"""
csv.py - read/write/investigate CSV files
"""

import re
from _csv import Error, __version__, writer, reader, register_dialect, \
 unregister_dialect, get_dialect, list_dialects, \
 field_size_limit, \
 QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC, QUOTE_NONE, \
 __doc__
from _csv import Dialect as _Dialect

from io import StringIO

__all__ = ["QUOTE_MINIMAL", "QUOTE_ALL", "QUOTE_NONNUMERIC", "QUOTE_NONE",
 "Error", "Dialect", "__doc__", "excel", "excel_tab",
 "field_size_limit", "reader", "writer",
 "register_dialect", "get_dialect", "list_dialects", "Sniffer",
 "unregister_dialect", "__version__", "DictReader", "DictWriter",
 "unix_dialect"]

class Dialect:
 """Describe a CSV dialect.

 This must be subclassed (see csv.excel). Valid attributes are:
 delimiter, quotechar, escapechar, doublequote, skipinitialspace,
 lineterminator, quoting.

 """
 _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
 self._validate()

 def _validate(self):
 try:
 _Dialect(self)
 except TypeError as e:
 # We do this for compatibility with py2.3
 raise Error(str(e))

class excel(Dialect):
 """Describe the usual properties of Excel-generated CSV files."""
 delimiter = ','
 quotechar = '"'
 doublequote = True
 skipinitialspace = False
 lineterminator = '\r\n'
 quoting = QUOTE_MINIMAL
register_dialect("excel", excel)

class excel_tab(excel):
 """Describe the usual properties of Excel-generated TAB-delimited files."""
 delimiter = '\t'
register_dialect("excel-tab", excel_tab)

class unix_dialect(Dialect):
 """Describe the usual properties of Unix-generated CSV files."""
 delimiter = ','
 quotechar = '"'
 doublequote = True
 skipinitialspace = False
 lineterminator = '\n'
 quoting = QUOTE_ALL
register_dialect("unix", unix_dialect)


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)
 self.dialect = dialect
 self.line_num = 0

 def __iter__(self):
 return self

 @property
 def fieldnames(self):
 if self._fieldnames is None:
 try:
 self._fieldnames = next(self.reader)
 except StopIteration:
 pass
 self.line_num = self.reader.line_num
 return self._fieldnames

 @fieldnames.setter
 def fieldnames(self, value):
 self._fieldnames = value

 def __next__(self):
 if self.line_num == 0:
 # Used only for its side effect.
 self.fieldnames
 row = next(self.reader)
 self.line_num = self.reader.line_num

 # 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 = next(self.reader)
 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 writeheader(self):
 header = dict(zip(self.fieldnames, self.fieldnames))
 return self.writerow(header)

 def _dict_to_list(self, rowdict):
 if self.extrasaction == "raise":
 wrong_fields = rowdict.keys() - self.fieldnames
 if wrong_fields:
 raise ValueError("dict contains fields not in fieldnames: "
 + ", ".join([repr(x) for x in wrong_fields]))
 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):
 return self.writer.writerows(map(self._dict_to_list, rowdicts))

# 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, doublequote, delimiter, skipinitialspace = \
 self._guess_quote_and_delimiter(sample, delimiters)
 if not delimiter:
 delimiter, skipinitialspace = self._guess_delimiter(sample,
 delimiters)

 if not delimiter:
 raise Error("Could not determine delimiter")

 class dialect(Dialect):
 _name = "sniffed"
 lineterminator = '\r\n'
 quoting = QUOTE_MINIMAL
 # escapechar = ''

 dialect.doublequote = doublequote
 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 (r'(?P<delim>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?P=delim)', # ,".*?",
 r'(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?P<delim>[^\w\n"\'])(?P<space> ?)', # ".*?",
 r'(?P<delim>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?:$|\n)', # ,".*?"
 r'(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?:$|\n)'): # ".*?" (no delim, no space)
 regexp = re.compile(restr, re.DOTALL | re.MULTILINE)
 matches = regexp.findall(data)
 if matches:
 break

 if not matches:
 # (quotechar, doublequote, delimiter, skipinitialspace)
 return ('', False, None, 0)
 quotes = {}
 delims = {}
 spaces = 0
 groupindex = regexp.groupindex
 for m in matches:
 n = groupindex['quote'] - 1
 key = m[n]
 if key:
 quotes[key] = quotes.get(key, 0) + 1
 try:
 n = 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 = groupindex['space'] - 1
 except KeyError:
 continue
 if m[n]:
 spaces += 1

 quotechar = max(quotes, key=quotes.get)

 if delims:
 delim = max(delims, key=delims.get)
 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

 # if we see an extra quote between delimiters, we've got a
 # double quoted format
 dq_regexp = re.compile(
 r"((%(delim)s)|^)\W*%(quote)s[^%(delim)s\n]*%(quote)s[^%(delim)s\n]*%(quote)s\W*((%(delim)s)|$)" % \
 {'delim':re.escape(delim), 'quote':quotechar}, re.MULTILINE)



 if dq_regexp.search(data):
 doublequote = True
 else:
 doublequote = False

 return (quotechar, doublequote, 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 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.
 """

 data = list(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, chunkLength
 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.count(char)
 # value is the mode
 metaFrequency[freq] = metaFrequency.get(freq, 0) + 1
 charFrequency[char] = metaFrequency

 for char in charFrequency.keys():
 items = list(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] = max(items, key=lambda x: x[1])
 # adjust the mode - subtract the sum of all
 # other frequencies
 items.remove(modes[char])
 modes[char] = (modes[char][0], modes[char][1]
 - sum(item[1] for item in items))
 else:
 modes[char] = items[0]

 # build a list of possible delimiters
 modeList = modes.items()
 total = float(min(chunkLength * iteration, len(data)))
 # (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 = list(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)

 # nothing else indicates a preference, pick the character that
 # dominates(?)
 items = [(v,k) for (k,v) in delims.items()]
 items.sort()
 delim = items[-1][1]

 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 = next(rdr) # 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 list(columnTypes.keys()):

 for thisType in [int, float, complex]:
 try:
 thisType(row[col])
 break
 except (ValueError, OverflowError):
 pass
 else:
 # fallback to length of string
 thisType = len(row[col])

 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