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csv.py - read/write/investigate CSV files
N)Error __version__writerreaderregister_dialectunregister_dialect get_dialect
list_dialectsfield_size_limit
QUOTE_MINIMAL QUOTE_ALLQUOTE_NONNUMERIC
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dd ZdS ) r zDescribe a CSV dialect.
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delimiter, quotechar, escapechar, doublequote, skipinitialspace,
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"Sniffs" the format of a CSV file (i.e. delimiter, quotechar)
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c C s dddddg| _ d S )Nr/ r1 ; :) preferred)r r r r r s zSniffer.__init__Nc C sd | j ||\}}}}|s(| j||\}}|s4tdG dd dt}||_||_|pVd|_||_|S )zI
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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,
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3) use the mode of the meta-frequency to determine the /expected/
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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
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additional chunks as necessary.
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All system for education purposes only. For more tools: Telegram @jackleet