from __future__ import annotations

import urllib.parse
from collections import Counter
from typing import Any

from .evidence import make_evidence
from .geometry import EARTH_RADIUS_M
from .http_client import post_text
from .models import EvidenceItem, SiteSelection

OVERPASS_URL = "https://overpass-api.de/api/interpreter"


def fetch_osm_context(selection: SiteSelection) -> tuple[dict[str, Any], list[EvidenceItem]]:
    if selection.anchor_lat is None or selection.anchor_lon is None:
        return {"counts": {}, "features": []}, [
            make_evidence(
                category="Geographic context",
                finding="OSM context was skipped because no real-world anchor coordinate is available.",
                source_name="OpenStreetMap",
                source_url="https://www.openstreetmap.org/copyright",
                source_type="open map data",
                resolution_or_scope="not available",
                confidence="low",
                limitation="Public map data requires a real-world coordinate.",
                design_implication="Use CAD/user observations until the site is anchored.",
                verification_needed="Provide lat/lon or draw the boundary on the map.",
                output_label="site_visit_required",
            )
        ]
    radius = int(selection.radius_m or 500)
    radius = min(max(radius, 100), 1500)
    query = f"""
    [out:json][timeout:20];
    (
      way(around:{radius},{selection.anchor_lat},{selection.anchor_lon})["highway"];
      way(around:{radius},{selection.anchor_lat},{selection.anchor_lon})["building"];
      way(around:{radius},{selection.anchor_lat},{selection.anchor_lon})["natural"="water"];
      way(around:{radius},{selection.anchor_lat},{selection.anchor_lon})["waterway"];
      way(around:{radius},{selection.anchor_lat},{selection.anchor_lon})["landuse"];
      way(around:{radius},{selection.anchor_lat},{selection.anchor_lon})["leisure"="park"];
      node(around:{radius},{selection.anchor_lat},{selection.anchor_lon})["amenity"];
    );
    out tags center geom 120;
    """
    try:
        payload = post_text(OVERPASS_URL, urllib.parse.urlencode({"data": query}))
        elements = payload.get("elements") or []
        counts = _count_context(elements)
        evidence = [
            make_evidence(
                category="Geographic context",
                finding=f"OSM context found {sum(counts.values())} nearby mapped features in the selected search radius.",
                source_name="OpenStreetMap / Overpass API",
                source_url="https://www.openstreetmap.org/copyright",
                source_type="open map data",
                resolution_or_scope=f"{radius} m around anchor coordinate",
                confidence="medium" if counts else "low",
                limitation="OSM tags may be incomplete or outdated; public tile/API use requires attribution.",
                design_implication="Use mapped roads, water, green, land-use, and amenities as first-pass context only.",
                verification_needed="Verify access, road widths, vegetation, water bodies, and local activity on site.",
                output_label="public_data",
            )
        ]
        return {"counts": dict(counts), "features": elements[:80], "radius_m": radius}, evidence
    except Exception as exc:  # noqa: BLE001
        return {"counts": {}, "features": [], "radius_m": radius}, [
            make_evidence(
                category="Geographic context",
                finding="OSM context could not be retrieved.",
                source_name="OpenStreetMap / Overpass API",
                source_url="https://overpass-api.de/",
                source_type="open map data",
                resolution_or_scope=f"{radius} m around anchor coordinate",
                confidence="low",
                limitation=f"Overpass request failed: {type(exc).__name__}.",
                design_implication="Do not infer mapped context from this missing layer.",
                verification_needed="Manually verify roads, water, vegetation, access, and surrounding buildings.",
                output_label="site_visit_required",
            )
        ]


def _count_context(elements: list[dict[str, Any]]) -> Counter[str]:
    counts: Counter[str] = Counter()
    for element in elements:
        tags = element.get("tags") or {}
        if "highway" in tags:
            counts["roads/access"] += 1
        if "building" in tags:
            counts["buildings"] += 1
        if tags.get("natural") == "water" or "waterway" in tags:
            counts["water"] += 1
        if tags.get("leisure") == "park" or tags.get("landuse") in {"forest", "grass", "recreation_ground"}:
            counts["green/open space"] += 1
        if "landuse" in tags:
            counts[f"landuse:{tags['landuse']}"] += 1
        if "amenity" in tags:
            counts[f"amenity:{tags['amenity']}"] += 1
    return counts