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CSV parsing and writing.
This module provides classes that assist in the reading and writing
of Comma Separated Value (CSV) files, and implements the interface
described by PEP 305. Although many CSV files are simple to parse,
the format is not formally defined by a stable specification and
is subtle enough that parsing lines of a CSV file with something
like line.split(",") is bound to fail. The module supports three
basic APIs: reading, writing, and registration of dialects.
DIALECT REGISTRATION:
Readers and writers support a dialect argument, which is a convenient
handle on a group of settings. When the dialect argument is a string,
it identifies one of the dialects previously registered with the module.
If it is a class or instance, the attributes of the argument are used as
the settings for the reader or writer:
class excel:
delimiter = ','
quotechar = '"'
escapechar = None
doublequote = True
skipinitialspace = False
lineterminator = '\r\n'
quoting = QUOTE_MINIMAL
SETTINGS:
* quotechar - specifies a one-character string to use as the
quoting character. It defaults to '"'.
* delimiter - specifies a one-character string to use as the
field separator. It defaults to ','.
* skipinitialspace - specifies how to interpret spaces which
immediately follow a delimiter. It defaults to False, which
means that spaces immediately following a delimiter is part
of the following field.
* lineterminator - specifies the character sequence which should
terminate rows.
* quoting - controls when quotes should be generated by the writer.
It can take on any of the following module constants:
csv.QUOTE_MINIMAL means only when required, for example, when a
field contains either the quotechar or the delimiter
csv.QUOTE_ALL means that quotes are always placed around fields.
csv.QUOTE_NONNUMERIC means that quotes are always placed around
fields which do not parse as integers or floating-point
numbers.
csv.QUOTE_STRINGS means that quotes are always placed around
fields which are strings. Note that the Python value None
is not a string.
csv.QUOTE_NOTNULL means that quotes are only placed around fields
that are not the Python value None.
csv.QUOTE_NONE means that quotes are never placed around fields.
* escapechar - specifies a one-character string used to escape
the delimiter when quoting is set to QUOTE_NONE.
* doublequote - controls the handling of quotes inside fields. When
True, two consecutive quotes are interpreted as one during read,
and when writing, each quote character embedded in the data is
written as two quotes
N)Errorwriterreaderregister_dialectunregister_dialect get_dialect
list_dialectsfield_size_limit
QUOTE_MINIMAL QUOTE_ALLQUOTE_NONNUMERIC
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S rS rSrg) r X zDescribe a CSV dialect.
This must be subclassed (see csv.excel). Valid attributes are:
delimiter, quotechar, escapechar, doublequote, skipinitialspace,
lineterminator, quoting.
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"Sniffs" the format of a CSV file (i.e. delimiter, quotechar)
Returns a Dialect object.
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Returns a dialect (or None) corresponding to the sample
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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.
)zI(?P[^\w\n"\'])(?P ?)(?P["\']).*?(?P=quote)(?P=delim)zG(?:^|\n)(?P["\']).*?(?P=quote)(?P[^\w\n"\'])(?P ?)zG(?P[^\w\n"\'])(?P ?)(?P["\']).*?(?P=quote)(?:$|\n)z-(?:^|\n)(?P["\']).*?(?P=quote)(?:$|\n))r FNr r quote delimspaceri rF r z]((%(delim)s)|^)\W*%(quote)s[^%(delim)s\n]*%(quote)s[^%(delim)s\n]*%(quote)s\W*((%(delim)s)|$))r r TF) recompileDOTALL MULTILINEfindall
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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,
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
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