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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def bulk_index(cls, documents, id_field='id', es=None, index=None):
 """Adds or updates a batch of documents. :arg documents: List of Python dicts representing individual documents to be added to the index .. Note:: This must be serializable into JSON. :arg id_field: The name of the field to use as the document id. This defaults to 'id'. :arg es: The `Elasticsearch` to use. If you don't specify an `Elasticsearch`, it'll use `cls.get_es()`. :arg index: The name of the index to use. If you don't specify one it'll use `cls.get_index()`. .. Note:: If you need the documents available for searches immediately, make sure to refresh the index by calling ``refresh_index()``. """

        if es is None:
            es = cls.get_es()

        if index is None:
            index = cls.get_index()

        documents = (dict(d, _id=d[id_field]) for d in documents)

        bulk_index(
            es,
            documents,
            index=index,
            doc_type=cls.get_mapping_type_name(),
            raise_on_error=True
        )