为多次迭代重置csv.reader的正确方法？

Question

自定义迭代器有一个问题，因为它只在文件上迭代一次。我在两次迭代之间对相关文件对象调用seek(0)，但是在第二次运行时对next()的第一次调用时抛出StopIteration。我觉得我忽略了一些显而易见的东西，但我希望能有一些新的眼光来看待这个问题：

class MappedIterator(object):
    """
    Given an iterator of dicts or objects and a attribute mapping dict, 
    will make the objects accessible via the desired interface.

    Currently it will only produce dictionaries with string values. Can be 
    made to support actual objects later on. Somehow... :D
    """

    def __init__(self, obj=None, mapping={}, *args, **kwargs):

        self._obj = obj
        self._mapping = mapping
        self.cnt = 0

    def __iter__(self):

        return self

    def reset(self):

        self.cnt = 0

    def next(self):

        try:

            try:
                item = self._obj.next()
            except AttributeError:
                item = self._obj[self.cnt]

            # If no mapping is provided, an empty object will be returned.
            mapped_obj = {}

            for mapped_attr in self._mapping:

                attr = mapped_attr.attribute
                new_attr = mapped_attr.mapped_name

                val = item.get(attr, '')
                val = str(val).strip() # get rid of whitespace

                # TODO: apply transformers...

                # This allows multi attribute mapping or grouping of multiple
                # attributes in to one.
                try:
                    mapped_obj[new_attr] += val
                except KeyError:
                    mapped_obj[new_attr] = val

            self.cnt += 1

            return mapped_obj

        except (IndexError, StopIteration):

            self.reset()
            raise StopIteration


class CSVMapper(MappedIterator):

    def __init__(self, reader, mapping={}, *args, **kwargs):

        self._reader = reader
        self._mapping = mapping

        self._file = kwargs.pop('file')

        super(CSVMapper, self).__init__(self._reader, self._mapping, *args, **kwargs)

    @classmethod
    def from_csv(cls, file, mapping, *args, **kwargs):

        # TODO: Parse kwargs for various DictReader kwargs.
        return cls(reader=DictReader(file), mapping=mapping, file=file)

    def __len__(self):

      return int(self._reader.line_num)

    def reset(self):

      if self._file:

        self._file.seek(0)

      super(CSVMapper, self).reset()

示例用法：

file = open('somefile.csv', 'rb') # say this file has 2 rows + a header row

mapping = MyMappingClass() # this isn't really relevant

reader = CSVMapper.from_csv(file, mapping)

# > 'John'
# > 'Bob'
for r in reader:

  print r['name']

# This won't print anything
for r in reader:

  print r['name']

Answer 1

对于听写器：

f = open(filename, "rb")
d = csv.DictReader(f, delimiter=",")

f.seek(0)
d.__init__(f, delimiter=",")

对于听写器：

f = open(filename, "rb+")
d = csv.DictWriter(f, fieldnames=fields, delimiter=",")

f.seek(0)
f.truncate(0)
d.__init__(f, fieldnames=fields, delimiter=",")
d.writeheader()
f.flush()