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import datetime
import time

from django.conf import settings

import elasticsearch_dsl as es
from elasticsearch.helpers import bulk
from elasticsearch_dsl.connections import connections

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ES_CONNECTIONS = {
    'default': {
        'hosts': [http://localhost:9200],
    }
}

ES_INDEXES = {
    'default': [
        ('users', 'some_app.indexes.Article'),
    ]

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from pydoc import locate

from django.conf import settings
from django.core.management.base import BaseCommand


class Command(BaseCommand):

    def __init__(self):
        super(Command, self).__init__()

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indexing the documents

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def get_reserved_tickets(self, performance=None):
    Offer = apps.get_model('events', 'Offer')
    Order = apps.get_model('events', 'Order')
    offers = Offer.objects.published().filter(
        state=1,
        ticket_price=self,
    )
    if performance:
        offers = offers.filter(performance=performance)
    pending_tickets = offers.filter(basket__state=0).distinct() \

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for offer in basket.offer_set.published().exclude(ticket_price__state=13):
    _voucher_ids = list(offer.ticket_price.ticket_vouchers_multiple.all().values_list('id', flat=True))
    if (offer.ticket_price.ticket_voucher and offer.ticket_price.ticket_voucher != ticket_price) or (_voucher_ids and ticket_price.id not in _voucher_ids):
        ....

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"""
Assume the structure of the document looks like this

{
    "user": {
        "first_name": "Foo",
        "last_name": "Bar",
        "age": "30",
        "city": {
            "id": 5,

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from elasticsearch_dsl import connections, UpdateByQuery


def bulk_update_docs(ids, instance, fields_changed=[]):
    """
    Arguments:
        ids: {list} -- list of ids of documents we want to update
        instance {Model instance} -- The updated user model object
        fields_changed {list} -- list of the model fields changed
    """

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# an example from elasticsearch-dsl docs
from elasticsearch_dsl import analyzer


html_strip = analyzer('html_strip',
    tokenizer="standard",
    filter=["standard", "lowercase", "stop", "snowball"],
    char_filter=["html_strip"]
)

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from elasticsearch_dsl import FacetedSearch, TermsFacet


class TweetSearch(FacetedSearch):

    facets = {
        # use bucket aggregations to define facets
        'city': TermsFacet(field='user.city.name'),
    }