"""Logic for the /participant-metrics endpoint."""

from typing import Any, Mapping

from ddtrace import tracer

from analytics.constants import cache
from analytics.queries.format import format_row
from analytics.queries.participant_metrics import (
    PARTICIPANT_METRICS_FIELDS,
    ParticipantMetrics,
)
from analytics.schemas.participants import ParticipantMetricsSchema
from analytics.utils import store_availability
from analytics.utils.cache import cache_in_redis


@cache_in_redis(ttl=cache.ONE_DAY)
@tracer.wrap(name="get_participant_metrics")
def get_participant_metrics(
    query_params: Mapping[str, Any], permissions: Mapping[str, Any]
):
    """Fetch participant metrics."""
    available_store_ids = store_availability.get_query_store_ids(
        query_params.get("store_ids") or []
    )
    if not available_store_ids:
        return ParticipantMetricsSchema.normalized_response(
            {"metrics": [], "total_participants": 0}
        )

    rows = ParticipantMetrics(
        {
            **permissions,
            **query_params,
            "store_ids": available_store_ids,
            "order_dir": (query_params.get("order_dir") or "DESC").upper(),
            "is_feed_data_available": store_availability.is_apple_spotify_data_in_sync(),
            # METRICS_BY_TRACK_PARTICIPANT_*_ROLLUP is widened by the
            # transfer-product-ownership dbt PR; rollup_grain dedups former-owner
            # rows that would otherwise inflate SUM()s post-transfer.
            "rollup_grain": True,
        }
    ).execute()

    metrics = [format_row(row) for row in rows]
    total_participants = metrics[0].pop("total_participants", 0) if metrics else 0
    for row in metrics[1:]:
        row.pop("total_participants", None)

    items = [
        {key: row[key] for key in PARTICIPANT_METRICS_FIELDS if key in row}
        for row in metrics
    ]

    return ParticipantMetricsSchema.normalized_response(
        {"metrics": items, "total_participants": total_participants}
    )