+ NV-jf^RIHt^RIHt^RIHt^RIt^RIHt^RIt^RI H t H t H t H t Ht^RIt^RIt^RIHtHt^RIHuHt^RIHt^R IHt^R IHtHt^R I H!t!^R I"H#t#H$t$H%t%H&t&H't'H(t(H)t)H*t*^R I+H,t,^RI-H.t.H/t/H0t0^RI1H2t2^RI3H4t4H5t5H6t6H7t7H8t8^RI9H:t:H;t;HH?t?^RI@HAtB^RICHDtD] 'd^RIEHFtFHGtGHHtHHItI^RIJHKtKHLtLHMtMHNtNHOtOHPtP!RR4tQRPRRlltR/RRbRRbRR bR!]PbR"RbR#RbR$RbR%R&bR'RbR(RbR)RbR*^bR+RbR,RbR-RbR.RbR/Rb/R0RbR1RbR2RbR3RbR4RbR5R6bR7RbR8RbR9RbR:RbR;RbRRbR?R@bRA]QPPbRB]PbCtWRCRDltXRERFltYRGRHltZRIt[]RJRKl4t\]RLRMl4t\RNROlt\R#)Q) annotations) defaultdictcopyN)Enum) TYPE_CHECKINGAnycastfinaloverload)libparsers) STR_NA_VALUES)import_optional_dependency) ParserError ParserWarning)find_stack_level) is_bool_dtype is_dict_likeis_float_dtype is_integeris_integer_dtype is_list_likeis_object_dtypeis_string_dtype)isna) DataFrame DatetimeIndex StringDtype) algorithms)ArrowExtensionArrayBaseMaskedArray BooleanArray FloatingArray IntegerArray)Index MultiIndex default_indexensure_index_from_sequences)Series) datetimes)is_potential_multi_index)CallableIterableMappingSequence) ArrayLikeDtypeArgHashable HashableTScalar SequenceTc]tRt^Vt$!RR]4tR]R&R]R&R]R&R]R&R]R&R ]R &R R ltR Rlt] RRl4t ] R.RRll4t ] R/RRll4t ] R/RRll4t ] R4t] RRl4t] RRl4t] R0RRll4t]RR l4t]R!R"l4t] R#R$l4t] R%R&l4t] R'R(l4t] R)R*l4t] R/R+R,ll4tR-tR#)1 ParserBasec"]tRt^Wt^t^t^tRtR#)ParserBase.BadLineHandleMethodN)__name__ __module__ __qualname____firstlineno__ERRORWARNSKIP__static_attributes__r;n/Volumes/fast/ai/experiments/ui-tars-smoke/.venv/lib/python3.14/site-packages/pandas/io/parsers/base_parser.pyBadLineHandleMethodr:WsrDrFbool_implicit_index _first_chunkkeep_default_nadayfirst cache_datesz str | None usecols_dtypecV^8dQhRR/#returnNoner;)formats"rE __annotate__ParserBase.__annotate__csFUFUFUrDc RVnVPR4VnRVnVPRR4Vn\ 4VnRVnRVnVPRR4pVe\P!V4'd \V4pM!\V\4'g \R4hW nVPR\P"4VnVPRR4VnVPRR4VnVPR 4VnVPR 4VnVPR R4VnVPR R 4Vn\3VPRR44VnVPR4VnVPR4VnVPR4VnVPR4VnVPRR 4VnVPR4Vn \CVP@RR7'dVPR4'd \ER4hVPR4'd \ER4hVPe\GVP4'dVP.VnMk\CVPRR7'd*\I\K\FVP44'g \ER4h\VP4VnR Vn&\OVR,4wVn(Vn)VPRVPTPV4Vn,R#)FnamesN index_col parse_dateszDOnly booleans and lists are accepted for the 'parse_dates' parameter date_parser date_formatrK na_values na_fvalues na_filterrJTdtype converters dtype_backend true_values false_valuesrLheader) allow_setsusecolsz;cannot specify usecols when specifying a multi-index headerz9cannot specify names when specifying a multi-index headerz]index_col must only contain integers of column positions when specifying a multi-index header on_bad_lines)-rHgetrW orig_namesrXset unnamed_cols index_names col_namespopr is_boolrG isinstancelist TypeErrorrY no_defaultrZr[rKr\r]r^rJrr_r`rarbrcrLrdr ValueErrorrallmaprI_validate_usecols_argrfrMrFr@rg)selfkwdsrYs&& rE__init__ParserBase.__init__cs$XXg& 59+t4!$6:48hh}e4  #++k":":{+KK..V )488M3>>B88M48U3 +.((<0+u5#xx(94@$((7D12 ((<0!XXo688M2 HH^488M48hhx(   6 6xx "" Qxx   O ~~)dnn--&*nn%5DN EBBC DNN;<<$? &*$..%9DN +@i+Q( d(!HH^T5M5M5S5STrDcV^8dQhRR/#rOr;)rSs"rErTrUs  t rDc R#Nr;)rxs&rEcloseParserBase.closes rDc V^8dQhRRRR/#)rPiintrQrGr;)rSs"rErTrUs  S T rDc H\VP\4'd VP#VPeVPV,pMRpVPfTMVPV,pW0P9;'gVRJ;'dW P9#r~)rprYrGrlrX)rxrnamejs&& rE_should_parse_datesParserBase._should_parse_datess d&& - -## #+''*^^+1BA)))D ==T-=-=%= rDc$V^8dQhRRRRRR/#)rPrlSequence[Hashable] | None passed_namesrGrQzUtuple[Sequence[Hashable], Sequence[Hashable] | None, Sequence[Hashable] | None, bool]r;)rSs"rErTrUs/D;D;/D; D;   D;rDc a a a \V4^8dV^,VRV3#VPpVf.p\V\\\ P 34'gV.p\V4o VPR 4pVPW P4wpp\V^,4o \;QJd&V 3RlVR,4F 'dK RM RM!V 3RlVR,44'g \R4hV V 3Rlo \\V 3RlV4R R/4pVP4p\V4FpVPW4K V'dQVU u.uFCp W^,,e.W^,,VP 9dW^,,MRNKE p p MR.\V4,p RpWrW3#uup i) a* Extract and return the names, index_names, col_names if the column names are a MultiIndex. Parameters ---------- header: list of lists The header rows index_names: list, optional The names of the future index passed_names: bool, default False A flag specifying if names where passed Nc3@<"TFp\V4S8HxK R#5ir~)len).0 header_iter field_counts& rE .sQj{3{#{2js:NNFTz1Header rows must have an equal number of columns.c<a\;QJd!.VV3Rl\S44FNK 5#!VV3Rl\S444#)c3F<"TFqS9gK SV,xK R#5ir~r;)rrrsics& rErMParserBase._extract_multi_indexer_columns..extract..sJ'9!c\1'9s!!)tuplerange)rrrsfrEextract:ParserBase._extract_multi_indexer_columns..extracts/5Ju['9J5 J5Ju['9JJ JrDc34<"TF pS!V4xK R#5ir~r;)rrrs& rErrs8AWQZZsstrict)rrXrprqrnpndarrayrjrn_clean_index_namesrurziprsortedinsertrk)rxrdrlric_columnsrW single_icrrmrrrs&&&& @@@rE_extract_multi_indexer_columns)ParserBase._extract_multi_indexer_columnss. v;?!9k4= = ^^ :B"tUBJJ788B"gjjn  33KP Q&)n sQfRjQsssQfRjQQQQR R Ks88FFG I LL .$    A!uX)qAxt?P?P/PQ% IV,I 9::s+A GNc$V^8dQhRRRRRR/#)rPrr6rmrrQzSequenceT | MultiIndexr;)rSs"rErTrUs(   -  rDc n\V4'd$\RV4p\P!W2R7#V#)zSequence[tuple[Hashable, ...]])rW)r,r r' from_tuples)rxrrm columns_mis&&& rE_maybe_make_multi_index_columns*ParserBase._maybe_make_multi_index_columnss2 $G , ,>HJ))*F FrDc V^8dQhRRRR/#)rP indexnamerowzlist[Scalar] | NonerQz4tuple[Index | None, Sequence[Hashable] | MultiIndex]r;)rSs"rErTrUs.A =rDc \VP\4'Ed\VP4'd.p.pVPFPp\V\4'd\ RV R24hVP V4VP W,4KR \VRR7F9pVPV4VP'dK(VPV4K; VPV4pV'd0\V4\V4, p VPVRV 4pMRpVPW P4pW3#)zIndex z invalidT)reverseN)rprXrqrstrrtappendrrnrH _agg_index set_namesrrm) rxalldatarr to_removeindexesidxrindexcoffsets &&&& rE _make_indexParserBase._make_indexs dnnd + +DNN0C0CIG~~c3''$vcU(%;<<  %w|, &It4 A+++KKN5OOG,El+c'l: Xg(>?E66wO~rDc \V\4'gV#/pVPfQhVP4FBwr4\V\4'd$W0P9dVPV,pWBV&KD \V\ 4'd[\ VP4\ VP44, pTPVUu/uF q3W,bK up4V#uupi)zconverts col numbers to names) rpdictriitemsrrrjkeysupdate)rxmappingcleancolvremaining_colss&& rE_clean_mappingParserBase._clean_mapping1s'4((N***mmoFC#s##??(Booc*#J& g{ + + 1C 4EEN LL~F~w|+~F G GsC3cV^8dQhRR/#)rPrQr&r;)rSs"rErTrUDs@2@25@2rDc  .pVPVP4pVPVP4pVPeVPpRpM\P !R.4pRp\ \WVR74EF0wpwrVPV4'dP\TVPeVPV,MRVPVPVPR7pVP'dVPp VPp M\!4p \!4p \#VP\$4'diVPfQhVPV,p V e/\'WPVPVP(4wrM\!4\!4rRp RpVPet\#V\$4'd$VP+VPV,R4p \#V\$4'd%VP+VPV,4RJpT ;'d\-V 4;'gT'*pVP/WV ,V RJV4wppV e\1WV RR7pM\3V.V .4pVP5V4EK3 \7V4^8Xd V^,#\8P:!V4#)NTF)rrrKrLr[)rr_r)rr`r_rl itertoolscycle enumeraterrdate_converterrKrLr[r^r\r]rjrpr get_na_valuesrJrhr _infer_typesr&r)rrr' from_arrays)rxrarraysr` clean_dtypesrW zip_strictrarrr col_na_valuescol_na_fvaluescol_name cast_typeindex_converter try_num_boolrrs&& rErParserBase._agg_indexCsv((9 **4::6    '"..EJOOTF+EJ'E(LMNA{''**$/3/?/?/K((+QU!]] $ 0 0 $ 0 0 ~~~ $ !% # !$$..$//''333++A.'4A ..$//4CWCW51M>58E35>I#O+lD11 , 0 01A1A!1Dd KIj$//&0nnT5E5Ea5H&IQU&UO99y9MMoL&&^3Y$5F FC$C)%H13%$@ MM# aNd v;! !9 ))&1 1rDc$V^8dQhRRRRRR/#)rP col_indicesz list[int]rWSequence[Hashable]rQset[int]r;)rSs"rErTrUs$7!7!$7!-?7! 7!rDc aaa\4pVPR8Xd\VP4oM1\ VP4'gVPR9dSoMRoRVVV3Rllp\ VP \4'dC\VP S4VP FpVPV!V44K V#VP 'd|\ VP\4'd-VPFpVPV!V44K V#VPe"VPV!VP44V#)a Set the columns that should not undergo dtype conversions. Currently, any column that is involved with date parsing will not undergo such conversions. If usecols is specified, the positions of the columns not to cast is relative to the usecols not to all columns. Parameters ---------- col_indices: The indices specifying order and positions of the columns names: The column names which order is corresponding with the order of col_indices Returns ------- A set of integers containing the positions of the columns not to convert. integerNcV^8dQhRR/#)rPrQrr;)rSs"rErT=ParserBase._set_noconvert_dtype_columns..__annotate__s  s rDc<Se\V4'd SV,p\V4'gSSPV4,pV#r~)rr)xrrWrfs&rE_set5ParserBase._set_noconvert_dtype_columns.._sets:"z!}}AJa== A/HrD)emptyN) rjrMrrfcallablerprYrqvalidate_parse_dates_presenceaddrX)rxrrWnoconvert_columnsrvalkrfs&ff @rE_set_noconvert_dtype_columns'ParserBase._set_noconvert_dtype_columnss, E    *T\\*G dll # #t'9'9'P"GG   d&& - - )$*:*:E B''!%%d3i0(!    $..$//A%))$q'2( ! +!%%d4>>&:;  rDc V^8dQhRRRR/#)rPrrGrQztuple[ArrayLike, int]r;)rSs"rErTrUs r r CGr r rDc   ^p\VPP\P\P 34'd\P !VUu.uFp\V\4'dKVNK up4p\P!W4pVPRRR7P4pV^8dV\V4'd VP\P4p\P!W\P 4W3#VP"pT;'dV\$P&Jp V'EdH\)VP4'Ed,\$P*!VVRV R7wrV 'dV f1\P,!V P.\P R7p V P14'd<\3\P4!V P.\P6R7V 4p MV\V 4'd \3W4p M9\9V 4'd \;W4p M\=V 4'd \?W4p V P4pMQ\AV 4P4pM7Tp VP\PJ8Xd\FPH!W4pV P\PJ8XEdTV'EdK\MV 4^8Xg\V ^,\N4'Eg\PPR!\PT!V4VPVVPXV R7wrV P\P 8XdIV 'dAV f1\P,!V P.\P R7p \;W4p MqV P\PJ8XdSV 'dK\$PZ!V RR 7'g-\]4p V P_4pVPaWR7p VR 8XEd \cR 4p\V \Pd4'd \gVP V RR 74p W3#\V \h4'dV PjP14'd/\gVP R.\MV 4,44p W3#\gVP V PlV PjR 74p W3#\gVP V Po4RR 74p W3#uupi \B\D3d\FPH!Y4pTp ELi;i) aC Infer types of values, possibly casting Parameters ---------- values : ndarray na_values : set no_dtype_specified: Specifies if we want to cast explicitly try_num_bool : bool, default try try to cast values to numeric (first preference) or boolean Returns ------- converted : ndarray or ExtensionArray na_count : int uint8Fr)convert_to_masked_nullableNr_)rbrcrTskipnapyarrow) from_pandas)mask)8 issubclassr_typernumberbool_arrayrprr isinastypesumrfloat64putmasknanrar rsrmaybe_convert_numericzerosshaperur%onesint64rr#rr$rrtrrrsanitize_objectsobject_rrlibopsmaybe_convert_boolasarrayrbrcis_datetime_arrayrconstruct_array_type_from_sequencerrr!r"_mask_datato_numpy)rxvaluesr\no_dtype_specifiedrna_countrrranon_default_dtype_backendresult result_mask bool_maskr_clspas&&&&& rErParserBase._infer_typess( fll''"))RXX)> ? ?!W#*SRUBV##!WXI??65D{{7{7;;=H!|#F++#]]2::6F 60# #**  F F=#F " >400W5N4++T22wBRBR7R#  ,, ,, F#M!($ rDc$V^8dQhRRRRRR/#)rPrrr)zSequence[ArrayLike]rQrRr;)rSs"rErTrU`s(#"  rDc VP'g\V4\V48wdV'd\VR,4;'d VR,R8HpV\VR,4,p\V4\V4^, 8Xd\P !V4'dR#\ P!R\\4R7R#R#R#R#)a-Checks if length of data is equal to length of column names. One set of trailing commas is allowed. self.index_col not False results in a ParserError previously when lengths do not match. Parameters ---------- columns: list of column names data: list of array-likes containing the data column-wise. NzkLength of header or names does not match length of data. This leads to a loss of data with index_col=False.) stacklevelr) rXrrrrruwarningswarnrr)rxrr) empty_strempty_str_or_nas&&& rE_check_data_lengthParserBase._check_data_length_s ~~~#g,#d)";'R1DDd2h"nI($tBx.8O7|s4y1},1H1H MM:+-  AH";~rDc$V^8dQhRRRRRR/#)rPrfr6rWr0rQr;)rSs"rErTrU~s!yirDc ~VUu.uF q3V9gK VNK pp\V4^8d\RV 24hV#uupi)a Validates that all usecols are present in a given list of names. If not, raise a ValueError that shows what usecols are missing. Parameters ---------- usecols : iterable of usecols The columns to validate are present in names. names : iterable of names The column names to check against. Returns ------- usecols : iterable of usecols The `usecols` parameter if the validation succeeds. Raises ------ ValueError : Columns were missing. Error message will list them. z>Usecols do not match columns, columns expected but not found: )rrt)rxrfrWcmissings&&& rE_validate_usecols_names"ParserBase._validate_usecols_names}sP.&8g%11g8 w >w-.0 O i(DA!S!!""1%(1GAy'(! t, 2 zt$""4()!-GA$$$1B1B)B!% .Y..rDc$V^8dQhRRRRRR/#)rPrzSequence[HashableT]r_zDtypeArg | NonerQz6tuple[Index, list[HashableT], dict[HashableT, Series]]r;)rSs"rErTrUs$4(4(*4(3B4( ?4(rDc  a\V4pVPpVPp\S4'g\ V3Rl4pMY\ \ S4o\ RSP4UUu/uF!wrg\V4'd W,MTVbK# upp4pVe VRJgVf \^4pMVU u.uFp \.WV ,R7NK p p \V 4^8Xd V ^,pM\P!V 4pVP4\V4FwrVP!W, 4K VU u/uFq\#.W],R7bK pp WV3#uuppiuup iuup i)c<S#r~r;rsrE,ParserBase._get_empty_meta..sUrDcR#r~r;r;rDrErLrMsrDF)rr_r)rqrXrlrrr rrrr(r&rr'rsortrrnr*)rxrr_rXrl dtype_dictrrrrr)rnrcol_dicts&&f rE_get_empty_metaParserBase._get_empty_metasaw-NN && E""$]3Ju%E$CH;;=Q=41z!}}!Q6=QJ  e!3 8K!!$EJUITbtd+;< 4yA~Q"..t4 NN !), AE"-NU MTfRz';< r?rrF__annotations__rzrr rrrrrrrrr r,r;rArrSrCr;rDrEr8r8Vsxd NFUP      D; D;L      @  " @2 @2D 7! 7!r r  r h ++   6  :  > #/ #/J 4( 4(rDr8FTc(V^8dQhRRRRRRRR/#)rPrr3rKrGrLr[z dict[Hashable, str] | str | Noner;)rSs"rErTrTs2   2 rDcVPPR9dV#\V\4'dVP V4MTp\ P !\P!V44p\P!VVRVVR7p\T\4'd$TP4pRTPnT#TP"# \\3dTu#i;i)MmF)rSutcrKcacheT)r_kindrprrhr ensure_string_arrayrrtools to_datetimertrrrrflags writeable_values) date_colrrKrLr[date_fmtstr_objsr"rs &&&&& rErrs~~d"'1+t'D'D{s#+H&&rzz(';>  "s2CC('C( delimiter escapechar quotechar"quoting doublequoteskipinitialspacelineterminatorrdinferrXrWskiprows skipfooternrowsr\rJrbrcr`r_rL thousandscommentdecimal.rYrKr[rf chunksizeencoding compressionskip_blank_linesencoding_errorsrrgracV^8dQhRR/#)rPrJrGr;)rSs"rErTrTDs % %t %rDc\V\4'dCW9dW,W ,3#V'd\\43#\4\43#W3#)aX Get the NaN values for a given column. Parameters ---------- col : str The name of the column. na_values : array-like, dict The object listing the NaN values as strings. na_fvalues : array-like, dict The object listing the NaN values as floats. keep_default_na : bool If `na_values` is a dict, and the column is not mapped in the dictionary, whether to return the default NaN values or the empty set. Returns ------- nan_tuple : A length-two tuple composed of 1) na_values : the string NaN values for that column. 2) na_fvalues : the float NaN values for that column. )rprrrj)rr\r]rJs&&&&rErrDsM.)T""  >:?2 2$ce++5#%< $$rDcV^8dQhRR/#)rPrQrGr;)rSs"rErTrTgs000rDc"VRJ;'dVRJ#)NFr;)rs&rErErEgs d? / /s%//rDc$V^8dQhRRRRRR/#)rPrYz bool | listrrrQrjr;)rSs"rErTrTks$+++'9++rDc\V\4'g \4#\4p\4pVFup\V\4'd-WA9dVP V4K2VP V4KEWA9dVP V4K^VP W,4Kw V'd*RP \ V44p\RV R24hV#)az Check if parse_dates are in columns. If user has provided names for parse_dates, check if those columns are available. Parameters ---------- columns : list List of names of the dataframe. Returns ------- The names of the columns which will get parsed later if a list is given as specification. Raises ------ ValueError If column to parse_date is not in dataframe. z, z+Missing column provided to 'parse_dates': '')rprqrjrrjoinrrt)rYrr@ unique_colsr missing_colss&& rErrks2 k4 ( (u eG%K c3  ! C $ ^ OOC OOGL )yy1 F|nTUVWW rDcRpVej\V4'dVR3#\V4'g \V4h\P!VRR7pVR9d \V4h\ V4pW3#VR3#)a Validate the 'usecols' parameter. Checks whether or not the 'usecols' parameter contains all integers (column selection by index), strings (column by name) or is a callable. Raises a ValueError if that is not the case. Parameters ---------- usecols : list-like, callable, or None List of columns to use when parsing or a callable that can be used to filter a list of table columns. Returns ------- usecols_tuple : tuple A tuple of (verified_usecols, usecols_dtype). 'verified_usecols' is either a set if an array-like is passed in or 'usecols' if a callable or None is passed in. 'usecols_dtype` is the inferred dtype of 'usecols' if an array-like is passed in or None if a callable or None is passed in. z['usecols' must either be list-like of all strings, all unicode, all integers or a callable.NFr)rrstring)rrrtr infer_dtyperj)rfmsgrMs& rErwrws4 & G  D= G$$S/ !>  > >S/ !g,%% D=rDc$V^8dQhRRRRRR/#)rPrfzCallable[[Hashable], object]rWIterable[Hashable]rQrr;)rSs"rErTrTs& ) rDcR#r~r;rfrWs&&rEevaluate_callable_usecolsrsrDc$V^8dQhRRRRRR/#)rPrfr6rWrrQr;)rSs"rErTrTs$ 1rDcR#r~r;rs&&rErrsrDc$V^8dQhRRRRRR/#)rPrfz(Callable[[Hashable], object] | SequenceTrWrrQzSequenceT | set[int]r;)rSs"rErTrTs&   5    rDc\V4'd0\V4UUu0uFwr#V!V4'gKVkK upp#V#uuppi)z Check whether or not the 'usecols' parameter is a callable. If so, enumerates the 'names' parameter and returns a set of indices for each entry in 'names' that evaluates to True. If not a callable, returns 'usecols'. )rr)rfrWrrs&& rErrs@!*5!1C!1gaWT]!1CC NDs AA)FTN)] __future__r collectionsrrcsvenumrrtypingrr r r r r7numpyr pandas._libsr rpandas._libs.ops_libsopsrpandas._libs.parsersrpandas.compat._optionalr pandas.errorsrrpandas.util._exceptionsrpandas.core.dtypes.commonrrrrrrrrpandas.core.dtypes.missingrpandasrrr pandas.corer pandas.core.arraysr!r"r#r$r%pandas.core.indexes.apir&r'r(r)pandas.core.seriesr*pandas.core.toolsr+r]pandas.io.commonr,collections.abcr-r.r/r0pandas._typingr1r2r3r4r5r6r8r QUOTE_MINIMALrFr@rsparser_defaultsrrErrwrr;rDrErs"# "!.>5   , # &05b (b (JB%%$%%s  % 4 %  %d% g%% T%%!% T%%t% 4!%"D#%$$%%& T'%(4)%*+%,t-%.s/%253%45%647%8t9%<=%>?%@4A%BC%DxE%FJ2288G%HS^^I%P %F0+\/d      rD