import time

import elasticsearch.client
from django.conf import settings
from elasticsearch_dsl import Document, InnerDoc, Date, Integer, Long, Text, Object, GeoPoint, Keyword, Boolean
from elasticsearch_dsl.connections import connections

from blog.models import Article

ELASTICSEARCH_ENABLED = hasattr(settings, 'ELASTICSEARCH_DSL')

if ELASTICSEARCH_ENABLED:
    connections.create_connection(
        hosts=[settings.ELASTICSEARCH_DSL['default']['hosts']])
    from elasticsearch import Elasticsearch

    es = Elasticsearch(settings.ELASTICSEARCH_DSL['default']['hosts'])
    from elasticsearch.client import IngestClient

    c = IngestClient(es)
    try:
        c.get_pipeline('geoip')
    except elasticsearch.exceptions.NotFoundError:
        c.put_pipeline('geoip', body='''{
              "description" : "Add geoip info",
              "processors" : [
                {
                  "geoip" : {
                    "field" : "ip"
                  }
                }
              ]
            }''')


class GeoIp(InnerDoc):
    continent_name = Keyword()
    country_iso_code = Keyword()
    country_name = Keyword()
    location = GeoPoint()


class UserAgentBrowser(InnerDoc):
    Family = Keyword()
    Version = Keyword()


class UserAgentOS(UserAgentBrowser):
    pass


class UserAgentDevice(InnerDoc):
    Family = Keyword()
    Brand = Keyword()
    Model = Keyword()


class UserAgent(InnerDoc):
    browser = Object(UserAgentBrowser, required=False)
    os = Object(UserAgentOS, required=False)
    device = Object(UserAgentDevice, required=False)
    string = Text()
    is_bot = Boolean()


class ElapsedTimeDocument(Document):
    url = Keyword()
    time_taken = Long()
    log_datetime = Date()
    ip = Keyword()
    geoip = Object(GeoIp, required=False)
    useragent = Object(UserAgent, required=False)

    class Index:
        name = 'performance'
        settings = {
            "number_of_shards": 1,
            "number_of_replicas": 0
        }

    class Meta:
        doc_type = 'ElapsedTime'


class ElaspedTimeDocumentManager:
    @staticmethod
    def build_index():
        from elasticsearch import Elasticsearch
        client = Elasticsearch(settings.ELASTICSEARCH_DSL['default']['hosts'])
        res = client.indices.exists(index="performance")
        if not res:
            ElapsedTimeDocument.init()

    @staticmethod
    def delete_index():
        from elasticsearch import Elasticsearch
        es = Elasticsearch(settings.ELASTICSEARCH_DSL['default']['hosts'])
        es.indices.delete(index='performance', ignore=[400, 404])

    @staticmethod
    def create(url, time_taken, log_datetime, useragent, ip):
        ElaspedTimeDocumentManager.build_index()
        ua = UserAgent()
        ua.browser = UserAgentBrowser()
        ua.browser.Family = useragent.browser.family
        ua.browser.Version = useragent.browser.version_string

        ua.os = UserAgentOS()
        ua.os.Family = useragent.os.family
        ua.os.Version = useragent.os.version_string

        ua.device = UserAgentDevice()
        ua.device.Family = useragent.device.family
        ua.device.Brand = useragent.device.brand
        ua.device.Model = useragent.device.model
        ua.string = useragent.ua_string
        ua.is_bot = useragent.is_bot

        doc = ElapsedTimeDocument(
            meta={
                'id': int(
                    round(
                        time.time() *
                        1000))
            },
            url=url,
            time_taken=time_taken,
            log_datetime=log_datetime,
            useragent=ua, ip=ip)
        doc.save(pipeline="geoip")


class ArticleDocument(Document):
    body = Text(analyzer='ik_max_word', search_analyzer='ik_smart')
    title = Text(analyzer='ik_max_word', search_analyzer='ik_smart')
    author = Object(properties={
        'nickname': Text(analyzer='ik_max_word', search_analyzer='ik_smart'),
        'id': Integer()
    })
    category = Object(properties={
        'name': Text(analyzer='ik_max_word', search_analyzer='ik_smart'),
        'id': Integer()
    })
    tags = Object(properties={
        'name': Text(analyzer='ik_max_word', search_analyzer='ik_smart'),
        'id': Integer()
    })

    pub_time = Date()
    status = Text()
    comment_status = Text()
    type = Text()
    views = Integer()
    article_order = Integer()

    class Index:
        name = 'blog'
        settings = {
            "number_of_shards": 1,
            "number_of_replicas": 0
        }

    class Meta:
        doc_type = 'Article'


class ArticleDocumentManager():

    def __init__(self):
        self.create_index()

    def create_index(self):
        ArticleDocument.init()

    def delete_index(self):
        from elasticsearch import Elasticsearch
        es = Elasticsearch(settings.ELASTICSEARCH_DSL['default']['hosts'])
        es.indices.delete(index='blog', ignore=[400, 404])

    def convert_to_doc(self, articles):
        return [
            ArticleDocument(
                meta={
                    'id': article.id},
                body=article.body,
                title=article.title,
                author={
                    'nickname': article.author.username,
                    'id': article.author.id},
                category={
                    'name': article.category.name,
                    'id': article.category.id},
                tags=[
                    {
                        'name': t.name,
                        'id': t.id} for t in article.tags.all()],
                pub_time=article.pub_time,
                status=article.status,
                comment_status=article.comment_status,
                type=article.type,
                views=article.views,
                article_order=article.article_order) for article in articles]

    def rebuild(self, articles=None):
        ArticleDocument.init()
        articles = articles if articles else Article.objects.all()
        docs = self.convert_to_doc(articles)
        for doc in docs:
            doc.save()

    def update_docs(self, docs):
        for doc in docs:
            doc.save()