How to use the unicodecsv.Sniffer function in unicodecsv

from __future__ import unicode_literals

from io import BytesIO

import six
import unicodecsv

from rows.plugins.utils import (
    create_table,
    ipartition,
    serialize,
)
from rows.utils import Source

sniffer = unicodecsv.Sniffer()
# Some CSV files have more than 128kB of data in a cell, so we force this value
# to be greater (16MB).
# TODO: check if it impacts in memory usage.
# TODO: may add option to change it by passing a parameter to import/export.
unicodecsv.field_size_limit(16777216)


def fix_dialect(dialect):
    if not dialect.doublequote and dialect.escapechar is None:
        dialect.doublequote = True

    if dialect.quoting == unicodecsv.QUOTE_MINIMAL and dialect.quotechar == "'":
        # Python csv's Sniffer seems to detect a wrong quotechar when
        # quoting is minimal
        dialect.quotechar = '"'

def csv_data(csv_path, skip_header=True):
    """Pass in the path to a CSV file, returns a CSV Reader object.
    """
    csv_file = open(csv_path, 'r')
    # Determine the CSV dialect.
    dialect = unicodecsv.Sniffer().sniff(csv_file.read(1024))
    csv_file.seek(0)
    data = unicodecsv.reader(csv_file, dialect)
    if skip_header:
        data.next()
    return data

def _csv_data_from_file(csv_file, preview_limit=10):

    try:
        dialect = unicodecsv.Sniffer().sniff(csv_file.read(1024))
        csv_file.seek(0)
        csv_reader = unicodecsv.reader(csv_file, dialect)
        csv_values = itertools.islice(csv_reader, preview_limit)
        csv_values = zip(*csv_values)
        return {'success': True, 'data': csv_values}
    except unicodecsv.Error as exc:
        return {'success': False, 'error': exc.message}
    except UnicodeDecodeError as exc:
        return {'success': False, 'error': exc}

break
        detector.close()
        encoding = detector.result['encoding']
        logger.info("Detected encoding: {} ({} confidence)".format(detector.result['encoding'],
                                                                   detector.result['confidence']))

    if delimiter is None:
        try: #Python 3
            with open(infile, 'r', errors='ignore') as csvfile:
                # dialect = csv.Sniffer().sniff(csvfile.read(1024), delimiters=";,$\t")
                dialect = csv.Sniffer().sniff(csvfile.readline()) #read only the header instead of the entire file to determine delimiter
                csvfile.seek(0)
        except TypeError: #Python 2
            with open(infile, 'r') as csvfile:
                # dialect = csv.Sniffer().sniff(csvfile.read(1024), delimiters=";,$\t")
                dialect = csv.Sniffer().sniff(csvfile.readline()) #read only the header instead of the entire file to determine delimiter
                csvfile.seek(0)
        logger.info("Detected dialect: {} (delimiter: '{}')".format(dialect, dialect.delimiter))
        delimiter = dialect.delimiter


    logger.info("Delimiter is: {}".format(delimiter))

    if base.endswith('/'):
        base = base[:-1]

    metadata = {
        u"@id": iribaker.to_iri(u"{}/{}".format(base, url)),
        u"@context": [u"https://raw.githubusercontent.com/CLARIAH/COW/master/csvw.json",
                     {u"@language": u"en",
                      u"@base": u"{}/".format(base)},
                     get_namespaces(base)],

def clean_csv_file(self):
        csv_file = self.cleaned_data['csv_file']

        # Universal newlines
        # Ugly hack - but works for now
        csv_string = '\n'.join(csv_file.read().splitlines())
        csv_file = StringIO.StringIO(csv_string)

        # TODO: Use chardet
        # Ref: https://github.com/dokterbob/django-newsletter/blob/master/newsletter/admin_forms.py#L86
        sniffer = csv.Sniffer()

        # Python's CSV code eats only UTF-8
        csv_file = codecs.EncodedFile(csv_file, self.charset)

        try:
            if self.dialect:
                # Override dialect, don't autodetect
                dialect = self.dialect
            else:
                # Sniff dialect
                dialect = sniffer.sniff(
                    csv_string,
                    delimiters=self.delimiters
                )

            # Sniff for a header