def _ReadCSV(self, file_name, cols, required, deprecated):
    """Reads lines from file_name, yielding a list of unicode values
    corresponding to the column names in cols."""
    contents = self._GetUtf8Contents(file_name)
    if not contents:
      return

    eol_checker = util.EndOfLineChecker(StringIO.StringIO(contents),
                                   file_name, self._problems)
    reader = csv.reader(eol_checker)  # Use excel dialect

    header = reader.next()
    header = map(lambda x: x.strip(), header)  # trim any whitespace
    header_occurrences = util.defaultdict(lambda: 0)
    for column_header in header:
      header_occurrences[column_header] += 1

    for name, count in header_occurrences.items():
      if count > 1:
        self._problems.DuplicateColumn(
            header=name,
            file_name=file_name,
            count=count)

    # check for unrecognized columns, which are often misspellings
    header_context = (file_name, 1, [''] * len(header), header)
    valid_cols = cols + [deprecated_name for (deprecated_name, _) in deprecated]
    unknown_cols = set(header).difference(set(valid_cols))
    for col in unknown_cols:
      # this is provided in order to create a nice colored list of
      # columns in the validator output
      self._problems.UnrecognizedColumn(file_name, col, header_context)

    # check for missing required columns
    col_index = [-1] * len(cols)
    for i in range(len(cols)):
      if cols[i] in header:
        col_index[i] = header.index(cols[i])
      elif cols[i] in required:
        self._problems.MissingColumn(file_name, cols[i], header_context)

    # check for deprecated columns
    for (deprecated_name, new_name) in deprecated:
      if deprecated_name in header:
        self._problems.DeprecatedColumn(file_name, deprecated_name, new_name,
                                        header_context)

    row_num = 1
    for row in reader:
      row_num += 1
      if len(row) == 0:  # skip extra empty lines in file
        continue

      if len(row) > len(header):
        self._problems.OtherProblem('Found too many cells (commas) in line '
                                    '%d of file "%s".  Every row in the file '
                                    'should have the same number of cells as '
                                    'the header (first line) does.' %
                                    (row_num, file_name), (file_name, row_num),
                                    type=problems.TYPE_WARNING)

      if len(row) < len(header):
        self._problems.OtherProblem('Found missing cells (commas) in line '
                                    '%d of file "%s".  Every row in the file '
                                    'should have the same number of cells as '
                                    'the header (first line) does.' %
                                    (row_num, file_name), (file_name, row_num),
                                    type=problems.TYPE_WARNING)

      result = [None] * len(cols)
      unicode_error_columns = []  # A list of column numbers with an error
      for i in range(len(cols)):
        ci = col_index[i]
        if ci >= 0:
          if len(row) <= ci:  # handle short CSV rows
            result[i] = u''
          else:
            try:
              result[i] = row[ci].decode('utf-8').strip()
            except __HOLE__:
              # Replace all invalid characters with
              # REPLACEMENT CHARACTER (U+FFFD)
              result[i] = codecs.getdecoder("utf8")(row[ci],
                                                    errors="replace")[0].strip()
              unicode_error_columns.append(i)

      for i in unicode_error_columns:
        self._problems.InvalidValue(cols[i], result[i],
                                    'Unicode error',
                                    (file_name, row_num, result, cols))
      yield (result, row_num, cols)
dataset/ETHPy150Open google/transitfeed/transitfeed/loader.py/Loader._ReadCSV