from __future__ import annotations

from datetime import datetime, time
from typing import Literal

from django.contrib.auth import get_user_model
from django.db.models import Count, Q, Sum
from django.db.models.functions import Coalesce, TruncDay, TruncMonth, TruncWeek
from django.shortcuts import get_object_or_404
from django.utils import timezone
from django.utils.dateparse import parse_date, parse_datetime
from ninja import Router
from ninja.errors import HttpError

from apps.analytics.api.schemas import (
    AdminDashboardAnalyticsSchema,
    AnalyticsEventOptionsSchema,
    BlogAnalyticsSchema,
    EventAnalyticsSchema,
    UserAnalyticsSchema,
)
from apps.blog.models import Category, Comment, Like, Post, SavedPost, Tag
from apps.events.models import Event, Registration
from apps.payments.models import Payment
from core.authentication import jwt_auth

analytics_router = Router()

UNKNOWN_LABEL = "نامشخص"
TOP_ITEMS_LIMIT = 12
PARTICIPANT_STATUSES = [
    Registration.StatusChoices.CONFIRMED,
    Registration.StatusChoices.ATTENDED,
]
GRANULARITY_TRUNC = {
    "day": TruncDay,
    "week": TruncWeek,
    "month": TruncMonth,
}
REGISTRATION_STATUS_LABELS = {
    Registration.StatusChoices.PENDING: "در انتظار",
    Registration.StatusChoices.CONFIRMED: "تایید شده",
    Registration.StatusChoices.CANCELLED: "لغو شده",
    Registration.StatusChoices.ATTENDED: "حاضر شده",
}
PAYMENT_STATUS_LABELS = {
    Payment.OrderStatusChoices.INIT: "ایجاد شده",
    Payment.OrderStatusChoices.PENDING: "در انتظار پرداخت",
    Payment.OrderStatusChoices.PAID: "پرداخت موفق",
    Payment.OrderStatusChoices.FAILED: "پرداخت ناموفق",
    Payment.OrderStatusChoices.CANCELED: "لغو شده",
}


def _parse_boundary(value: str | None, *, is_end: bool = False) -> datetime | None:
    if not value:
        return None
    parsed_datetime = parse_datetime(value)
    if parsed_datetime is None:
        parsed_date = parse_date(value)
        if parsed_date is None:
            raise HttpError(400, "Invalid date filter.")
        parsed_datetime = datetime.combine(parsed_date, time.max if is_end else time.min)
    if timezone.is_naive(parsed_datetime):
        parsed_datetime = timezone.make_aware(parsed_datetime, timezone.get_current_timezone())
    return parsed_datetime


def _apply_range(queryset, field: str, start: datetime | None, end: datetime | None):
    if start:
        queryset = queryset.filter(**{f"{field}__gte": start})
    if end:
        queryset = queryset.filter(**{f"{field}__lte": end})
    return queryset


def _auto_granularity(start: datetime | None, end: datetime | None) -> Literal["day", "week", "month"]:
    if not start or not end:
        return "month"
    days = max((end - start).days, 1)
    if days <= 45:
        return "day"
    if days <= 180:
        return "week"
    return "month"


def _label(value) -> str:
    return str(value or UNKNOWN_LABEL)


def _point_queryset(queryset, label_field: str, *, limit: int = 12):
    return [
        {"label": _label(item.get(label_field)), "value": item["value"]}
        for item in queryset.values(label_field).annotate(value=Count("id")).order_by("-value", label_field)[:limit]
    ]


def _point_group_queryset(queryset, label_field: str, *, limit: int = TOP_ITEMS_LIMIT, sum_field: str | None = None):
    if sum_field:
        rows = list(
            queryset.values(label_field)
            .annotate(value=Coalesce(Sum(sum_field), 0))
            .order_by("-value", label_field)
        )
    else:
        rows = list(
            queryset.values(label_field)
            .annotate(value=Count("id"))
            .order_by("-value", label_field)
        )
    total_count = len(rows)
    top_rows = rows[:limit]
    other_rows = rows[limit:]
    return {
        "top_items": [
            {"label": _label(item.get(label_field)), "value": int(item["value"] or 0)}
            for item in top_rows
        ],
        "other_count": len(other_rows),
        "total_count": total_count,
    }


def _trend_queryset(queryset, field: str, granularity: str):
    trunc = GRANULARITY_TRUNC[granularity]
    rows = (
        queryset.annotate(bucket=trunc(field))
        .values("bucket")
        .annotate(value=Count("id"))
        .order_by("bucket")
    )
    return [
        {
            "date": item["bucket"].date().isoformat() if item["bucket"] else "",
            "label": item["bucket"].date().isoformat() if item["bucket"] else UNKNOWN_LABEL,
            "value": item["value"],
        }
        for item in rows
    ]


def _trend_sum_queryset(queryset, field: str, sum_field: str, granularity: str):
    trunc = GRANULARITY_TRUNC[granularity]
    rows = (
        queryset.annotate(bucket=trunc(field))
        .values("bucket")
        .annotate(value=Coalesce(Sum(sum_field), 0))
        .order_by("bucket")
    )
    return [
        {
            "date": item["bucket"].date().isoformat() if item["bucket"] else "",
            "label": item["bucket"].date().isoformat() if item["bucket"] else UNKNOWN_LABEL,
            "value": int(item["value"] or 0),
        }
        for item in rows
    ]


def _sum(queryset, field: str) -> int:
    return int(queryset.aggregate(total=Coalesce(Sum(field), 0))["total"] or 0)


def _status_label(value) -> str:
    try:
        return PAYMENT_STATUS_LABELS.get(Payment.OrderStatusChoices(value), str(value))
    except ValueError:
        return str(value)


def _registration_status_label(value: str) -> str:
    try:
        return REGISTRATION_STATUS_LABELS.get(Registration.StatusChoices(value), value)
    except ValueError:
        return value


def _event_learning_hours(events_queryset) -> float:
    learning_hours = 0.0
    for event in events_queryset.annotate(
        attendees=Count(
            "registrations",
            filter=Q(registrations__is_deleted=False, registrations__status__in=PARTICIPANT_STATUSES),
            distinct=True,
        )
    ):
        duration = event.end_time - event.start_time
        learning_hours += max(duration.total_seconds(), 0) / 3600 * event.attendees
    return round(learning_hours, 1)


def _filters_payload(start: datetime | None, end: datetime | None, *, event_id: int | None = None, include_granularity: bool = False):
    payload = {
        "date_from": start.isoformat() if start else None,
        "date_to": end.isoformat() if end else None,
    }
    if event_id is not None:
        payload["event_id"] = event_id
    if include_granularity:
        payload["granularity"] = _auto_granularity(start, end)
    return payload


def _require_staff(user):
    if not (user and (user.is_staff or user.is_superuser)):
        raise HttpError(403, "اجازه دسترسی ندارید.")


@analytics_router.get("/admin/events/options", response=AnalyticsEventOptionsSchema, auth=jwt_auth)
def admin_event_options(
    request,
    search: str | None = None,
    limit: int = 20,
    offset: int = 0,
):
    _require_staff(request.auth)
    safe_limit = max(1, min(limit, 50))
    safe_offset = max(offset, 0)
    queryset = Event.objects.filter(is_deleted=False)
    if search:
        queryset = queryset.filter(Q(title__icontains=search) | Q(slug__icontains=search))
    queryset = queryset.order_by("-start_time", "-id")
    count = queryset.count()
    results = [
        {
            "value": str(event.id),
            "label": event.title,
            "description": event.start_time.date().isoformat() if event.start_time else None,
        }
        for event in queryset[safe_offset : safe_offset + safe_limit]
    ]
    return {"count": count, "results": results}


@analytics_router.get("/admin/users", response=UserAnalyticsSchema, auth=jwt_auth)
def admin_users_analytics(request, date_from: str | None = None, date_to: str | None = None):
    _require_staff(request.auth)
    start = _parse_boundary(date_from)
    end = _parse_boundary(date_to, is_end=True)
    if start and end and start > end:
        raise HttpError(400, "Start date must be before end date.")
    granularity = _auto_granularity(start, end)

    User = get_user_model()
    users_qs = _apply_range(User.objects.filter(is_deleted=False), "date_joined", start, end)
    total_users = users_qs.count()
    verified_users = users_qs.filter(is_mobile_verified=True).count()
    completed_profiles = users_qs.exclude(first_name="").exclude(last_name="").filter(
        mobile__isnull=False,
        major__isnull=False,
        university__isnull=False,
    ).count()

    return {
        "filters": _filters_payload(start, end, include_granularity=True),
        "summary": {
            "total_users": total_users,
            "verified_users": verified_users,
            "unverified_users": max(total_users - verified_users, 0),
            "profile_completion_rate": round((completed_profiles / total_users) * 100, 1) if total_users else 0,
        },
        "signup_trend": _trend_queryset(users_qs, "date_joined", granularity),
        "by_major": _point_group_queryset(users_qs, "major__name"),
        "by_university": _point_group_queryset(users_qs, "university__name"),
        "by_year": _point_group_queryset(users_qs, "year_of_study"),
    }


@analytics_router.get("/admin/events", response=EventAnalyticsSchema, auth=jwt_auth)
def admin_events_analytics(
    request,
    date_from: str | None = None,
    date_to: str | None = None,
    event_id: int | None = None,
):
    _require_staff(request.auth)
    start = _parse_boundary(date_from)
    end = _parse_boundary(date_to, is_end=True)
    if start and end and start > end:
        raise HttpError(400, "Start date must be before end date.")
    granularity = _auto_granularity(start, end)

    selected_event = None
    if event_id is not None:
        selected_event = get_object_or_404(Event, id=event_id, is_deleted=False)

    events_qs = Event.objects.filter(is_deleted=False)
    if selected_event:
        events_qs = events_qs.filter(id=selected_event.id)
    else:
        events_qs = _apply_range(events_qs, "start_time", start, end)

    registrations_qs = _apply_range(
        Registration.objects.filter(is_deleted=False).select_related("user", "event", "user__major", "user__university"),
        "registered_at",
        start,
        end,
    )
    if selected_event:
        registrations_qs = registrations_qs.filter(event_id=selected_event.id)

    participant_qs = registrations_qs.filter(status__in=PARTICIPANT_STATUSES)
    paid_payments_qs = Payment.objects.filter(is_deleted=False, status=Payment.OrderStatusChoices.PAID, verified_at__isnull=False)
    paid_payments_qs = _apply_range(paid_payments_qs.select_related("event"), "verified_at", start, end)
    all_payments_qs = _apply_range(Payment.objects.filter(is_deleted=False), "created_at", start, end)
    if selected_event:
        paid_payments_qs = paid_payments_qs.filter(event_id=selected_event.id)
        all_payments_qs = all_payments_qs.filter(event_id=selected_event.id)

    registration_status = [
        {"status": item["status"], "label": _registration_status_label(item["status"]), "value": item["value"]}
        for item in registrations_qs.values("status").annotate(value=Count("id")).order_by("status")
    ]
    payment_status = [
        {"status": str(item["status"]), "label": _status_label(item["status"]), "value": item["value"]}
        for item in all_payments_qs.values("status").annotate(value=Count("id")).order_by("status")
    ]

    top_events_qs = Event.objects.filter(is_deleted=False)
    if selected_event:
        top_events_qs = top_events_qs.filter(id=selected_event.id)
    top_events_annotated = list(
        top_events_qs.annotate(
            attendees=Count(
                "registrations",
                filter=Q(registrations__is_deleted=False, registrations__status__in=PARTICIPANT_STATUSES),
                distinct=True,
            ),
            revenue=Coalesce(
                Sum(
                    "payments__amount",
                    filter=Q(payments__is_deleted=False, payments__status=Payment.OrderStatusChoices.PAID),
                ),
                0,
            ),
        ).order_by("-attendees", "-revenue", "-start_time")
    )
    top_events = []
    for event in top_events_annotated[:TOP_ITEMS_LIMIT]:
        fill_rate = round((event.attendees / event.capacity) * 100, 1) if event.capacity else None
        top_events.append(
            {
                "id": event.id,
                "title": event.title,
                "slug": event.slug,
                "attendees": event.attendees,
                "capacity": event.capacity,
                "fill_rate": fill_rate,
                "revenue": int(event.revenue or 0),
            }
        )

    total_revenue = _sum(paid_payments_qs, "amount")
    total_discount = _sum(paid_payments_qs, "discount_amount")
    total_base = _sum(paid_payments_qs, "base_amount")

    return {
        "filters": _filters_payload(start, end, event_id=event_id),
        "summary": {
            "total_events": events_qs.count(),
            "total_registrations": registrations_qs.count(),
            "distinct_participants": participant_qs.values("user_id").distinct().count(),
            "total_revenue": total_revenue,
            "total_discount": total_discount,
            "total_base": total_base,
            "learning_hours": _event_learning_hours(events_qs),
        },
        "registration_status": registration_status,
        "payment_status": payment_status,
        "attendee_by_major": _point_group_queryset(participant_qs, "user__major__name"),
        "attendee_by_university": _point_group_queryset(participant_qs, "user__university__name"),
        "registration_trend": _trend_queryset(registrations_qs, "registered_at", granularity),
        "revenue_trend": _trend_sum_queryset(paid_payments_qs, "verified_at", "amount", granularity),
        "revenue_by_event": _point_group_queryset(paid_payments_qs, "event__title", sum_field="amount"),
        "top_events": {
            "top_items": top_events,
            "other_count": max(len(top_events_annotated) - TOP_ITEMS_LIMIT, 0),
            "total_count": len(top_events_annotated),
        },
    }


@analytics_router.get("/admin/blog", response=BlogAnalyticsSchema, auth=jwt_auth)
def admin_blog_analytics(request, date_from: str | None = None, date_to: str | None = None):
    _require_staff(request.auth)
    start = _parse_boundary(date_from)
    end = _parse_boundary(date_to, is_end=True)
    if start and end and start > end:
        raise HttpError(400, "Start date must be before end date.")
    granularity = _auto_granularity(start, end)

    published_posts_qs = _apply_range(
        Post.objects.filter(is_deleted=False, status=Post.StatusChoices.PUBLISHED),
        "published_at",
        start,
        end,
    )
    visible_comments_qs = _apply_range(
        Comment.objects.filter(
            is_deleted=False,
            is_hidden=False,
            is_approved=True,
            post__is_deleted=False,
            post__status=Post.StatusChoices.PUBLISHED,
        ),
        "created_at",
        start,
        end,
    )
    likes_qs = _apply_range(
        Like.objects.filter(post__is_deleted=False, post__status=Post.StatusChoices.PUBLISHED),
        "created_at",
        start,
        end,
    )
    saves_qs = _apply_range(
        SavedPost.objects.filter(post__is_deleted=False, post__status=Post.StatusChoices.PUBLISHED),
        "created_at",
        start,
        end,
    )

    like_filter = Q()
    save_filter = Q()
    comment_filter = Q(comments__is_deleted=False, comments__is_hidden=False, comments__is_approved=True)
    if start:
        like_filter &= Q(likes__created_at__gte=start)
        save_filter &= Q(saves__created_at__gte=start)
        comment_filter &= Q(comments__created_at__gte=start)
    if end:
        like_filter &= Q(likes__created_at__lte=end)
        save_filter &= Q(saves__created_at__lte=end)
        comment_filter &= Q(comments__created_at__lte=end)

    post_popularity_all = list(
        Post.objects.filter(is_deleted=False, status=Post.StatusChoices.PUBLISHED)
        .annotate(
            likes_total=Count("likes", filter=like_filter, distinct=True),
            saves_total=Count("saves", filter=save_filter, distinct=True),
            comments_total=Count("comments", filter=comment_filter, distinct=True),
        )
        .filter(Q(likes_total__gt=0) | Q(saves_total__gt=0) | Q(comments_total__gt=0))
        .order_by("-likes_total", "-saves_total", "-comments_total", "-published_at")
    )
    post_popularity = [
        {
            "id": post.id,
            "title": post.title,
            "slug": post.slug,
            "likes": post.likes_total,
            "saves": post.saves_total,
            "comments": post.comments_total,
        }
        for post in post_popularity_all[:TOP_ITEMS_LIMIT]
    ]
    top_posts = [
        {
            **post,
            "score": post["likes"] + post["saves"] + post["comments"],
        }
        for post in sorted(post_popularity, key=lambda item: item["likes"] + item["saves"] + item["comments"], reverse=True)
    ]

    activity_buckets: dict[str, dict[str, int | str]] = {}
    for key, qs in (("likes", likes_qs), ("saves", saves_qs), ("comments", visible_comments_qs)):
        for item in (
            qs.annotate(bucket=GRANULARITY_TRUNC[granularity]("created_at"))
            .values("bucket")
            .annotate(value=Count("id"))
            .order_by("bucket")
        ):
            bucket = item["bucket"].date().isoformat() if item["bucket"] else UNKNOWN_LABEL
            activity_buckets.setdefault(bucket, {"date": bucket, "likes": 0, "saves": 0, "comments": 0})
            activity_buckets[bucket][key] = item["value"]

    total_likes = likes_qs.count()
    total_saves = saves_qs.count()
    total_comments = visible_comments_qs.count()

    return {
        "filters": _filters_payload(start, end),
        "summary": {
            "published_posts": published_posts_qs.count(),
            "total_likes": total_likes,
            "total_saves": total_saves,
            "total_comments": total_comments,
            "community_engagement": total_likes + total_saves + total_comments,
        },
        "activity_trend": list(activity_buckets.values()),
        "post_popularity": {
            "top_items": post_popularity,
            "other_count": max(len(post_popularity_all) - TOP_ITEMS_LIMIT, 0),
            "total_count": len(post_popularity_all),
        },
        "top_posts": top_posts,
        "by_category": _point_group_queryset(published_posts_qs, "category__name"),
        "by_tag": _point_group_queryset(published_posts_qs.filter(tags__is_deleted=False), "tags__name"),
    }


@analytics_router.get("/admin/dashboard", response=AdminDashboardAnalyticsSchema, auth=jwt_auth)
def admin_dashboard(
    request,
    date_from: str | None = None,
    date_to: str | None = None,
    event_id: int | None = None,
    granularity: Literal["day", "week", "month", "auto"] = "auto",
):
    user = request.auth
    if not (user and (user.is_staff or user.is_superuser)):
        raise HttpError(403, "اجازه دسترسی ندارید.")

    start = _parse_boundary(date_from)
    end = _parse_boundary(date_to, is_end=True)
    if start and end and start > end:
        raise HttpError(400, "Start date must be before end date.")
    selected_granularity = _auto_granularity(start, end) if granularity == "auto" else granularity

    if event_id is not None:
        get_object_or_404(Event, id=event_id, is_deleted=False)

    User = get_user_model()
    users_qs = _apply_range(User.objects.filter(is_deleted=False), "date_joined", start, end)
    events_qs = _apply_range(Event.objects.filter(is_deleted=False), "start_time", start, end)
    registrations_qs = _apply_range(
        Registration.objects.filter(is_deleted=False).select_related("user", "event", "user__major", "user__university"),
        "registered_at",
        start,
        end,
    )
    if event_id is not None:
        registrations_qs = registrations_qs.filter(event_id=event_id)

    paid_payments_qs = Payment.objects.filter(is_deleted=False, status=Payment.OrderStatusChoices.PAID, verified_at__isnull=False)
    paid_payments_qs = _apply_range(paid_payments_qs.select_related("event"), "verified_at", start, end)
    all_payments_qs = _apply_range(Payment.objects.filter(is_deleted=False), "created_at", start, end)
    if event_id is not None:
        paid_payments_qs = paid_payments_qs.filter(event_id=event_id)
        all_payments_qs = all_payments_qs.filter(event_id=event_id)

    published_posts_qs = _apply_range(
        Post.objects.filter(is_deleted=False, status=Post.StatusChoices.PUBLISHED),
        "published_at",
        start,
        end,
    )
    visible_comments_qs = _apply_range(
        Comment.objects.filter(
            is_deleted=False,
            is_hidden=False,
            is_approved=True,
            post__is_deleted=False,
            post__status=Post.StatusChoices.PUBLISHED,
        ),
        "created_at",
        start,
        end,
    )
    likes_qs = _apply_range(
        Like.objects.filter(post__is_deleted=False, post__status=Post.StatusChoices.PUBLISHED),
        "created_at",
        start,
        end,
    )
    saves_qs = _apply_range(
        SavedPost.objects.filter(post__is_deleted=False, post__status=Post.StatusChoices.PUBLISHED),
        "created_at",
        start,
        end,
    )

    participant_qs = registrations_qs.filter(status__in=PARTICIPANT_STATUSES)
    registration_status = [
        {"status": item["status"], "label": _registration_status_label(item["status"]), "value": item["value"]}
        for item in registrations_qs.values("status").annotate(value=Count("id")).order_by("status")
    ]
    payment_status = [
        {"status": str(item["status"]), "label": _status_label(item["status"]), "value": item["value"]}
        for item in all_payments_qs.values("status").annotate(value=Count("id")).order_by("status")
    ]

    top_events_qs = Event.objects.filter(is_deleted=False)
    if event_id is not None:
        top_events_qs = top_events_qs.filter(id=event_id)
    top_events = []
    for event in (
        top_events_qs.annotate(
            attendees=Count(
                "registrations",
                filter=Q(registrations__is_deleted=False, registrations__status__in=PARTICIPANT_STATUSES),
                distinct=True,
            ),
            revenue=Coalesce(
                Sum(
                    "payments__amount",
                    filter=Q(payments__is_deleted=False, payments__status=Payment.OrderStatusChoices.PAID),
                ),
                0,
            ),
        )
        .order_by("-attendees", "-revenue", "-start_time")[:10]
    ):
        fill_rate = round((event.attendees / event.capacity) * 100, 1) if event.capacity else None
        top_events.append(
            {
                "id": event.id,
                "title": event.title,
                "slug": event.slug,
                "attendees": event.attendees,
                "capacity": event.capacity,
                "fill_rate": fill_rate,
                "revenue": int(event.revenue or 0),
            }
        )

    revenue_trend = [
        {
            "date": item["bucket"].date().isoformat() if item["bucket"] else "",
            "label": item["bucket"].date().isoformat() if item["bucket"] else UNKNOWN_LABEL,
            "value": int(item["value"] or 0),
        }
        for item in (
            paid_payments_qs.annotate(bucket=GRANULARITY_TRUNC[selected_granularity]("verified_at"))
            .values("bucket")
            .annotate(value=Coalesce(Sum("amount"), 0))
            .order_by("bucket")
        )
    ]

    revenue_by_event = [
        {"label": _label(item["event__title"]), "value": int(item["value"] or 0)}
        for item in (
            paid_payments_qs.values("event__title")
            .annotate(value=Coalesce(Sum("amount"), 0))
            .order_by("-value", "event__title")[:10]
        )
    ]

    post_popularity_qs = (
        Post.objects.filter(is_deleted=False, status=Post.StatusChoices.PUBLISHED)
        .annotate(
            likes_total=Count("likes", distinct=True),
            saves_total=Count("saves", distinct=True),
            comments_total=Count(
                "comments",
                filter=Q(comments__is_deleted=False, comments__is_hidden=False, comments__is_approved=True),
                distinct=True,
            ),
        )
        .order_by("-likes_total", "-saves_total", "-comments_total")[:30]
    )
    post_popularity = [
        {
            "id": post.id,
            "title": post.title,
            "slug": post.slug,
            "likes": post.likes_total,
            "saves": post.saves_total,
            "comments": post.comments_total,
        }
        for post in post_popularity_qs
    ]
    top_posts = [
        {
            **post,
            "score": post["likes"] + post["saves"] + post["comments"],
        }
        for post in sorted(post_popularity, key=lambda item: item["likes"] + item["saves"] + item["comments"], reverse=True)[:10]
    ]

    activity_buckets: dict[str, dict[str, int | str]] = {}
    for key, qs in (("likes", likes_qs), ("saves", saves_qs), ("comments", visible_comments_qs)):
        for item in (
            qs.annotate(bucket=GRANULARITY_TRUNC[selected_granularity]("created_at"))
            .values("bucket")
            .annotate(value=Count("id"))
            .order_by("bucket")
        ):
            bucket = item["bucket"].date().isoformat() if item["bucket"] else UNKNOWN_LABEL
            activity_buckets.setdefault(bucket, {"date": bucket, "likes": 0, "saves": 0, "comments": 0})
            activity_buckets[bucket][key] = item["value"]

    category_engagement = [
        {"label": _label(item["name"]), "value": item["value"]}
        for item in (
            Category.objects.filter(is_deleted=False, posts__status=Post.StatusChoices.PUBLISHED, posts__is_deleted=False)
            .annotate(value=Count("posts", distinct=True))
            .order_by("-value", "name")[:10]
            .values("name", "value")
        )
    ]
    tag_engagement = [
        {"label": _label(item["name"]), "value": item["value"]}
        for item in (
            Tag.objects.filter(is_deleted=False, posts__status=Post.StatusChoices.PUBLISHED, posts__is_deleted=False)
            .annotate(value=Count("posts", distinct=True))
            .order_by("-value", "name")[:10]
            .values("name", "value")
        )
    ]

    learning_hours = 0.0
    for event in Event.objects.filter(is_deleted=False).annotate(
        attendees=Count(
            "registrations",
            filter=Q(registrations__is_deleted=False, registrations__status__in=PARTICIPANT_STATUSES),
            distinct=True,
        )
    ):
        duration = event.end_time - event.start_time
        learning_hours += max(duration.total_seconds(), 0) / 3600 * event.attendees

    total_revenue = _sum(paid_payments_qs, "amount")
    total_discount = _sum(paid_payments_qs, "discount_amount")
    total_base = _sum(paid_payments_qs, "base_amount")
    total_likes = likes_qs.count()
    total_saves = saves_qs.count()
    total_comments = visible_comments_qs.count()
    published_posts_count = published_posts_qs.count()

    return {
        "filters": {
            "date_from": start.isoformat() if start else None,
            "date_to": end.isoformat() if end else None,
            "event_id": event_id,
            "granularity": selected_granularity,
        },
        "summary": {
            "total_users": users_qs.count(),
            "verified_users": users_qs.filter(is_mobile_verified=True).count(),
            "total_events": events_qs.count(),
            "total_registrations": registrations_qs.count(),
            "total_revenue": total_revenue,
            "total_discount": total_discount,
            "published_posts": published_posts_count,
            "total_likes": total_likes,
            "total_saves": total_saves,
            "total_comments": total_comments,
        },
        "users": {
            "signup_trend": _trend_queryset(users_qs, "date_joined", selected_granularity),
            "by_major": _point_queryset(users_qs, "major__name"),
            "by_university": _point_queryset(users_qs, "university__name"),
            "by_year": _point_queryset(users_qs, "year_of_study"),
        },
        "events": {
            "registration_status": registration_status,
            "by_major": _point_queryset(participant_qs, "user__major__name"),
            "by_university": _point_queryset(participant_qs, "user__university__name"),
            "top_events": top_events,
            "registration_trend": _trend_queryset(registrations_qs, "registered_at", selected_granularity),
        },
        "revenue": {
            "trend": revenue_trend,
            "by_event": revenue_by_event,
            "payment_status": payment_status,
            "total_paid": total_revenue,
            "total_discount": total_discount,
            "total_base": total_base,
        },
        "blog": {
            "totals": {
                "posts": published_posts_count,
                "likes": total_likes,
                "saves": total_saves,
                "comments": total_comments,
            },
            "post_popularity": post_popularity,
            "top_posts": top_posts,
            "activity_trend": list(activity_buckets.values()),
            "by_category": category_engagement,
            "by_tag": tag_engagement,
        },
        "achievements": {
            "distinct_participants": participant_qs.values("user_id").distinct().count(),
            "learning_hours": round(learning_hours, 1),
            "published_content": published_posts_count,
            "community_engagement": total_likes + total_saves + total_comments,
        },
    }