+ 3i:Rt^RIt^RIt^RIt^RIHtHtHt^RIH t ^RI H t ^RI H t HtHt^RIHt^RIHt^RIHt^R IHt^R IHt^R IHt^R IHt!R R4tR#)a Module containing the UniversalDetector detector class, which is the primary class a user of ``chardet`` should use. :author: Mark Pilgrim (initial port to Python) :author: Shy Shalom (original C code) :author: Dan Blanchard (major refactoring for 3.0) :author: Ian Cordasco N)ListOptionalUnion)CharSetGroupProber) CharSetProber) InputStateLanguageFilter ProbingState)EscCharSetProber) Latin1Prober)MacRomanProber)MBCSGroupProber ResultDict)SBCSGroupProber) UTF1632Proberca]tRt^8toRtRt]P!R4t]P!R4t ]P!R4t RRRR R R R R RRRRRRRR/t RRRRRRRRRRRRRR/t ] PR3V3R lR!llt]V3R"lR#l4t]V3R$lR%l4t]V3R&lR'l4tV3R(lR)ltV3R*lR+ltV3R,lR-ltR.tVtR/#)0UniversalDetectoraI The ``UniversalDetector`` class underlies the ``chardet.detect`` function and coordinates all of the different charset probers. To get a ``dict`` containing an encoding and its confidence, you can simply run: .. code:: u = UniversalDetector() u.feed(some_bytes) u.close() detected = u.result g?s[-]s(|~{)s[-]z iso-8859-1z Windows-1252z iso-8859-2z Windows-1250z iso-8859-5z Windows-1251z iso-8859-6z Windows-1256z iso-8859-7z Windows-1253z iso-8859-8z Windows-1255z iso-8859-9z Windows-1254z iso-8859-13z Windows-1257asciiztis-620z ISO-8859-11gb2312GB18030zeuc-krCP949zutf-16leUTF-16Fc*<V^8dQhRS[RS[RR/#) lang_filtershould_rename_legacyreturnN)rbool)format __classdict__s";/usr/lib/python3/dist-packages/chardet/universaldetector.py __annotate__UniversalDetector.__annotate__ds)##  c"RVnRVn.VnRRRRRR/VnRVnRVn\ PVnRVn Wn \P!\4VnRVnW nVP#4R#)Nencoding confidencelanguageFr$)_esc_charset_prober_utf1632_prober_charset_probersresultdone _got_datar PURE_ASCII _input_state _last_charrlogging getLogger__name__logger_has_win_bytesrreset)selfrrs&&&r!__init__UniversalDetector.__init__ds @D 8<57  # #   &11&''1 #$8! r$c <V^8dQhRS[/#rr)int)rr s"r!r"r#|s!!S!r$cVP#N)r1r9s&r! input_stateUniversalDetector.input_state{s   r$c <V^8dQhRS[/#r=)r)rr s"r!r"r#s##t#r$cVP#r@)r7rAs&r! has_win_bytesUniversalDetector.has_win_bytess"""r$c0<V^8dQhRS[S[,/#r=)rr)rr s"r!r"r#s%%m!4%r$cVP#r@)r,rAs&r!charset_probers!UniversalDetector.charset_proberss$$$r$c<V^8dQhRR/#)rrN)rr s"r!r"r#str$c xRRRRRR/VnRVnRVnRVn\P VnRVnVP'dVPP4VP'dVPP4VPFpVP4K R#)z Reset the UniversalDetector and all of its probers back to their initial states. This is called by ``__init__``, so you only need to call this directly in between analyses of different documents. r&Nr'r(r)Fr$) r-r.r/r7rr0r1r2r*r8r+r,)r9probers& r!r8UniversalDetector.resets "4sJM  #&11  # # #  $ $ * * ,      & & (++F LLN,r$c:<V^8dQhRS[S[S[3,RR/#)rbyte_strrN)rbytes bytearray)rr s"r!r"r#s)A+A+U5)#34A+A+r$c VP'dR#V'gR#\V\4'g \V4pVP'Eg(VP \ P 4'dRRRRRR/VnMVP \ P\ P34'dRRRRRR/VnMVP R 4'dRR RRRR/VnMgVP R 4'dRR RRRR/VnMBVP \ P\ P34'dRR RRRR/VnRVnVPR,e RVnR#VP\P8XdVPP!V4'd\P"Vn MfVP\P8XdHVP$P!VP&V,4'd\P(Vn VRRVnVP*'g\-4VnVP*P.\0P28XdqVP*P5V4\0P68XdCRVP*P8RVP*P;4RR/VnRVnR#VP\P(8XdVP<'g\?VP@4VnVP<P5V4\0P68XdWRVP<P8RVP<P;4RVP<PB/VnRVnR#R#VP\P"8XEdYVPD'g\GVP@4.Vn"VP@\HPJ,'d$VPDPM\O44VPDPM\Q44VPDPM\S44VPDF_pVP5V4\0P68XgK)RVP8RVP;4RVPB/VnRVnM VPTP!V4'd RVn+R#R#R#)a Takes a chunk of a document and feeds it through all of the relevant charset probers. After calling ``feed``, you can check the value of the ``done`` attribute to see if you need to continue feeding the ``UniversalDetector`` more data, or if it has made a prediction (in the ``result`` attribute). .. note:: You should always call ``close`` when you're done feeding in your document if ``done`` is not already ``True``. Nr&z UTF-8-SIGr'?r)zUTF-32szX-ISO-10646-UCS-4-3412szX-ISO-10646-UCS-4-2143rT),r. isinstancerTr/ startswithcodecsBOM_UTF8r- BOM_UTF32_LE BOM_UTF32_BEBOM_LEBOM_BEr1rr0HIGH_BYTE_DETECTORsearch HIGH_BYTE ESC_DETECTORr2 ESC_ASCIIr+rstater DETECTINGfeedFOUND_IT charset_nameget_confidencer*r rr)r,r rNON_CJKappendrr r WIN_BYTE_DETECTORr7)r9rRrOs&& r!rhUniversalDetector.feeds- 999  (I.. *H~~~""6??33  # $$f&9&96;N;N%OPP *8\3 TVW $$%899 8 #  $$%899 8 #  $$fmmV]]%CDD *8\3 TVW !DN{{:&2      5 5 5&&--h77$.$8$8!!!Z%:%::%%,,T__x-GHH$.$8$8!"23-####0?D    % %)?)? ?##((2l6K6KK 4 4 A A $"6"6"E"E"G !     4 4 4++++;D//;;x(L,A,AA"F$7$7$f&;&;&="FOO#DK !%DI0%%,,X66&*#7#7r$c <V^8dQhRS[/#r=r)rr s"r!r"r#sMMzMr$c  VP'd VP#RVnVP'gVPP R4EMxVP \ P8XdRRRRRR/VnEMJVP \ P8XEd+R pR pR pVPF)pV'gK VP4pW8gK%TpTpK+ V'dW P8dVPpVfQhVP4pVP4pVPR 4'd.VP'dVP P#We4pVP$'d5VP&P#T;'gRP4V4pRVRVRVP(/VnVPP+4\,P.8:dVPR,fVPP R 4VPFpV'gK \1V\24'dVVP4FCpVPP R VPVP(VP44KE KxVPP R VPVP(VP44K VP#)z Stop analyzing the current document and come up with a final prediction. :returns: The ``result`` attribute, a ``dict`` with the keys `encoding`, `confidence`, and `language`. Tzno data received!r&rr'rVr)rWNr(ziso-8859z no probers hit minimum thresholdz%s %s confidence = %s)r.r-r/r6debugr1rr0rcr,rkMINIMUM_THRESHOLDrjlowerrZr7 ISO_WIN_MAPgetr LEGACY_MAPr)getEffectiveLevelr3DEBUGrYrprobers) r9prober_confidencemax_prober_confidence max_proberrOrjlower_charset_namer' group_probers & r!closeUniversalDetector.closesy 999;;  ~~~ KK  1 2  *"7"7 7%w c:rRDK  *"6"6 6 $ $' !J//$*$9$9$;!$<,=)!'J 047M7MM)66 #///%1%7%7%9"'668 &00<<***'+'7'7';';.( ,,,#'??#6#6%++224l$L  * 3 3  ;; ( ( *gmm ;{{:&. !!"DE$($9$9L' !,0BCC&2&:&:F KK-- 7 & 3 3 & & 5 5 7 '; ))3(55(11(779 %:${{r$) r,r*r/r7r1r2r+r.rr6r-rN)r5 __module__ __qualname____firstlineno____doc__rsrecompilerardrnrurwrALLr:propertyrBrFrJr8rhr__static_attributes____classdictcell__)r s@r!rr8s N3::l+L >2nnnnnnn~ K n=n)'HJ'5&8&8%*.!!##%%&A+A+FMMr$r)rr[r3rtypingrrrcharsetgroupproberr charsetproberrenumsrrr escproberr latin1proberr macromanproberr mbcsgroupproberr resultdictrsbcsgroupproberr utf1632proberrrrMr$r!rsH8 ((2(;;'&*,",(rrr$