from __future__ import annotations

from typing import Any, Dict, List, Mapping


def search_symbols_catalog(symbols: Mapping[str, Any], query: str) -> Dict[str, Any]:
    query_lower = query.lower()
    results: List[Dict[str, Any]] = []
    for symbol, config in symbols.items():
        score = 0
        if query_lower == symbol.lower():
            score = 100
        elif query_lower in symbol.lower():
            score = 80
        elif query_lower in config.label.lower():
            score = 60
        elif query_lower in config.label_en.lower():
            score = 50
        elif query_lower in config.category.lower():
            score = 30

        if score > 0:
            results.append(
                {
                    "symbol": symbol,
                    "label": config.label,
                    "label_en": config.label_en,
                    "category": config.category,
                    "score": score,
                }
            )

    results.sort(key=lambda item: -item["score"])
    return {"query": query, "count": len(results), "results": results[:20]}


def build_market_peer_candidates(
    symbols: Mapping[str, Any],
    symbol: str,
    limit: int,
) -> Dict[str, Any]:
    if symbol not in symbols:
        return {"category": "Unknown", "symbol": symbol, "peers": [], "count": 0}

    config = symbols[symbol]
    peers = [item for item in symbols.values() if item.category == config.category and item.symbol != symbol]
    if len(peers) < limit:
        fallback = [
            item
            for item in symbols.values()
            if item.symbol not in {symbol, *(peer.symbol for peer in peers)}
        ]
        peers.extend(fallback)

    return {
        "category": config.category,
        "symbol": symbol,
        "peer_configs": peers[:limit],
    }


def assemble_market_peer_payload(
    category: str,
    symbol: str,
    peer_configs: List[Any],
    peer_results: List[Any],
) -> Dict[str, Any]:
    peer_data: List[Dict[str, Any]] = []
    for peer, result in zip(peer_configs, peer_results):
        entry = {
            "symbol": peer.symbol,
            "name": peer.label,
            "description": peer.description,
            "category": peer.category,
            "price": 0.0,
            "change_24h": 0.0,
        }
        if isinstance(result, Exception):
            peer_data.append(entry)
            continue

        entry["price"] = float(result.get("price", 0.0) or 0.0)
        entry["change_24h"] = float(result.get("change_pct", result.get("change_24h", 0.0)) or 0.0)
        peer_data.append(entry)

    return {
        "category": category,
        "symbol": symbol,
        "peers": peer_data,
        "count": len(peer_data),
    }