grthtrhthjhtyjytjytkergtrhtrjytjerhrfh4:24 29/09/2026  q5ᙊdZddlZddlmZmZmZmZmZmZm Z m Z m Z m Z m Z mZmZmZddlmZddlmZgdZGddZGd d eZed eGd d eZed eGddeZedeGddZGddZ en #e$reZYnwxYwGddZdS)z+ csv.py - read/write/investigate CSV files N)Error __version__writerreaderregister_dialectunregister_dialect get_dialect list_dialectsfield_size_limit QUOTE_MINIMAL QUOTE_ALLQUOTE_NONNUMERIC QUOTE_NONE__doc__)Dialect)StringIO)r r rrrrrexcel excel_tabr rrrr r Snifferrr DictReader DictWriter unix_dialectcBeZdZdZdZdZdZdZdZdZ dZ dZ dZ dZ dZdS)rzDescribe a CSV dialect. This must be subclassed (see csv.excel). Valid attributes are: delimiter, quotechar, escapechar, doublequote, skipinitialspace, lineterminator, quoting. FNc\|jtkrd|_|dS)NT) __class__r_valid _validateselfs */opt/alt/python311/lib64/python3.11/csv.py__init__zDialect.__init__*s, >W $ $DK c t|dS#t$r!}tt|d}~wwxYwN)_Dialect TypeErrorrstr)r es r!rzDialect._validate/sG TNNNNN   A--  s >9>)__name__ __module__ __qualname__r_namer delimiter quotechar escapechar doublequoteskipinitialspacelineterminatorquotingr"rr#r!rrsl E FIIJKNG      r#rc*eZdZdZdZdZdZdZdZe Z dS)rz;Describe the usual properties of Excel-generated CSV files.,"TF N) r*r+r,rr.r/r1r2r3r r4r5r#r!rr6s3EEIIKNGGGr#rceZdZdZdZdS)rzEDescribe the usual properties of Excel-generated TAB-delimited files. N)r*r+r,rr.r5r#r!rr@sOOIIIr#rz excel-tabc*eZdZdZdZdZdZdZdZe Z dS)rz:Describe the usual properties of Unix-generated CSV files.r7r8TF N) r*r+r,rr.r/r1r2r3r r4r5r#r!rrEs3DDIIKNGGGr#runixc\eZdZ ddZdZedZejdZdZdS) rNrcx||_||_||_t||g|Ri||_||_d|_dSNr) _fieldnamesrestkeyrestvalrdialectline_num)r f fieldnamesrCrDrEargskwdss r!r"zDictReader.__init__QsK%  Q7$777$77   r#c|Sr%r5rs r!__iter__zDictReader.__iter__Zs r#c|j+ t|j|_n#t$rYnwxYw|jj|_|jSr%)rBnextr StopIterationrFrs r!rHzDictReader.fieldnames]sZ   # #' #4#4        , s # 00c||_dSr%)rB)r values r!rHzDictReader.fieldnamesgs r#c|jdkr|jt|j}|jj|_|gkrt|j}|gkt t |j|}t |j}t |}||kr||d||j<n"||kr|j|dD] }|j||< |SrA) rFrHrNrdictziplenrCrD)r rowdlflrkeys r!__next__zDictReader.__next__ks =A   OO4; , Riit{##CRii T_c** + +  ! ! XX 77!"##hAdlOO "WWrss+ & &#r#)NNNr) r*r+r,r"rLpropertyrHsetterr[r5r#r!rrPsAE   X !!!r#rc2eZdZ d dZdZdZdZdZd S) rrraiserc||_||_|dvrtd|z||_t ||g|Ri||_dS)N)r_ignorez-extrasaction (%s) must be 'raise' or 'ignore')rHrDlower ValueError extrasactionr)r rGrHrDrdrErIrJs r!r"zDictWriter.__init__sr$     ': : :L+,-- -(Q7$777$77 r#cztt|j|j}||Sr%)rSrTrHwriterow)r headers r! writeheaderzDictWriter.writeheaders/c$/4?;;<<}}V$$$r#cjdkrMjz }|r/tddd|DzfdjDS)Nr_z(dict contains fields not in fieldnames: z, c,g|]}t|Sr5)repr).0xs r! z,DictWriter._dict_to_list..s-L-L-L!d1gg-L-L-Lr#c3NK|]}|jV dSr%)getrD)rlrZrowdictr s r! z+DictWriter._dict_to_list..s3JJ3 C..JJJJJJr#)rdkeysrHrcjoin)r rq wrong_fieldss`` r! _dict_to_listzDictWriter._dict_to_lists   ' '"<<>>DO;L O !K#'99-L-L|-L-L-L#M#M"NOOOJJJJJ$/JJJJr#c\|j||Sr%)rrfrv)r rqs r!rfzDictWriter.writerows&{##D$6$6w$?$?@@@r#c\|jt|j|Sr%)r writerowsmaprv)r rowdictss r!ryzDictWriter.writerowss%{$$S);X%F%FGGGr#N)rr_r)r*r+r,r"rhrvrfryr5r#r!rrsu?F 8888%%%KKKAAAHHHHHr#rc2eZdZdZdZddZdZdZdZdS) rze "Sniffs" the format of a CSV file (i.e. delimiter, quotechar) Returns a Dialect object. cgd|_dS)N)r7r;; :) preferredrs r!r"zSniffer.__init__s333r#NcJ|dddd}|||\}}}}|s|||\}}|stdGddt}||_||_|pd|_||_|S)zI Returns a dialect (or None) corresponding to the sample r9r= zCould not determine delimiterceZdZdZdZeZdS)Sniffer.sniff..dialectsniffedr9N)r*r+r,r-r3r r4r5r#r!rErsE#N#GGGr#rEr8) replace_guess_quote_and_delimiter_guess_delimiterrrr1r.r/r2)r sample delimitersr/r1r.r2rEs r!sniffz Sniffer.sniffs --55dDAA226:FF < ; +; L*.*?*?@J+L+L 'I' 9788 8 $ $ $ $ $g $ $ $ *%%,#3 r#cd}g}dD]J}tj||ztjtjz}||}|rnK|sdSi}i}d} |j} |D]} | ddz } | | } | r|| ddz|| < | ddz } | | } n#t$rYTwxYw| r"|| |vr|| ddz|| < | d dz } n#t$rYwxYw| | r| dz } t||j }|r+t||j }||| k}|d krd }nd }d}d }|rstjdtj |||dkrdnd dztj}|dztfd| |D}||||fS)a Looks for text enclosed between two identical quotes (the probable quotechar) which are preceded and followed by the same character (the probable delimiter). For example: ,'some text', The quote with the most wins, same with the delimiter. If there is no quotechar the delimiter can't be determined this way. z#(?:(?P=quote){2}|(?!(?P=quote)).)*+)zH(?P[^\w\n"\'])(?P ?)(?P["\'])%s(?P=quote)(?P=delim)zF(?:^|\n)(?P["\'])%s(?P=quote)(?P[^\w\n"\'])(?P ?)zF(?P[^\w\n"\'])(?P ?)(?P["\'])%s(?P=quote)(?:$|\n)z,(?:^|\n)(?P["\'])%s(?P=quote)(?:$|\n))rFNrrquotedelimNspacerZr=rFzg(?:(?<=%(delim)s)|^)%(space)s%(quote)s((?:%(quote)s%(quote)s|[^%(quote)s]++)*+)%(quote)s(?:%(delim)s|$)rz *+)rrrc3,K|]}|dvVdSrNr5)rlm dquotechars r!rrz5Sniffer._guess_quote_and_delimiter..sHAA"#)AaD0AAAAAAr#) recompileDOTALL MULTILINEfindall groupindexrpKeyErrormaxescapeanyfinditer)r datarbodymatchesrestrregexpquotesdelimsspacesrrnrZr/rr2r1 dq_regexprs @r!rz"Sniffer._guess_quote_and_delimiters6G  EZ bi",.FGGFnnT**G   (''&   A7#a'AA$C 5$jja0014s  w'!+d     5 *cZ.?.?$jja0014s  w'!+    t ! FJ///  !FJ///E%e}6 }}E    A 0!# % 0 09).#2??? L""I#QJAAAA'0'9'9$'?'?AAAAAK;/?@@s$B.. B;:B;# C// C<;C<c.ttd|d}dtdD}t dt |}d}i}i}i}d|} } | t |kr|dz }|| | D]S} |D]N} || i} | | }| |ddz| |<| || <OT|D]} t||  }t |dkr|dddkrOt |dkrjt|d || <| || || d|| dtd |Dz f|| <|d|| <| }tt ||zt |}d }d }t |dkr^||krX|D]7\}}|ddkr&|ddkr|d|z |kr |||vr|||<8|d z}t |dkr||kXt |dkrft|d}|d||dd|zk}||fS| } | |z } | t |k|sdSt |dkra|jD]Y}||vrA|d||dd|zk}||fcSZd| D}||dd}|d||dd|zk}||fS)a The delimiter /should/ occur the same number of times on each row. However, due to malformed data, it may not. We don't want an all or nothing approach, so we allow for small variations in this number. 1) build a table of the frequency of each character on every line. 2) build a table of frequencies of this frequency (meta-frequency?), e.g. 'x occurred 5 times in 10 rows, 6 times in 1000 rows, 7 times in 2 rows' 3) use the mode of the meta-frequency to determine the /expected/ frequency for that character 4) find out how often the character actually meets that goal 5) the character that best meets its goal is the delimiter For performance reasons, the data is evaluated in chunks, so it can try and evaluate the smallest portion of the data possible, evaluating additional chunks as necessary. 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