iSrSSKJrJrJrJrJr SSKJr SSK J r SSK J r SSK Jr SSKJr S S KJr S S KJr \(aSS KJrJr "S S\5rg)aThis module implements an Earley parser with a dynamic lexer The core Earley algorithm used here is based on Elizabeth Scott's implementation, here: https://www.sciencedirect.com/science/article/pii/S1571066108001497 That is probably the best reference for understanding the algorithm here. The Earley parser outputs an SPPF-tree as per that document. The SPPF tree format is better documented here: http://www.bramvandersanden.com/post/2014/06/shared-packed-parse-forest/ Instead of running a lexer beforehand, or using a costy char-by-char method, this parser uses regular expressions by necessity, achieving high-performance while maintaining all of Earley's power in parsing any CFG. ) TYPE_CHECKINGCallableOptionalListAny) defaultdict)Tree)UnexpectedCharacters)Token)Terminal)Parser) TokenNode) LexerConf ParserConfcj\rSrSrSSS\S4SSSSS\S \S \S \S \\\\ /\ 4S \4Sjjr SSjr Sr g)rTF lexer_confr parser_confr term_matcherresolve_ambiguity complete_lexdebug tree_class ordered_setsc [R"XX#UXgU5 URV s/sHn [U 5PM sn UlXPlgs sn fN) BaseParser__init__ignorer r) selfrrrrrrrrts Q/home/mande/repo/quber/.venv/lib/python3.13/site-packages/lark/parsers/xearley.pyr Parser.__init__sK DkIZ!| =,6,=,=>,=qx{,=> (?sA Nc ~^^^^^ ^ ^ ^ ^ ^UU U UUUU U U U4 Sjn[[5m TRm TRRm 0/mSm Sm Sn0nTH9nTR XcTTU5 U"Xc5up7US:XaT S- m Sm OT S- m US- nM; TR XcTTU5 U[ T5S- :XdeU$)Nc > 0nTRU5GH/nT"URTU5nU(dM![URRUR S5UTT5nTUR 5R X0U45 TR(dMUR S5n[S[U55H{nT"URUSU*5nU(dM#[URRUR S5UTT5nTXR 5-R X0U45 M} GM2 TRHnT"UTU5nU(dMTUR 5RUVs/sHo3US4PM sn5 TUR 5RTUVs/sH+o3R(dMURT:XdM'X0S4PM- sn5 M TR5n TR5n TR U 5 TR 05 TUS-GH up;n U bTU lTS-U lUS-U lUR#5n U RU R$US-4n['U TU R(5nX;aX.OUR+UTR,"U65U lU R.R1U RUR2U R$UR.U5 OUn U RTR4;aU R7U 5 GMU R7U 5 GM# TUS- U (doT(dhU (da[9[;USS95n[=TUTTUVs1sHo3RRiM sn[?U5[ASU55US9eX4$s snfs snfs snf)a@The core Earley Scanner. This is a custom implementation of the scanner that uses the Lark lexer to match tokens. The scan list is built by the Earley predictor, based on the previously completed tokens. This ensures that at each phase of the parse we have a custom lexer context, allowing for more complex ambiguities.rrNcBURRR$r)ruleoriginnamekeys r$-Parser._parse..scan..|sH\H\r,c38# UHoRv M g7fr)s).0is r$ .Parser._parse..scan..~sH^V]QRV]s)stateconsidered_rules)!Setexpectr r+groupendappendrrangelenr!extend is_completer2end_line end_columnend_posadvancestartrtype setdefault SymbolNodenode add_familyr) TERMINALSaddlistsortedr set frozenset)r4to_scan node_cacheitemmr#r2jx next_to_scannext_setrFtokennew_itemlabel token_noder8columnsdelayed_matchesmatchr" start_symbolstream terminals text_column text_line transitivess r$scanParser._parse..scan)sJ)$++vq11dkk.. Ay+VA#AEEG,33dq\C(((GGAJ!&q#a&!1A %dkk1Sqb6 :A q$)$++*:*:AGGAJ9Va$b /%%' : A ADQ< Q "2*.[[!VQ'1#AEEG,33QX4ZQXAt_QX4Z[$AEEG,33QXYZQ[5LQ[_o_o_txtztzKuK_dt_Q[5LM! 88:LxxzH NN8 $   r "'6ac&:"U$%.EN'2QE$$%EEM#||~H%ZZQ?E!*5)EJJ2G!HJ9>9LJ$5R\RgRghmoso~o~AFpGSHHMMM,,XZZHNNTXT]T]_ij#H??dnn4 $$X.LL*'';* !$OL#'w<\(]#^ *61ilsNtlsdh{{O_O_lsNt+.wrs< @?#-($.HZHr0