Source code for azure.search._index._paging

# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
from typing import TYPE_CHECKING

import base64
import itertools
import json

from azure.core.paging import ItemPaged, PageIterator, ReturnType
from ._generated.models import SearchRequest

if TYPE_CHECKING:
    # pylint:disable=unused-import,ungrouped-imports
    from typing import Any, Union


def convert_search_result(result):
    ret = result.additional_properties
    ret["@search.score"] = result.score
    ret["@search.highlights"] = result.highlights
    return ret


def pack_continuation_token(response):
    if response.next_page_parameters is not None:
        return base64.b64encode(
            json.dumps(
                [response.next_link, response.next_page_parameters.serialize()]
            ).encode("utf-8")
        )
    return None


def unpack_continuation_token(token):
    next_link, next_page_parameters = json.loads(base64.b64decode(token))
    next_page_request = SearchRequest.deserialize(next_page_parameters)
    return next_link, next_page_request


[docs]class SearchItemPaged(ItemPaged[ReturnType]): def __init__(self, *args, **kwargs): super(SearchItemPaged, self).__init__(*args, **kwargs) self._first_page_iterator_instance = None def __next__(self): # type: () -> ReturnType if self._page_iterator is None: first_iterator = self._first_iterator_instance() self._page_iterator = itertools.chain.from_iterable(first_iterator) return next(self._page_iterator) def _first_iterator_instance(self): if self._first_page_iterator_instance is None: self._first_page_iterator_instance = self.by_page() return self._first_page_iterator_instance
[docs] def get_facets(self): # type: () -> Union[dict, None] """Return any facet results if faceting was requested. """ return self._first_iterator_instance().get_facets()
class SearchPageIterator(PageIterator): def __init__(self, client, initial_query, kwargs, continuation_token=None): super(SearchPageIterator, self).__init__( get_next=self._get_next_cb, extract_data=self._extract_data_cb, continuation_token=continuation_token, ) self._client = client self._initial_query = initial_query self._kwargs = kwargs self._facets = None def _get_next_cb(self, continuation_token): if continuation_token is None: return self._client.documents.search_post( search_request=self._initial_query.request, **self._kwargs ) _next_link, next_page_request = unpack_continuation_token(continuation_token) return self._client.documents.search_post(search_request=next_page_request) def _extract_data_cb(self, response): # pylint:disable=no-self-use continuation_token = pack_continuation_token(response) facets = response.facets if facets is not None: self._facets = {k: [x.as_dict() for x in v] for k, v in facets.items()} results = [convert_search_result(r) for r in response.results] return continuation_token, results def get_facets(self): if self._current_page is None: self._response = self._get_next(self.continuation_token) self.continuation_token, self._current_page = self._extract_data( self._response ) return self._facets