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csv.pyc
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� �mec@s�dZddlZddlmZddlmZmZmZmZm Z m Z mZmZm Z mZmZmZmZmZddlmZyddlmZWn!ek r�ddlmZnXddd d ddd dddddddddddddgZdd"d��YZdefd��YZe de�defd��YZe de�dd#d��YZdd$d ��YZyeWnek r�eZnXdd%d!��YZdS(&s+ csv.py - read/write/investigate CSV files i����N(treduce(tErrort__version__twritertreadertregister_dialecttunregister_dialecttget_dialectt list_dialectstfield_size_limitt QUOTE_MINIMALt QUOTE_ALLtQUOTE_NONNUMERICt QUOTE_NONEt__doc__(tDialect(tStringIOR RRR RRRtexcelt excel_tabR RRRRRtSnifferRRt DictReadert DictWritercBsVeZdZdZeZdZdZdZ dZ dZdZdZ d�Zd�ZRS(s�Describe an Excel dialect. This must be subclassed (see csv.excel). Valid attributes are: delimiter, quotechar, escapechar, doublequote, skipinitialspace, lineterminator, quoting. tcCs)|jtkrt|_n|j�dS(N(t __class__RtTruet_validt _validate(tself((s/usr/lib64/python2.7/csv.pyt__init__-scCs:yt|�Wn%tk r5}tt|���nXdS(N(t_Dialectt TypeErrorRtstr(Rte((s/usr/lib64/python2.7/csv.pyR2sN(t__name__t __module__Rt_nametFalseRtNonet delimitert quotechart escapechartdoublequotetskipinitialspacetlineterminatortquotingRR(((s/usr/lib64/python2.7/csv.pyRs cBs2eZdZdZdZeZeZdZ e ZRS(s;Describe the usual properties of Excel-generated CSV files.t,t"s (R!R"RR&R'RR)R$R*R+R R,(((s/usr/lib64/python2.7/csv.pyR9scBseZdZdZRS(sEDescribe the usual properties of Excel-generated TAB-delimited files.s (R!R"RR&(((s/usr/lib64/python2.7/csv.pyRCss excel-tabcBsPeZddddd�Zd�Zed��Zejd��Zd�ZRS(RcOsI||_||_||_t||||�|_||_d|_dS(Ni(t_fieldnamestrestkeytrestvalRtdialecttline_num(Rtft fieldnamesR0R1R2targstkwds((s/usr/lib64/python2.7/csv.pyRJs cCs|S(N((R((s/usr/lib64/python2.7/csv.pyt__iter__SscCsR|jdkr<y|jj�|_Wq<tk r8q<Xn|jj|_|jS(N(R/R%Rtnextt StopIterationR3(R((s/usr/lib64/python2.7/csv.pyR5Vs cCs ||_dS(N(R/(Rtvalue((s/usr/lib64/python2.7/csv.pyR5`scCs�|jdkr|jn|jj�}|jj|_x|gkrX|jj�}q:Wtt|j|��}t|j�}t|�}||kr�||||j<n4||kr�x%|j|D]}|j||<q�Wn|S(Ni( R3R5RR9tdicttziptlenR0R1(Rtrowtdtlftlrtkey((s/usr/lib64/python2.7/csv.pyR9ds N( R!R"R%RR8tpropertyR5tsetterR9(((s/usr/lib64/python2.7/csv.pyRIs cBs>eZdddd�Zd�Zd�Zd�Zd�ZRS(RtraiseRcOsY||_||_|j�dkr4td|�n||_t||||�|_dS(NRFtignores-extrasaction (%s) must be 'raise' or 'ignore'(RFsignore(R5R1tlowert ValueErrortextrasactionR(RR4R5R1RJR2R6R7((s/usr/lib64/python2.7/csv.pyR|s cCs,tt|j|j��}|j|�dS(N(R<R=R5twriterow(Rtheader((s/usr/lib64/python2.7/csv.pytwriteheader�scCs�|jdkr\g|D]}||jkr|^q}|r\tddj|���q\ng|jD]}|j||j�^qfS(NRFs(dict contains fields not in fieldnames: s, (RJR5RItjointgetR1(Rtrowdicttktwrong_fieldsRC((s/usr/lib64/python2.7/csv.pyt _dict_to_list�s(cCs|jj|j|��S(N(RRKRS(RRP((s/usr/lib64/python2.7/csv.pyRK�scCs=g}x$|D]}|j|j|��q W|jj|�S(N(tappendRSRt writerows(RtrowdictstrowsRP((s/usr/lib64/python2.7/csv.pyRU�s (R!R"RRMRSRKRU(((s/usr/lib64/python2.7/csv.pyR{s cBs>eZdZd�Zdd�Zd�Zd�Zd�ZRS(se "Sniffs" the format of a CSV file (i.e. delimiter, quotechar) Returns a Dialect object. cCsdddddg|_dS(NR-s t;t t:(t preferred(R((s/usr/lib64/python2.7/csv.pyR�scCs�|j||�\}}}}|s?|j||�\}}n|sQtd�ndtfd��Y}||_||_|p�d|_||_|S(sI Returns a dialect (or None) corresponding to the sample sCould not determine delimiterR2cBseZdZdZeZRS(tsniffeds (R!R"R#R+R R,(((s/usr/lib64/python2.7/csv.pyR2�sR.(t_guess_quote_and_delimitert_guess_delimiterRRR)R&R'R*(Rtsamplet delimitersR'R)R&R*R2((s/usr/lib64/python2.7/csv.pytsniff�s cCs<g}xCdD];}tj|tjtjB�}|j|�}|r Pq q W|sbdtddfSi}i}d}x|D]�} |jdd} | | }|r�|j|d�d||<ny|jd d} | | }Wnt k r�q{nX|r0|dks||kr0|j|d�d||<ny|jd d} Wnt k r[q{nX| | r{|d7}q{q{Wt |d�|j��}|r�t |d�|j��} || |k}| d kr�d} q�nd} d}tjdi| d 6|d6tj�}|j|�r&t }nt}||| |fS(s� Looks for text enclosed between two identical quotes (the probable quotechar) which are preceded and followed by the same character (the probable delimiter). For example: ,'some text', The quote with the most wins, same with the delimiter. If there is no quotechar the delimiter can't be determined this way. sF(?P<delim>[^\w "'])(?P<space> ?)(?P<quote>["']).*?(?P=quote)(?P=delim)sC(?:^| )(?P<quote>["']).*?(?P=quote)(?P<delim>[^\w "'])(?P<space> ?)sD(?P<delim>>[^\w "'])(?P<space> ?)(?P<quote>["']).*?(?P=quote)(?:$| )s*(?:^| )(?P<quote>["']).*?(?P=quote)(?:$| )RitquoteitdelimtspacecSs||||kr|p|S(N((tatbtquotes((s/usr/lib64/python2.7/csv.pyt<lambda>�scSs||||kr|p|S(N((ReRftdelims((s/usr/lib64/python2.7/csv.pyRh�ss s]((%(delim)s)|^)\W*%(quote)s[^%(delim)s\n]*%(quote)s[^%(delim)s\n]*%(quote)s\W*((%(delim)s)|$)(sF(?P<delim>[^\w "'])(?P<space> ?)(?P<quote>["']).*?(?P=quote)(?P=delim)sC(?:^| )(?P<quote>["']).*?(?P=quote)(?P<delim>[^\w "'])(?P<space> ?)sD(?P<delim>>[^\w "'])(?P<space> ?)(?P<quote>["']).*?(?P=quote)(?:$| )s*(?:^| )(?P<quote>["']).*?(?P=quote)(?:$| )N(tretcompiletDOTALLt MULTILINEtfindallR$R%t groupindexROtKeyErrorRtkeystsearchR(RtdataR`tmatchestrestrtregexpRgRitspacestmtnRCR'RcR*t dq_regexpR)((s/usr/lib64/python2.7/csv.pyR]�s` cCstd|jd��}gtd�D]}t|�^q%}tdt|��}d}i}i}i} dt|t|��} }x�| t|�kr|d7}xk|| |!D]\}xS|D]K} |j| i�}|j| �}|j|d�d||<||| <q�Wq�Wx�|j �D]�} || j �}t|�dkrb|dddkrbq nt|�dkr�td�|�|| <|j|| �|| d|| dtd�|�df|| <q |d|| <q W|j �}t ||�}d}d }x�t| �dkr�||kr�xp|D]h\}}|ddkr4|ddkr4|d||kr�|dks�||kr�|| |<q�q4q4W|d 8}qWt| �dkr| j �d}|dj|�|djd|�k}||fS|} ||7}q�W| s"dSt| �dkr�xZ|jD]L}|| j �kr>|dj|�|djd|�k}||fSq>Wng| j �D]\}}||f^q�}|j�|d d}|dj|�|djd|�k}||fS(s� The delimiter /should/ occur the same number of times on each row. However, due to malformed data, it may not. We don't want an all or nothing approach, so we allow for small variations in this number. 1) build a table of the frequency of each character on every line. 2) build a table of frequencies of this frequency (meta-frequency?), e.g. 'x occurred 5 times in 10 rows, 6 times in 1000 rows, 7 times in 2 rows' 3) use the mode of the meta-frequency to determine the /expected/ frequency for that character 4) find out how often the character actually meets that goal 5) the character that best meets its goal is the delimiter For performance reasons, the data is evaluated in chunks, so it can try and evaluate the smallest portion of the data possible, evaluating additional chunks as necessary. s ii iicSs|d|dkr|p|S(Ni((ReRf((s/usr/lib64/python2.7/csv.pyRhDscSsd|d|dfS(Nii((ReRf((s/usr/lib64/python2.7/csv.pyRhJsg�?g�������?g{�G�z�?s%c Ri����N(Ri(tfilterR%tsplittrangetchrtminR>ROtcountRqtitemsRtremovetfloatR[tsort(RRsR`tctasciitchunkLengtht iterationt charFrequencytmodesRitstarttendtlinetchart metaFrequencytfreqR�tmodeListttotaltconsistencyt thresholdRQtvRcR*R@((s/usr/lib64/python2.7/csv.pyR^sx% & ! + c Cstt|�|j|��}|j�}t|�}i}xt|�D]}d||<qIWd}x�|D]�}|dkr�Pn|d7}t|�|kr�qjnx�|j�D]�} xWtt t tgD]3} y| || �PWq�tt fk r�q�Xq�Wt|| �} | t kr$t} n| || kr�|| dkrQ| || <q[|| =q�q�WqjWd}x�|j�D]�\} }t|�td�kr�t|| �|kr�|d7}q |d8}qvy||| �Wn!ttfk r�|d7}qvX|d8}qvW|dkS(Niii(RRRaR9R>R}R%RqtinttlongR�tcomplexRIt OverflowErrorR�ttypeR( RR_trdrRLtcolumnstcolumnTypestitcheckedR?tcoltthisTypet hasHeadertcolType((s/usr/lib64/python2.7/csv.pyt has_header~sN N( R!R"RRR%RaR]R^R�(((s/usr/lib64/python2.7/csv.pyR�s L i((((( RRjt functoolsRt_csvRRRRRRRRR R RRR RRt cStringIORtImportErrort__all__RRRRR�t NameErrorR�R(((s/usr/lib64/python2.7/csv.pyt<module>s2^ 2"
/home/sudancam/./../../lib/../lib64/python2.7/csv.pyc