import logging
from datetime import datetime
from pprint import pprint
import httpx
import orjson

import requests
from django.conf import settings

from core.db import StorageBackend, add_defaults, dedup_list
from core.db.processing import parse_results
from core.lib.parsing import (
    QueryError,
    parse_date_time,
    parse_index,
    parse_rule,
    parse_sentiment,
    parse_size,
    parse_sort,
    parse_source,
)

logger = logging.getLogger(__name__)


class ManticoreBackend(StorageBackend):
    def __init__(self):
        super().__init__("manticore")

    def initialise(self, **kwargs):
        """
        Initialise the Manticore client
        """
        pass  # we use requests

    async def async_initialise(self, **kwargs):
        """
        Initialise the Manticore client in async mode
        """
        pass  # we use requests

    def delete_rule_entries(self, rule_id):
        """
        Delete all entries for a given rule.
        :param rule_id: The rule ID to delete.
        """
        # TODO

    def construct_query(self, query, size=None, blank=False, **kwargs):
        """
        Accept some query parameters and construct an OpenSearch query.
        """
        if not size:
            size = 5
        query_base = {
            "index": kwargs.get("index"),
            "limit": size,
            "query": {"bool": {"must": []}},
        }
        print("BASE", query_base)
        query_string = {
            "query_string": query,
        }
        if not blank:
            query_base["query"]["bool"]["must"].append(query_string)
        return query_base
    
    def parse(self, response, **kwargs):
        parsed = parse_results(response, **kwargs)
        return parsed

    def run_query(self, user, search_query, **kwargs):
        """
        Low level helper to run Manticore query.
        """
        index = kwargs.get("index")
        raw = kwargs.get("raw")
        if search_query and not raw:
            search_query["index"] = index
            pprint(search_query)


        path = kwargs.get("path", "json/search")
        if raw:
            response = requests.post(
                f"{settings.MANTICORE_URL}/{path}", search_query
            )
        else:
            response = requests.post(
                f"{settings.MANTICORE_URL}/{path}", json=search_query
            )

        return orjson.loads(response.text)
    
    async def async_run_query(self, user, search_query, **kwargs):
        """
        Low level helper to run Manticore query asynchronously.
        """
        index = kwargs.get("index")
        search_query["index"] = index
        pprint(search_query)
        async with httpx.AsyncClient() as client:
            response = await client.post(
                f"{settings.MANTICORE_URL}/json/search", json=search_query
            )
        return orjson.loads(response.text)
    
    async def async_store_matches(self, matches):
        """
        Store a list of matches in Manticore.
        :param index: The index to store the matches in.
        :param matches: A list of matches to store.
        """
        # TODO

    def store_matches(self, matches):
        """
        Store a list of matches in Manticore.
        :param index: The index to store the matches in.
        :param matches: A list of matches to store.
        """
        # TODO

    def prepare_schedule_query(self, rule_object):
        """
        Helper to run a scheduled query with reduced functionality.
        """
        # TODO

    def schedule_query_results_test_sync(self, rule_object):
        """
        Helper to run a scheduled query test with reduced functionality.
        Sync version for running from Django forms.
        Does not return results.
        """
        # TODO

    async def schedule_query_results(self, rule_object):
        """
        Helper to run a scheduled query with reduced functionality and async.
        """
        # TODO

    def query_results(
        self,
        request,
        query_params,
        size=None,
        annotate=True,
        custom_query=False,
        reverse=False,
        dedup=False,
        dedup_fields=None,
        tags=None,
    ):
        query = None
        message = None
        message_class = None
        add_bool = []
        add_top = []
        add_top_negative = []
        sort = None
        query_created = False
        source = None
        add_defaults(query_params)

        # Now, run the helpers for SIQTSRSS/ADR
        # S - Size
        # I - Index
        # Q - Query
        # T - Tags
        # S - Source
        # R - Ranges
        # S - Sort
        # S - Sentiment
        # A - Annotate
        # D - Dedup
        # R - Reverse

        # S - Size
        if request.user.is_anonymous:
            sizes = settings.MAIN_SIZES_ANON
        else:
            sizes = settings.MAIN_SIZES
        if not size:
            size = parse_size(query_params, sizes)
            if isinstance(size, dict):
                return size
            
        rule_object = parse_rule(request.user, query_params)
        if isinstance(rule_object, dict):
            return rule_object

        if rule_object is not None:
            index = settings.INDEX_RULE_STORAGE
            add_bool.append({"rule_id": str(rule_object.id)})
        else:
            # I - Index
            index = parse_index(request.user, query_params)
            if isinstance(index, dict):
                return index

        # Q/T - Query/Tags
        search_query = self.parse_query(
            query_params, tags, size, custom_query, add_bool
        )
        # Query should be a dict, so check if it contains message here
        if "message" in search_query:
            return search_query

        # S - Sources
        sources = parse_source(request.user, query_params)
        if isinstance(sources, dict):
            return sources
        total_count = len(sources)
        # Total is -1 due to the "all" source
        total_sources = (
            len(settings.MAIN_SOURCES) - 1 + len(settings.SOURCES_RESTRICTED)
        )

        # If the sources the user has access to are equal to all
        # possible sources, then we don't need to add the source
        # filter to the query.
        if total_count != total_sources:
            add_top_tmp = {"bool": {"should": []}}
            for source_iter in sources:
                add_top_tmp["bool"]["should"].append(
                    {"match_phrase": {"src": source_iter}}
                )
            if query_params["source"] != "all":
                add_top.append(add_top_tmp)

        # R - Ranges
        # date_query = False
        from_ts, to_ts = parse_date_time(query_params)
        if from_ts:
            range_query = {
                "range": {
                    "ts": {
                        "gt": from_ts,
                        "lt": to_ts,
                    }
                }
            }
            add_top.append(range_query)

        # S - Sort
        sort = parse_sort(query_params)
        if isinstance(sort, dict):
            return sort

        if rule_object is not None:
            field = "match_ts"
        else:
            field = "ts"
        if sort:
            # For Druid compatibility
            sort_map = {"ascending": "asc", "descending": "desc"}
            sorting = [
                {
                    field: {
                        "order": sort_map[sort],
                    }
                }
            ]
            search_query["sort"] = sorting

        # S - Sentiment
        sentiment_r = parse_sentiment(query_params)
        if isinstance(sentiment_r, dict):
            return sentiment_r
        if sentiment_r:
            if rule_object is not None:
                sentiment_index = "meta.aggs.avg_sentiment.value"
            else:
                sentiment_index = "sentiment"
            sentiment_method, sentiment = sentiment_r
            range_query_compare = {"range": {sentiment_index: {}}}
            range_query_precise = {
                "match": {
                    sentiment_index: None,
                }
            }
            if sentiment_method == "below":
                range_query_compare["range"][sentiment_index]["lt"] = sentiment
                add_top.append(range_query_compare)
            elif sentiment_method == "above":
                range_query_compare["range"][sentiment_index]["gt"] = sentiment
                add_top.append(range_query_compare)
            elif sentiment_method == "exact":
                range_query_precise["match"][sentiment_index] = sentiment
                add_top.append(range_query_precise)
            elif sentiment_method == "nonzero":
                range_query_precise["match"][sentiment_index] = 0
                add_top_negative.append(range_query_precise)

        # Add in the additional information we already populated
        self.add_bool(search_query, add_bool)
        self.add_top(search_query, add_top)
        self.add_top(search_query, add_top_negative, negative=True)

        response = self.query(
            request.user,
            search_query,
            index=index,
        )
        if not response:
            message = "Error running query"
            message_class = "danger"
            return {"message": message, "class": message_class}

        # results = results.to_dict()
        if "error" in response:
            message = response["error"]
            message_class = "danger"
            return {"message": message, "class": message_class}
        if "message" in response:
            return response

        # A/D/R - Annotate/Dedup/Reverse
        response["object_list"] = self.process_results(
            response["object_list"],
            annotate=annotate,
            dedup=dedup,
            dedup_fields=dedup_fields,
            reverse=reverse,
        )

        context = response
        return context