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-
- """
- csv.py - read/write/investigate CSV files
- """
-
- import re
- from _csv import Error, __version__, writer, reader, register_dialect, \
- unregister_dialect, get_dialect, list_dialects, \
- QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC, QUOTE_NONE, \
- __doc__
-
- try:
- from cStringIO import StringIO
- except ImportError:
- from StringIO import StringIO
-
- __all__ = [ "QUOTE_MINIMAL", "QUOTE_ALL", "QUOTE_NONNUMERIC", "QUOTE_NONE",
- "Error", "Dialect", "excel", "excel_tab", "reader", "writer",
- "register_dialect", "get_dialect", "list_dialects", "Sniffer",
- "unregister_dialect", "__version__", "DictReader", "DictWriter" ]
-
- class Dialect:
- _name = ""
- _valid = False
- # placeholders
- delimiter = None
- quotechar = None
- escapechar = None
- doublequote = None
- skipinitialspace = None
- lineterminator = None
- quoting = None
-
- def __init__(self):
- if self.__class__ != Dialect:
- self._valid = True
- errors = self._validate()
- if errors != []:
- raise Error, "Dialect did not validate: %s" % ", ".join(errors)
-
- def _validate(self):
- errors = []
- if not self._valid:
- errors.append("can't directly instantiate Dialect class")
-
- if self.delimiter is None:
- errors.append("delimiter character not set")
- elif (not isinstance(self.delimiter, str) or
- len(self.delimiter) > 1):
- errors.append("delimiter must be one-character string")
-
- if self.quotechar is None:
- if self.quoting != QUOTE_NONE:
- errors.append("quotechar not set")
- elif (not isinstance(self.quotechar, str) or
- len(self.quotechar) > 1):
- errors.append("quotechar must be one-character string")
-
- if self.lineterminator is None:
- errors.append("lineterminator not set")
- elif not isinstance(self.lineterminator, str):
- errors.append("lineterminator must be a string")
-
- if self.doublequote not in (True, False):
- errors.append("doublequote parameter must be True or False")
-
- if self.skipinitialspace not in (True, False):
- errors.append("skipinitialspace parameter must be True or False")
-
- if self.quoting is None:
- errors.append("quoting parameter not set")
-
- if self.quoting is QUOTE_NONE:
- if (not isinstance(self.escapechar, (unicode, str)) or
- len(self.escapechar) > 1):
- errors.append("escapechar must be a one-character string or unicode object")
-
- return errors
-
- class excel(Dialect):
- delimiter = ','
- quotechar = '"'
- doublequote = True
- skipinitialspace = False
- lineterminator = '\r\n'
- quoting = QUOTE_MINIMAL
- register_dialect("excel", excel)
-
- class excel_tab(excel):
- delimiter = '\t'
- register_dialect("excel-tab", excel_tab)
-
-
- class DictReader:
- def __init__(self, f, fieldnames=None, restkey=None, restval=None,
- dialect="excel", *args, **kwds):
- self.fieldnames = fieldnames # list of keys for the dict
- self.restkey = restkey # key to catch long rows
- self.restval = restval # default value for short rows
- self.reader = reader(f, dialect, *args, **kwds)
-
- def __iter__(self):
- return self
-
- def next(self):
- row = self.reader.next()
- if self.fieldnames is None:
- self.fieldnames = row
- row = self.reader.next()
-
- # unlike the basic reader, we prefer not to return blanks,
- # because we will typically wind up with a dict full of None
- # values
- while row == []:
- row = self.reader.next()
- d = dict(zip(self.fieldnames, row))
- lf = len(self.fieldnames)
- lr = len(row)
- if lf < lr:
- d[self.restkey] = row[lf:]
- elif lf > lr:
- for key in self.fieldnames[lr:]:
- d[key] = self.restval
- return d
-
-
- class DictWriter:
- def __init__(self, f, fieldnames, restval="", extrasaction="raise",
- dialect="excel", *args, **kwds):
- self.fieldnames = fieldnames # list of keys for the dict
- self.restval = restval # for writing short dicts
- if extrasaction.lower() not in ("raise", "ignore"):
- raise ValueError, \
- ("extrasaction (%s) must be 'raise' or 'ignore'" %
- extrasaction)
- self.extrasaction = extrasaction
- self.writer = writer(f, dialect, *args, **kwds)
-
- def _dict_to_list(self, rowdict):
- if self.extrasaction == "raise":
- for k in rowdict.keys():
- if k not in self.fieldnames:
- raise ValueError, "dict contains fields not in fieldnames"
- return [rowdict.get(key, self.restval) for key in self.fieldnames]
-
- def writerow(self, rowdict):
- return self.writer.writerow(self._dict_to_list(rowdict))
-
- def writerows(self, rowdicts):
- rows = []
- for rowdict in rowdicts:
- rows.append(self._dict_to_list(rowdict))
- return self.writer.writerows(rows)
-
- # Guard Sniffer's type checking against builds that exclude complex()
- try:
- complex
- except NameError:
- complex = float
-
- class Sniffer:
- '''
- "Sniffs" the format of a CSV file (i.e. delimiter, quotechar)
- Returns a Dialect object.
- '''
- def __init__(self):
- # in case there is more than one possible delimiter
- self.preferred = [',', '\t', ';', ' ', ':']
-
-
- def sniff(self, sample, delimiters=None):
- """
- Returns a dialect (or None) corresponding to the sample
- """
-
- quotechar, delimiter, skipinitialspace = \
- self._guess_quote_and_delimiter(sample, delimiters)
- if delimiter is None:
- delimiter, skipinitialspace = self._guess_delimiter(sample,
- delimiters)
-
- class dialect(Dialect):
- _name = "sniffed"
- lineterminator = '\r\n'
- quoting = QUOTE_MINIMAL
- # escapechar = ''
- doublequote = False
-
- dialect.delimiter = delimiter
- # _csv.reader won't accept a quotechar of ''
- dialect.quotechar = quotechar or '"'
- dialect.skipinitialspace = skipinitialspace
-
- return dialect
-
-
- def _guess_quote_and_delimiter(self, data, delimiters):
- """
- 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.
- """
-
- matches = []
- for restr in ('(?P<delim>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?P=delim)', # ,".*?",
- '(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?P<delim>[^\w\n"\'])(?P<space> ?)', # ".*?",
- '(?P<delim>>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?:$|\n)', # ,".*?"
- '(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?:$|\n)'): # ".*?" (no delim, no space)
- regexp = re.compile(restr, re.DOTALL | re.MULTILINE)
- matches = regexp.findall(data)
- if matches:
- break
-
- if not matches:
- return ('', None, 0) # (quotechar, delimiter, skipinitialspace)
-
- quotes = {}
- delims = {}
- spaces = 0
- for m in matches:
- n = regexp.groupindex['quote'] - 1
- key = m[n]
- if key:
- quotes[key] = quotes.get(key, 0) + 1
- try:
- n = regexp.groupindex['delim'] - 1
- key = m[n]
- except KeyError:
- continue
- if key and (delimiters is None or key in delimiters):
- delims[key] = delims.get(key, 0) + 1
- try:
- n = regexp.groupindex['space'] - 1
- except KeyError:
- continue
- if m[n]:
- spaces += 1
-
- quotechar = reduce(lambda a, b, quotes = quotes:
- (quotes[a] > quotes[b]) and a or b, quotes.keys())
-
- if delims:
- delim = reduce(lambda a, b, delims = delims:
- (delims[a] > delims[b]) and a or b, delims.keys())
- skipinitialspace = delims[delim] == spaces
- if delim == '\n': # most likely a file with a single column
- delim = ''
- else:
- # there is *no* delimiter, it's a single column of quoted data
- delim = ''
- skipinitialspace = 0
-
- return (quotechar, delim, skipinitialspace)
-
-
- def _guess_delimiter(self, data, delimiters):
- """
- 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 freqencies 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.
- """
-
- data = filter(None, data.split('\n'))
-
- ascii = [chr(c) for c in range(127)] # 7-bit ASCII
-
- # build frequency tables
- chunkLength = min(10, len(data))
- iteration = 0
- charFrequency = {}
- modes = {}
- delims = {}
- start, end = 0, min(chunkLength, len(data))
- while start < len(data):
- iteration += 1
- for line in data[start:end]:
- for char in ascii:
- metaFrequency = charFrequency.get(char, {})
- # must count even if frequency is 0
- freq = line.strip().count(char)
- # value is the mode
- metaFrequency[freq] = metaFrequency.get(freq, 0) + 1
- charFrequency[char] = metaFrequency
-
- for char in charFrequency.keys():
- items = charFrequency[char].items()
- if len(items) == 1 and items[0][0] == 0:
- continue
- # get the mode of the frequencies
- if len(items) > 1:
- modes[char] = reduce(lambda a, b: a[1] > b[1] and a or b,
- items)
- # adjust the mode - subtract the sum of all
- # other frequencies
- items.remove(modes[char])
- modes[char] = (modes[char][0], modes[char][1]
- - reduce(lambda a, b: (0, a[1] + b[1]),
- items)[1])
- else:
- modes[char] = items[0]
-
- # build a list of possible delimiters
- modeList = modes.items()
- total = float(chunkLength * iteration)
- # (rows of consistent data) / (number of rows) = 100%
- consistency = 1.0
- # minimum consistency threshold
- threshold = 0.9
- while len(delims) == 0 and consistency >= threshold:
- for k, v in modeList:
- if v[0] > 0 and v[1] > 0:
- if ((v[1]/total) >= consistency and
- (delimiters is None or k in delimiters)):
- delims[k] = v
- consistency -= 0.01
-
- if len(delims) == 1:
- delim = delims.keys()[0]
- skipinitialspace = (data[0].count(delim) ==
- data[0].count("%c " % delim))
- return (delim, skipinitialspace)
-
- # analyze another chunkLength lines
- start = end
- end += chunkLength
-
- if not delims:
- return ('', 0)
-
- # if there's more than one, fall back to a 'preferred' list
- if len(delims) > 1:
- for d in self.preferred:
- if d in delims.keys():
- skipinitialspace = (data[0].count(d) ==
- data[0].count("%c " % d))
- return (d, skipinitialspace)
-
- # finally, just return the first damn character in the list
- delim = delims.keys()[0]
- skipinitialspace = (data[0].count(delim) ==
- data[0].count("%c " % delim))
- return (delim, skipinitialspace)
-
-
- def has_header(self, sample):
- # Creates a dictionary of types of data in each column. If any
- # column is of a single type (say, integers), *except* for the first
- # row, then the first row is presumed to be labels. If the type
- # can't be determined, it is assumed to be a string in which case
- # the length of the string is the determining factor: if all of the
- # rows except for the first are the same length, it's a header.
- # Finally, a 'vote' is taken at the end for each column, adding or
- # subtracting from the likelihood of the first row being a header.
-
- rdr = reader(StringIO(sample), self.sniff(sample))
-
- header = rdr.next() # assume first row is header
-
- columns = len(header)
- columnTypes = {}
- for i in range(columns): columnTypes[i] = None
-
- checked = 0
- for row in rdr:
- # arbitrary number of rows to check, to keep it sane
- if checked > 20:
- break
- checked += 1
-
- if len(row) != columns:
- continue # skip rows that have irregular number of columns
-
- for col in columnTypes.keys():
-
- for thisType in [int, long, float, complex]:
- try:
- thisType(row[col])
- break
- except (ValueError, OverflowError):
- pass
- else:
- # fallback to length of string
- thisType = len(row[col])
-
- # treat longs as ints
- if thisType == long:
- thisType = int
-
- if thisType != columnTypes[col]:
- if columnTypes[col] is None: # add new column type
- columnTypes[col] = thisType
- else:
- # type is inconsistent, remove column from
- # consideration
- del columnTypes[col]
-
- # finally, compare results against first row and "vote"
- # on whether it's a header
- hasHeader = 0
- for col, colType in columnTypes.items():
- if type(colType) == type(0): # it's a length
- if len(header[col]) != colType:
- hasHeader += 1
- else:
- hasHeader -= 1
- else: # attempt typecast
- try:
- colType(header[col])
- except (ValueError, TypeError):
- hasHeader += 1
- else:
- hasHeader -= 1
-
- return hasHeader > 0
-