GIF89a=( õ' 7IAXKgNgYvYx\%wh…hŽth%ˆs%—x¨}9®Œ©€&©‰%¶†(¹–.¹5·œD¹&Çš)ÇŸ5ǘ;Í£*È¡&Õ²)ׯ7×µ<Ñ»4ï°3ø‘HÖ§KͯT÷¨Yÿšqÿ»qÿÔFØ !ù ' !ÿ NETSCAPE2.0 , =( þÀ“pH,È¤rÉl:ŸÐ¨tJ­Z¯Ø¬vËíz¿à°xL.›Ïè´zÍn»ßð¸|N¯Ûïø¼~Ïïûÿ€‚ƒ„…†‡ˆ‰Š‹ŒŽ‘’“”•–—˜™š›œžŸ ¡¢£¤¥¦§gª«ªE¯°¨¬ª±²Œ¹º¹E¾­”´ÂB¶¯ §Åȸ»ÑD¾¿Á•ÄÅ®° ÝH¾ÒLÀÆDÙ«D¶BÝïðÀ¾DÑÑÔTÌÍíH òGö¨A RÎڐ |¥ ٭&ºìE8œ¹kGÔAÞpx­a¶­ã R2XB®åE8I€Õ6Xî:vT)äžþÀq¦è³¥ì仕F~%xñ  4#ZÔ‰O|-4Bs‘X:= QÉ œš lºÒyXJŠGȦ|s hÏíK–3l7·B|¥$'7Jީܪ‰‡àá”Dæn=Pƒ ¤Òëí‰`䌨ljóá¯Éüv>á–Á¼5 ½.69ûϸd«­ºÀûnlv©‹ªîf{¬ÜãPbŸ  l5‘Ž¯pß ´ ˜3aÅùäI«O’ý·‘áÞ‡˜¾Æ‚ÙÏiÇÿ‹Àƒ #öó)pâš Þ½ ‘Ý{ó)vmÞü%D~ 6f s}ŃƒDØW Eþ`‡þ À…L8xá†ç˜{)x`X/> Ì}mø‚–RØ‘*|`D=‚Ø_ ^ð5 !_…'aä“OÚ—7âcð`D”Cx`ÝÂ¥ä‹éY¹—F¼¤¥Š?¡Õ™ n@`} lď’ÄÉ@4>ñd œ à‘vÒxNÃ×™@žd=ˆgsžG±æ ´²æud &p8Qñ)ˆ«lXD©øÜéAžHìySun jª×k*D¤LH] †¦§C™Jä–´Xb~ʪwStŽ6K,°£qÁœ:9ت:¨þªl¨@¡`‚ûÚ ».Û¬¯t‹ÆSÉ[:°=Š‹„‘Nåû”Ìî{¿ÂA ‡Rà›ÀÙ6úë°Ÿð0Ä_ ½;ÃϱîÉì^ÇÛÇ#Ëë¼ôº!±Ä˜íUîÅÇ;0L1óÁµö«p% AÀºU̬ݵ¼á%霼€‡¯Á~`ÏG¯»À× ­²± =4ªnpð3¾¤³¯­ü¾¦îuÙuµÙ®|%2ÊIÿür¦#0·ÔJ``8È@S@5ê¢ ö×Þ^`8EÜ]ý.뜃Âç 7 ú ȉÞj œ½Dç zý¸iþœÑÙûÄë!ˆÞÀl§Ïw‹*DçI€nEX¯¬¼ &A¬Go¼QföõFç°¯;é¦÷îŽêJ°îúôF5¡ÌQ|îúöXªæ»TÁÏyñêï]ê² o óÎC=öõ›ÒÓPB@ D×½œä(>èCÂxŽ`±«Ÿ–JЀ»Û á¤±p+eE0`ëŽ`A Ú/NE€Ø†À9‚@¤à H½7”à‡%B‰`Àl*ƒó‘–‡8 2ñ%¸ —€:Ù1Á‰E¸àux%nP1ð!‘ðC)¾P81lÑɸF#ˆ€{´âé°ÈB„0>±û °b¡Š´±O‚3È–Ù()yRpbµ¨E.Z‘D8ÊH@% òŒx+%Ù˜Æcü »¸˜fõ¬b·d`Fê™8èXH"ÉÈ-±|1Ô6iI, 2““¬$+](A*jÐ QTÂo‰.ÛU슬Œã„Ž`¯SN¡–¶Äåyše¯ª’­¬‚´b¦Éož œ)åyâ@Ì®3 ÎtT̉°&Ø+žLÀf"Ø-|žçÔ>‡Ðv¦Ðžì\‚ Q1)Ž@Žh#aP72”ˆ™¨$‚ !ù " , =( …7IAXG]KgNgYvYxR"k\%w]'}hŽth%ˆg+ˆs%—r.—m3šx3˜x¨}9®€&©€+¨‡7§‰%¶†(¹–.¹œD¹&ǘ;Í•&ײ)×»4ïÌ6ò§KÍ þ@‘pH,È¤rÉl:ŸÐ¨tJ­Z¯Ø¬vËíz¿à°xL.›Ïè´zÍn»ßð¸|N¯Ûïø¼~Ïïûÿ€‚ƒ„…†‡ˆ‰Š‹ŒŽ‘’“”•–—˜™š›œžŸ ¡¢£¤¥¦§g «¬ E ±± ¨­¶°ººE Á´”·®C¬²§Ç¶Œ»ÓDÃÕƷ¯Ê±H½ºM×ÁGÚ¬D¶BËÁ½î½DÓôTÏÛßîG»ôõC×CÌ l&âž:'òtU³6ɹ#·Ø)€'Ü.6±&ëÍÈ» K(8p0N?!æ2"ÛˆNIJX>R¼ÐO‚M '¡¨2¸*Ÿþ>#n↠å@‚<[:¡Iïf’ ¤TÚ˘CdbÜÙ“[«ŽEú5MBo¤×@€`@„€Êt W-3 ¶Ÿ¡BíêäjIÝ…Eò9[T…$íêﯧ„…•s»Óȳ¹€ÅÚdc®UUρ#±Ùïldj?´í¼²`\ŽÁðÞu|3'ÖŒ]ë6 ¶S#²‡˜FKLÈ *N E´‘áäŠ$˜›eÄYD„ºq«.è촁ƒs \-ÔjA 9²õ÷å- üúM[Âx(ís÷ì®x€|í¡Ù’p¦‚ ŽkÛTÇDpE@WÜ ²Ç]kŠ1¨ þ€·Yb ÓÁ‰l°*n0 ç™—žzBdОu¾7ĉBl€â‰-ºx~|UåU‰  h*Hœ|e"#"?vpÄiŠe6^ˆ„+qâŠm8 #VÇá ‘å–ÄV„œ|Šè•m"сœn|@›U¶ÆΞ—Špb¥G¨ED”€±Úê2FÌIç? >Éxå Œ± ¡¤„%‘žjŸ‘ꄯ<Ìaà9ijÐ2˜D¦È&›†Z`‚å]wþ¼Â:ç6àB¤7eFJ|õÒ§Õ,¨äàFÇ®cS·Ê¶+B°,‘Þ˜ºNûãØ>PADÌHD¹æž«ÄÀnÌ¥}­#Ë’ë QÀÉSÌÂÇ2ÌXÀ{æk²lQÁ2«ÊðÀ¯w|2Í h‹ÄÂG€,m¾¶ë3ÐÙ6-´ÅE¬L°ÆIij*K½ÀÇqï`DwVÍQXœÚÔpeœ±¬Ñ q˜§Tœ½µƒ°Œìu Â<¶aØ*At¯lmEØ ü ôÛN[P1ÔÛ¦­±$ÜÆ@`ùåDpy¶yXvCAyåB`ŽD¶ 0QwG#¯ æš[^Äþ $ÀÓÝǦ{„L™[±úKÄgÌ;ï£S~¹ìGX.ôgoT.»åˆ°ùŸûù¡?1zö¦Ÿž:ÅgÁ|ìL¹ „®£œŠ‚à0œ]PÁ^p F<"•ç?!,ñ‡N4—…PÄ Á„ö¨Û:Tè@hÀ‹%táÿ:ø-žI<`þ‹p I….)^ 40D#p@ƒj4–؀:²‰1Øâr˜¼F2oW¼#Z†;$Q q” ‘ ÂK¦ñNl#29 !’F@¥Bh·ᏀL!—XFóLH‘Kh¤.«hE&JòG¨¥<™WN!€ÑÙÚˆY„@†>Œž19J" 2,/ &.GXB%ÌRÈ9B6¹W]’î×ÔW¥’IÎ$ ñ‹ÓŒE8YÆ ¼³™ñA5“à®Q.aŸB€&Ø©³ JÁ—! ¦t)K%tœ-¦JF bòNMxLôþ)ÐR¸Ð™‘ èÝ6‘O!THÌ„HÛ ‰ !ù ) , =( …AXKgNgYvYxR"k\%wh…hŽh%ˆg+ˆs%—r.—x3˜x¨}9®€&©€+¨Œ,©‡7§‰%¶†(¹–.¹5·&Çš)ǘ;Í•&×£*Ȳ)ׯ7×»4ï°3øÌ6ò‘HÖ§KÍ»Hó¯T÷¨Yÿ»qÿÇhÿ þÀ”pH,È¤rÉl:ŸÐ¨tJ­Z¯Ø¬vËíz¿à°xL.›Ïè´zÍn»ßð¸|N¯Ûïø¼~Ïïûÿ€‚ƒ„…†‡ˆ‰Š‹ŒŽ‘’“”•–—˜™š›œžŸ ¡¢£¤¥¦§g ª« E$±²¨ª­ · °²½$E$ÂÕ««D· Í ¿¦Ç¶¸ÌŒ¾³CÃÅÆ E ééH½MÛÂGâªD­ çBêêϾD²ÒaÀà€Š1r­ðÓ¤ ÔožzU!L˜C'¾yW½UGtäÇïÙllê0×àÂuGþ)AÀs[þ·xì ÁxO%ƒûX2ó—  P£n›R/¡ÑšHše+êDm?# —‘Ç£6¡8íJ¡ŸâDiäªM¥Ö„ôj“¬¹£5oQ7°- <‡ *´lãÓŒ2r/a!l)dÈ A™ÈE¢ôÔ͆…ð ;Ö˜c ¡%ß‚’Ùˆâ¸b½—pe~C"BíëÚHïeF2§æŠ8qb t_`urŠeü wÅu3êæPv§h•"ß`íÍxçLĹÜÖ3á  ~Öº“®›¸ÏMDfJÙ °„ÛµáWõ%§œ‚à©–‚X Ó؁)@®Ñ›Eþ´wëuÅSxb8y\mÖzœ¥§ZbºE—ÂLªÌw!y(>¡™wú=Ç|ÅÝs¢d €CÁW)HÜcC$€L Ä7„r.á\{)@ð` @ äXÈ$PD” `šaG:§æˆOˆ72EÐamn]ù"ŒcÊxÑŒ° &dR8`g«iÙŸLR!¦P …d’ä¡“¦ðÎTƒ¦ià|À _ ¥ Qi#¦Šg›Æ ›noMµ ›V ã£)p ç£ÎW…š=Âeªk§†j„ ´®1ß²sÉxéW«jšl|0¯B0Û, \jÛ´›6±¬¶C ÛíWþï|ëÙ‹¸ñzĸV {ì;Ýñn¼òVˆm³I¼³.Ðã¤PN¥ ²µ¼„µCã+¹ÍByî£Ñ¾HŸ›ëê 7ìYÆFTk¨SaoaY$Dµœìï¿Ã29RÈkt Çïfñ ÇÒ:ÀÐSp¹3ÇI¨â¥DZÄ ü9Ïýögñ½­uÔ*3)O‘˜Ö[_hv ,àî×Et Ÿé¶BH€ Õ[ü±64M@ÔSÌM7dÐl5-ÄÙU܍´©zߌ3Ô€3ž„ „ ¶ÛPô½5×g› êÚ˜kN„Ý…0Îj4€Ìë°“#{þÕ3S2çKÜ'ợlø¼Ú2K{° {Û¶?žm𸧠ËI¼nEò='êüóºè^üæÃ_Û=°óž‚ì#Oý¿Í'¡½áo..ÏYìnüñCœO±Áa¿¢Kô½o,üÄËbö²çºíï{ËC Ú— "”Ï{ËK ÍÒw„õ±Oz dÕ¨à:$ ƒô—«v»] A#ð «€¿šéz)Rx׿ˆ¥‚d``èw-îyÏf×K!ð€þ­Ð|ìPľ„=Ì`ý(f” 'Pa ¥ÐBJa%Ðâf§„%Š¡}FàáÝ×6>ÉäŠG"éŽè=ø!oŠ°^FP¼Ø©Q„ÀCÙÁ`(Ž\ÄÝ® ©Â$<n@dÄ E#ììUÒI! ‚#lù‹`k¦ÐÇ'Rró’ZýNBÈMF Í[¤+‹ðɈ-áwj¨¥þ8¾rá ,VÂh„"|½œ=×G_¦Ñ™EØ 0i*%̲˜Æda0mV‚k¾)›;„&6 p>ÓjK “¦Ç# âDÂ:ûc?:R Ó¬fÞéI-Ì“•Ã<ä=™Ï7˜3œ¨˜c2ŒW ,ˆ”8(T™P‰F¡Jhç"‚ ; 403WebShell
403Webshell
Server IP : 172.67.177.218  /  Your IP : 216.73.216.195
Web Server : LiteSpeed
System : Linux premium229.web-hosting.com 4.18.0-553.45.1.lve.el8.x86_64 #1 SMP Wed Mar 26 12:08:09 UTC 2025 x86_64
User : akhalid ( 749)
PHP Version : 8.3.22
Disable Function : NONE
MySQL : OFF  |  cURL : ON  |  WGET : ON  |  Perl : ON  |  Python : ON  |  Sudo : OFF  |  Pkexec : OFF
Directory :  /opt/hc_python/lib/python3.12/site-packages/charset_normalizer/

Upload File :
current_dir [ Writeable ] document_root [ Writeable ]

 

Command :

[ Back ]     

Current File : /opt/hc_python/lib/python3.12/site-packages/charset_normalizer/md.py
from __future__ import annotations

from functools import lru_cache
from logging import getLogger

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: str | None = 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:  # Abstract
        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:  # Abstract
        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:  # Abstract
        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: str | None = 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:  # Abstract
        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: str | None = 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: str | None = unicode_range(self._last_printable_seen)
        unicode_range_b: str | None = 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:  # Abstract
        self._character_count = 0
        self._suspicious_successive_range_count = 0
        self._last_printable_seen = None

    @property
    def ratio(self) -> float:
        if self._character_count <= 13:
            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
        self._buffer_glyph_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
            if (
                is_cjk(character)
                or is_hangul(character)
                or is_katakana(character)
                or is_hiragana(character)
                or is_thai(character)
            ):
                self._buffer_glyph_count += 1
            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 >= 0.5:
                    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.
                elif (
                    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
                elif self._buffer_glyph_count == 1:
                    self._is_current_word_bad = True
                    self._foreign_long_count += 1
            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
            self._buffer_glyph_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:  # Abstract
        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:  # Abstract
        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: str | None = 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:  # Abstract
        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:  # Abstract
        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: str | None, unicode_range_b: str | None
) -> 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:
            logger.log(TRACE, f"{dt.__class__}: {dt.ratio}")

    return round(mean_mess_ratio, 3)

Youez - 2016 - github.com/yon3zu
LinuXploit