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✨ File Manager Magic · Hostinger Optimized ✨
{|jBHdZddlZddlZddlmZmZmZmZmZm Z m Z m Z m Z m Z mZmZmZmZmZmZddlmZddlmZgdZGddZGd d eZed eGd d eZed eGddeZedeGddZGddZGddZy)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 QUOTE_STRINGS QUOTE_NOTNULL__doc__)Dialect)StringIO)r r rrrrrrrexcel excel_tabr rrrr r Snifferrr DictReader DictWriter unix_dialectc@eZdZdZdZdZdZdZdZdZ dZ dZ dZ dZ dZy)rzDescribe a CSV dialect. This must be subclassed (see csv.excel). Valid attributes are: delimiter, quotechar, escapechar, doublequote, skipinitialspace, lineterminator, quoting. 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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))rFNrrquotedelimspacer^r?rFzg(?:(?<=%(delim)s)|^)%(space)s%(quote)s((?:%(quote)s%(quote)s|[^%(quote)s]++)*+)%(quote)s(?:%(delim)s|$)rz *+)rrrc3,K|] }|dv ywrNr7)rtm dquotechars r#rvz5Sniffer._guess_quote_and_delimiter..#s#A'?!)AaD0'?s) recompileDOTALL MULTILINEfindall groupindexrsKeyErrormaxescapeanyfinditer)r"datarbodymatchesrestrregexpquotesdelimsspacesrrnr^r1rr4r3 dq_regexprs @r#rz"Sniffer._guess_quote_and_delimiters#6GEZZ bii",,.FGFnnT*GG'&& A7#a'AA$C$jja014s  w'!+d *cZ.?$jja014s  w'!+t! #&FJJ/ FJJ/E%e}6 }E    0!# % 09).#2?? LL"I#QJA'0'9'9$'?AAK;/?@@Q     s$ F F* F'&F'* F76F7cttd|jd}tdDcgc] }t |}}t dt |}d}i}i}i} d|} } | t |kr |dz }|| | D]I} |D]B} |j| i}| j| }|j|ddz||<||| <DK|jD]} t|| j}t |dk(r |dddk(r9t |dkDrLt|d|| <|j|| || d|| dtd |Dz f|| <|d|| <|j}tt ||zt |}d }d }t | dk(rR||k\rM|D]/\}}|ddkDs|ddkDs|d|z |k\s$|||vs+|| |<1|d z}t | dk(r||k\rMt | dk(rLt| jd}|dj||djd |zk(}||fS| } | |z } | t |kr | syt | dkDrU|jD]F}|| jvs|dj||djd |zk(}||fcS| jDcgc] \}}||f }}}|j!|dd}|dj||djd |zk(}||fScc}wcc}}w)a The delimiter /should/ occur the same number of times on each row. However, due to malformed data, it may not. We don't want an all or nothing approach, so we allow for small variations in this number. 1) build a table of the frequency of each character on every line. 2) build a table of frequencies of this frequency (meta-frequency?), e.g. 'x occurred 5 times in 10 rows, 6 times in 1000 rows, 7 times in 2 rows' 3) use the mode of the meta-frequency to determine the /expected/ frequency for that character 4) find out how often the character actually meets that goal 5) the character that best meets its goal is the delimiter For performance reasons, the data is evaluated in chunks, so it can try and evaluate the smallest portion of the data possible, evaluating additional chunks as necessary. Nr? rrc |dS)Nrr7)r{s r#z*Sniffer._guess_delimiter..Xs1Q4r%rc3&K|] }|d ywrr7)rtitems r#rvz+Sniffer._guess_delimiter..]s(CUTaUsg?g?g{Gz?z%c )rr)rEfiltersplitrangechrminrYrscountrwitemsrremovesumfloatrsort)r"rrcascii chunkLength iteration charFrequencymodesrstartendlinechar metaFrequencyfreqrmodeListtotal consistency thresholdkvrr4r[s r#rzSniffer._guess_delimiter)s&F4D!123!&s,AQ,"c$i(    sc$i NIU3!D$1$5$5dB$?M::d+D*7*;*;D!*Dq*HM$'*7M$' "(&**,]406689u:?uQx{a'7u:>"%e"@E$KLLt-#(;q>5;q>%((CU(C%C4D#EE$K#((E$K- {{}H#kI5s4yABEKIf+"{i'?$DAqtaxAaD1HqT%ZK7'/1 ?()F1I % t# f+"{i'?6{aV[[]+A.$(GMM%$8$(GMM%%-$@%A /00E ; Ccc$if v;?^^ %(,Q a(8(,Q eai(@)A$/00 $%+LLN3N5Aa!AN3 b !  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