectorPlugin):
    def __init__(self) -> None:
        self._word_count: int = 0
        self._bad_word_count: int = 0
        self._foreign_long_count: int = 0

        self._is_current_word_bad: bool = False
        self._foreign_long_watch: bool = False

        self._character_count: int = 0
        self._bad_character_count: int = 0

        self._buffer: str = ""
        self._buffer_accent_count: int = 0

    def eligible(self, character: str) -> bool:
        return True

    def feed(self, character: str) -> None:
        if character.isalpha():
            self._buffer += character
            if is_accentuated(character):
                self._buffer_accent_count += 1
            if (
                self._foreign_long_watch is False
                and (is_latin(character) is False or is_accentuated(character))
                and is_cjk(character) is False
                and is_hangul(character) is False
                and is_katakana(character) is False
                and is_hiragana(character) is False
                and is_thai(character) is False
            ):
                self._foreign_long_watch = True
            return
        if not self._buffer:
            return
        if (
            character.isspace() or is_punctuation(character) or is_separator(character)
        ) and self._buffer:
            self._word_count += 1
            buffer_length: int = len(self._buffer)

            self._character_count += buffer_length

            if buffer_length >= 4:
                if self._buffer_accent_count / buffer_length > 0.34:
                    self._is_current_word_bad = True
                # Word/Buffer ending with an upper case accentuated letter are so rare,
                # that we will consider them all as suspicious. Same weight as foreign_long suspicious.
                if (
                    is_accentuated(self._buffer[-1])
                    and self._buffer[-1].isupper()
                    and all(_.isupper() for _ in self._buffer) is False
                ):
                    self._foreign_long_count += 1
                    self._is_current_word_bad = True
            if buffer_length >= 24 and self._foreign_long_watch:
                camel_case_dst = [
                    i
                    for c, i in zip(self._buffer, range(0, buffer_length))
                    if c.isupper()
                ]
                probable_camel_cased: bool = False

                if camel_case_dst and (len(camel_case_dst) / buffer_length <= 0.3):
                    probable_camel_cased = True

                if not probable_camel_cased:
                    self._foreign_long_count += 1
                    self._is_current_word_bad = True

            if self._is_current_word_bad:
                self._bad_word_count += 1
                self._bad_character_count += len(self._buffer)
                self._is_current_word_bad = False

            self._foreign_long_watch = False
            self._buffer = ""
            self._buffer_accent_count = 0
        elif (
            character not in {"<", ">", "-", "=", "~", "|", "_"}
            and character.isdigit() is False
            and is_symbol(character)
        ):
            self._is_current_word_bad = True
            self._buffer += character

    def reset(self) -> None:  # pragma: no cover
        self._buffer = ""
        self._is_current_word_bad = False
        self._foreign_long_watch = False
        self._bad_word_count = 0
        self._word_count = 0
        self._character_count = 0
        self._bad_character_count = 0
        self._foreign_long_count = 0

    @property
    def ratio(self) -> float:
        if self._word_count <= 10 and self._foreign_long_count == 0:
            return 0.0

        return self._bad_character_count / self._character_count


class CjkInvalidStopPlugin(MessDetectorPlugin):
    """
    GB(Chinese) based encoding often render the stop incorrectly when the content does not fit and
    can be easily detected. Searching for the overuse of '丅' and '丄'.
    """

    def __init__(self) -> None:
        self._wrong_stop_count: int = 0
        self._cjk_character_count: int = 0

    def eligible(self, character: str) -> bool:
        return True

    def feed(self, character: str) -> None:
        if character in {"丅", "丄"}:
            self._wrong_stop_count += 1
            return
        if is_cjk(character):
            self._cjk_character_count += 1

    def reset(self) -> None:  # pragma: no cover
        self._wrong_stop_count = 0
        self._cjk_character_count = 0

    @property
    def ratio(self) -> float:
        if self._cjk_character_count < 16:
            return 0.0
        return self._wrong_stop_count / self._cjk_character_count


class ArchaicUpperLowerPlugin(MessDetectorPlugin):
    def __init__(self) -> None:
        self._buf: bool = False

        self._character_count_since_last_sep: int = 0

        self._successive_upper_lower_count: int = 0
        self._successive_upper_lower_count_final: int = 0

        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)