from typing import Any, Dict, List, Mapping

from analytics.constants import cache
from analytics.constants import date as date_constants
from analytics.queries.format import format_row
from analytics.queries.product import (
    ProductBulkGrowthPeriods,
    ProductDownloadsTimeSeries,
    ProductStreamsTimeSeries,
)
from analytics.utils.cache import cache_in_redis
from analytics.utils.store_availability import is_apple_spotify_data_in_sync

# TODO implement remaining aggregations
from analytics.utils.streams import (
    breakdown_by_sos,
    calc_date_skip_rate,
    check_store_ids_for_sos_detailed,
    get_streams_sos_detailed_columns,
    get_streams_sos_detailed_columns_from_stream_sources,
)

TOTAL_TIMESERIES_TYPE = "PRODUCT_STREAMS"
TOTAL_SUMMARY_TYPE = "TOTAL"

AGGREGATION_FIELDS_TIMESERIES = {
    "PRODUCT_STREAMS_BY_STORE": "store_id",
    "PRODUCT_STREAMS_BY_TRACK": "tracks.isrc",
    "PRODUCT_STREAMS_BY_COUNTRY": "country_code",
    "PRODUCT_DOWNLOADS_BY_COUNTRY": "country_code",
    "PRODUCT_DOWNLOADS_BY_STORE": "store_id",
    "TRACK_DOWNLOADS_BY_TRACK": "tracks.isrc",
    "TRACK_DOWNLOADS_BY_COUNTRY": "country_code",
    "TRACK_DOWNLOADS_BY_STORE": "store_id",
}
AGGREGATION_FIELDS_SUMMARY = {
    "TOTAL": "product_id",
    "STORE": "store_id",
    # TODO SOUND_RECORDING was "tracks.track_unique_id", check data and multi product
    "SOUND_RECORDING": "isrc",
    "COUNTRY": "country_code",
    # TODO check data is accurate when using this for id
    "SOS": "product_id",
}

# map of type -> aggregation type -> table
PRODUCT_TABLES_TIMESERIES = {
    # Product streams
    "PRODUCT_STREAMS": {
        "total": "V_STREAMS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
        "country": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "PRODUCT_STREAMS_BY_TRACK": {
        "total": "V_STREAMS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
        "country": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "PRODUCT_STREAMS_BY_COUNTRY": {
        "total": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
        "country": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "PRODUCT_STREAMS_BY_STORE": {
        "total": "V_STREAMS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
        "country": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "PRODUCT_STREAMS_BY_SOS": {
        "total": "V_STREAMS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
        "country": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "PRODUCT_STREAMS_BY_SOS_DETAILED": {
        "total": "V_STREAMS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
        "country": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    # Product downloads
    "PRODUCT_DOWNLOADS": {
        "total": "DOWNLOADS_BY_PRODUCT_FEED_DISTRIBUTOR_DAILY",
        "country": "DOWNLOADS_BY_PRODUCT_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "PRODUCT_DOWNLOADS_BY_COUNTRY": {
        "total": "DOWNLOADS_BY_PRODUCT_COUNTRY_FEED_DISTRIBUTOR_DAILY",
        "country": "DOWNLOADS_BY_PRODUCT_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "PRODUCT_DOWNLOADS_BY_STORE": {
        "total": "DOWNLOADS_BY_PRODUCT_FEED_DISTRIBUTOR_DAILY",
        "country": "DOWNLOADS_BY_PRODUCT_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    # Product track downloads
    "TRACK_DOWNLOADS": {
        "total": "DOWNLOADS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
        "country": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "TRACK_DOWNLOADS_BY_TRACK": {
        "total": "DOWNLOADS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
        "country": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "TRACK_DOWNLOADS_BY_COUNTRY": {
        "total": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
        "country": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
    "TRACK_DOWNLOADS_BY_STORE": {
        "total": "DOWNLOADS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
        "country": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
    },
}

# map of type -> aggregation type -> dict of tables required
PRODUCT_TABLES_SUMMARY = {
    # Product streams
    "TOTAL": {
        "total": {
            "streams_table": "V_STREAMS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_FEED_DISTRIBUTOR_DAILY",
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
        "country": {
            "streams_table": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
    },
    "SOUND_RECORDING": {
        "total": {
            "streams_table": "V_STREAMS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
        "country": {
            "streams_table": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
    },
    "COUNTRY": {
        "total": {
            "streams_table": "STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
        "country": {
            "streams_table": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
    },
    "STORE": {
        "total": {
            "streams_table": "V_STREAMS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_FEED_DISTRIBUTOR_DAILY",
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
        "country": {
            "streams_table": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
    },
    "SOS": {
        "total": {
            "streams_table": "V_STREAMS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
        "country": {
            "streams_table": "V_STREAMS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
            "product_track_downloads_table": "DOWNLOADS_BY_PRODUCT_TRACK_COUNTRY_FEED_DISTRIBUTOR_DAILY",  # noqa
        },
    },
}


def get_product_table_for_timeseries(query_type: str, countries: List) -> str:
    key = "total"
    if len(countries) != 0:
        key = "country"
    table_options = PRODUCT_TABLES_TIMESERIES.get(query_type)
    if not table_options:
        raise NotImplementedError(f"Query {query_type} not supported")
    table = table_options.get(key)
    if not table:
        raise NotImplementedError(f"Query {query_type} not supported with type {key}")

    return table


@cache_in_redis(ttl=cache.ONE_DAY)
def get_product_timeseries(
    query_params: Mapping[str, Any],
    permissions: Mapping[str, Any],
) -> List[Dict]:
    if query_params.get("multi_product"):
        # check if we're requesting all time and if so, get the min release date
        if query_params.get("date_period") == date_constants.ALL_TIME_GRAPHQL:
            query_params["get_all_time_for_multi_product"] = True

    query_type = query_params.get("type", TOTAL_TIMESERIES_TYPE)

    aggregation_field = AGGREGATION_FIELDS_TIMESERIES.get(query_type)
    if aggregation_field:
        query_params["aggregation_field"] = aggregation_field
    countries = query_params.get("countries", [])

    query_params["product_table"] = get_product_table_for_timeseries(
        query_type, countries
    )

    if query_type == "PRODUCT_STREAMS_BY_SOS_DETAILED":
        store_ids = check_store_ids_for_sos_detailed(query_params.get("store_ids", []))
        stream_sources = query_params.get("stream_sources", [])
        if stream_sources:
            query_params[
                "streams_sos_columns"
            ] = get_streams_sos_detailed_columns_from_stream_sources(
                store_ids, stream_sources
            )
        else:
            query_params["streams_sos_columns"] = get_streams_sos_detailed_columns(
                store_ids
            )

    if query_type.startswith("PRODUCT_STREAMS"):
        query = ProductStreamsTimeSeries({**query_params, **permissions})
    else:
        query = ProductDownloadsTimeSeries({**query_params, **permissions})

    time_series = query.execute()

    ts = []
    # todo refactor
    for data_point in time_series:
        data_point = format_row(data_point)
        if (
            data_point.get("streams_with_skips")
            or data_point.get("streams_with_skips") == 0
        ):
            skip_rate = calc_date_skip_rate(data_point)
            del data_point["streams_with_skips"]
            data_point["skip_rate"] = skip_rate
        ts.append(data_point)

    if query_type == "PRODUCT_STREAMS_BY_SOS":
        ids = query_params.get("ids")

        timeseries = []
        for item in ts:
            timeseries.extend(breakdown_by_sos(item, sources=ids))
        ts = timeseries

    if query_type == "PRODUCT_STREAMS_BY_SOS_DETAILED":
        timeseries = []
        for item in ts:
            timeseries.extend(
                breakdown_by_sos(
                    item,
                    sources=query_params["streams_sos_columns"],
                    version=2,
                )
            )
        ts = timeseries

    return ts


@cache_in_redis(ttl=cache.ONE_DAY)
def get_product_growth_periods_bulk(
    query_params: Mapping[str, Any],
    permissions: Mapping[str, Any],
) -> List[Dict]:
    query_params["is_feed_data_available"] = is_apple_spotify_data_in_sync()
    query = ProductBulkGrowthPeriods({**query_params, **permissions})
    return [format_row(data_point) for data_point in query.execute()]