thrillwiki_django_no_react/core/selectors.py

"""
Selectors for core functionality including map services and analytics.
Following Django styleguide pattern for separating data access from business logic.
"""

from typing import Optional, Dict, Any, List
from django.db.models import QuerySet, Q, Count
from django.contrib.gis.geos import Point, Polygon
from django.contrib.gis.measure import Distance
from django.utils import timezone
from datetime import timedelta

from .analytics import PageView
from parks.models import Park
from rides.models import Ride


def unified_locations_for_map(
    *,
    bounds: Optional[Polygon] = None,
    location_types: Optional[List[str]] = None,
    filters: Optional[Dict[str, Any]] = None,
) -> Dict[str, QuerySet]:
    """
    Get unified location data for map display across all location types.

    Args:
        bounds: Geographic boundary polygon
        location_types: List of location types to include ('park', 'ride')
        filters: Additional filter parameters

    Returns:
        Dictionary containing querysets for each location type
    """
    results = {}

    # Default to all location types if none specified
    if not location_types:
        location_types = ["park", "ride"]

    # Parks
    if "park" in location_types:
        park_queryset = (
            Park.objects.select_related("operator")
            .prefetch_related("location")
            .annotate(ride_count_calculated=Count("rides"))
        )

        if bounds:
            park_queryset = park_queryset.filter(location__coordinates__within=bounds)

        if filters:
            if "status" in filters:
                park_queryset = park_queryset.filter(status=filters["status"])
            if "operator" in filters:
                park_queryset = park_queryset.filter(operator=filters["operator"])

        results["parks"] = park_queryset.order_by("name")

    # Rides
    if "ride" in location_types:
        ride_queryset = Ride.objects.select_related(
            "park", "manufacturer"
        ).prefetch_related("park__location", "location")

        if bounds:
            ride_queryset = ride_queryset.filter(
                Q(location__coordinates__within=bounds)
                | Q(park__location__coordinates__within=bounds)
            )

        if filters:
            if "category" in filters:
                ride_queryset = ride_queryset.filter(category=filters["category"])
            if "manufacturer" in filters:
                ride_queryset = ride_queryset.filter(
                    manufacturer=filters["manufacturer"]
                )
            if "park" in filters:
                ride_queryset = ride_queryset.filter(park=filters["park"])

        results["rides"] = ride_queryset.order_by("park__name", "name")

    return results


def locations_near_point(
    *,
    point: Point,
    distance_km: float = 50,
    location_types: Optional[List[str]] = None,
    limit: int = 20,
) -> Dict[str, QuerySet]:
    """
    Get locations near a specific geographic point across all types.

    Args:
        point: Geographic point (longitude, latitude)
        distance_km: Maximum distance in kilometers
        location_types: List of location types to include
        limit: Maximum number of results per type

    Returns:
        Dictionary containing nearby locations by type
    """
    results = {}

    if not location_types:
        location_types = ["park", "ride"]

    # Parks near point
    if "park" in location_types:
        results["parks"] = (
            Park.objects.filter(
                location__coordinates__distance_lte=(
                    point,
                    Distance(km=distance_km),
                )
            )
            .select_related("operator")
            .prefetch_related("location")
            .distance(point)
            .order_by("distance")[:limit]
        )

    # Rides near point
    if "ride" in location_types:
        results["rides"] = (
            Ride.objects.filter(
                Q(
                    location__coordinates__distance_lte=(
                        point,
                        Distance(km=distance_km),
                    )
                )
                | Q(
                    park__location__coordinates__distance_lte=(
                        point,
                        Distance(km=distance_km),
                    )
                )
            )
            .select_related("park", "manufacturer")
            .prefetch_related("park__location")
            .distance(point)
            .order_by("distance")[:limit]
        )

    return results


def search_all_locations(*, query: str, limit: int = 20) -> Dict[str, QuerySet]:
    """
    Search across all location types for a query string.

    Args:
        query: Search string
        limit: Maximum results per type

    Returns:
        Dictionary containing search results by type
    """
    results = {}

    # Search parks
    results["parks"] = (
        Park.objects.filter(
            Q(name__icontains=query)
            | Q(description__icontains=query)
            | Q(location__city__icontains=query)
            | Q(location__region__icontains=query)
        )
        .select_related("operator")
        .prefetch_related("location")
        .order_by("name")[:limit]
    )

    # Search rides
    results["rides"] = (
        Ride.objects.filter(
            Q(name__icontains=query)
            | Q(description__icontains=query)
            | Q(park__name__icontains=query)
            | Q(manufacturer__name__icontains=query)
        )
        .select_related("park", "manufacturer")
        .prefetch_related("park__location")
        .order_by("park__name", "name")[:limit]
    )

    return results


def page_views_for_analytics(
    *,
    start_date: Optional[timezone.datetime] = None,
    end_date: Optional[timezone.datetime] = None,
    path_pattern: Optional[str] = None,
) -> QuerySet[PageView]:
    """
    Get page views for analytics with optional filtering.

    Args:
        start_date: Start date for filtering
        end_date: End date for filtering
        path_pattern: URL path pattern to filter by

    Returns:
        QuerySet of page views
    """
    queryset = PageView.objects.all()

    if start_date:
        queryset = queryset.filter(timestamp__gte=start_date)

    if end_date:
        queryset = queryset.filter(timestamp__lte=end_date)

    if path_pattern:
        queryset = queryset.filter(path__icontains=path_pattern)

    return queryset.order_by("-timestamp")


def popular_pages_summary(*, days: int = 30) -> Dict[str, Any]:
    """
    Get summary of most popular pages in the last N days.

    Args:
        days: Number of days to analyze

    Returns:
        Dictionary containing popular pages statistics
    """
    cutoff_date = timezone.now() - timedelta(days=days)

    # Most viewed pages
    popular_pages = (
        PageView.objects.filter(timestamp__gte=cutoff_date)
        .values("path")
        .annotate(view_count=Count("id"))
        .order_by("-view_count")[:10]
    )

    # Total page views
    total_views = PageView.objects.filter(timestamp__gte=cutoff_date).count()

    # Unique visitors (based on IP)
    unique_visitors = (
        PageView.objects.filter(timestamp__gte=cutoff_date)
        .values("ip_address")
        .distinct()
        .count()
    )

    return {
        "popular_pages": list(popular_pages),
        "total_views": total_views,
        "unique_visitors": unique_visitors,
        "period_days": days,
    }


def geographic_distribution_summary() -> Dict[str, Any]:
    """
    Get geographic distribution statistics for all locations.

    Returns:
        Dictionary containing geographic statistics
    """
    # Parks by country
    parks_by_country = (
        Park.objects.filter(location__country__isnull=False)
        .values("location__country")
        .annotate(count=Count("id"))
        .order_by("-count")
    )

    # Rides by country (through park location)
    rides_by_country = (
        Ride.objects.filter(park__location__country__isnull=False)
        .values("park__location__country")
        .annotate(count=Count("id"))
        .order_by("-count")
    )

    return {
        "parks_by_country": list(parks_by_country),
        "rides_by_country": list(rides_by_country),
    }


def system_health_metrics() -> Dict[str, Any]:
    """
    Get system health and activity metrics.

    Returns:
        Dictionary containing system health statistics
    """
    now = timezone.now()
    last_24h = now - timedelta(hours=24)
    last_7d = now - timedelta(days=7)

    return {
        "total_parks": Park.objects.count(),
        "operating_parks": Park.objects.filter(status="OPERATING").count(),
        "total_rides": Ride.objects.count(),
        "page_views_24h": PageView.objects.filter(timestamp__gte=last_24h).count(),
        "page_views_7d": PageView.objects.filter(timestamp__gte=last_7d).count(),
        "data_freshness": {
            "latest_park_update": (
                Park.objects.order_by("-updated_at").first().updated_at
                if Park.objects.exists()
                else None
            ),
            "latest_ride_update": (
                Ride.objects.order_by("-updated_at").first().updated_at
                if Ride.objects.exists()
                else None
            ),
        },
    }