"""Fetch restaurant data from Dianping (大众点评)."""

import time
import random
from typing import List, Dict, Optional
from dataclasses import dataclass
import requests
from bs4 import BeautifulSoup


@dataclass
class DianpingRestaurant:
    """Restaurant data from Dianping."""
    name: str
    rating: float
    review_count: int
    price_range: str
    address: str
    tags: List[str]
    url: str


class DianpingFetcher:
    """Fetch restaurant data from Dianping."""

    def __init__(self, config: Dict):
        self.config = config
        self.base_url = "https://www.dianping.com"
        self.session = requests.Session()
        self._setup_headers()

    def _setup_headers(self):
        """Setup request headers to mimic browser."""
        user_agents = [
            'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36',
            'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36',
        ]
        self.session.headers.update({
            'User-Agent': random.choice(user_agents),
            'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
            'Accept-Language': 'zh-CN,zh;q=0.9,en;q=0.8',
        })

    def search(self, location: str, cuisine: str, min_rating: float = 4.0) -> List[DianpingRestaurant]:
        """
        Search for restaurants by location and cuisine.

        Args:
            location: Geographic area (e.g., "上海静安区")
            cuisine: Cuisine type (e.g., "日式料理")
            min_rating: Minimum rating to include

        Returns:
            List of DianpingRestaurant objects
        """
        # Note: This is a simplified implementation
        # Actual implementation needs to handle:
        # - Dynamic content (JavaScript rendering)
        # - Anti-scraping measures
        # - Pagination
        # - Rate limiting

        search_query = f"{location} {cuisine}"
        print(f"🔍 Searching Dianping for: {search_query}")

        # Simulated data for demonstration
        # In production, this would scrape actual Dianping pages
        restaurants = self._fetch_mock_data(location, cuisine)

        # Filter by rating
        filtered = [r for r in restaurants if r.rating >= min_rating]

        # Rate limiting
        time.sleep(self.config.get('dianping_delay', 2))

        return filtered

    def _fetch_mock_data(self, location: str, cuisine: str) -> List[DianpingRestaurant]:
        """Generate mock data for testing (replace with actual scraping)."""
        mock_data = [
            DianpingRestaurant(
                name=f"{cuisine}店A",
                rating=4.8,
                review_count=2300,
                price_range="¥200-300",
                address=f"{location}某某路123号",
                tags=["美味", "环境好", "服务热情"],
                url=f"{self.base_url}/shop/12345"
            ),
            DianpingRestaurant(
                name=f"{cuisine}店B",
                rating=4.5,
                review_count=856,
                price_range="¥150-200",
                address=f"{location}某某路456号",
                tags=["性价比高", "分量足"],
                url=f"{self.base_url}/shop/67890"
            ),
        ]
        return mock_data

    def _get_search_url(self, location: str, cuisine: str) -> str:
        """Construct search URL."""
        # Simplified URL construction
        # Actual implementation would encode parameters properly
        return f"{self.base_url}/search/keyword/{cuisine}/region/{location}"


def fetch_dianping(location: str, cuisine: str, config: Dict) -> List[DianpingRestaurant]:
    """Convenience function to fetch Dianping data."""
    fetcher = DianpingFetcher(config)
    return fetcher.search(location, cuisine)