#!/usr/bin/env python3
"""
将clothing数据的多个字段拆解后写入ES索引的tags和keyword.zh字段

字段说明:
- category_path: 按 > 分隔
- tags: 按 , 分隔
- target_audience: 按 , 分隔
- usage_scene: 按 , 分隔
- season: 按 , 分隔
- key_attributes: 按 , 分隔
- material: 按 , 分隔
- features: 按 , 分隔

ES配置:
- 索引: search_products_tenant_170
- 用户: essa
- 密码: 4hOaLaf41y2VuI8y
- 地址: http://localhost:9200
"""

import csv
import json
import sys
from elasticsearch import Elasticsearch
from collections import defaultdict

# ES配置
ES_CONFIG = {
    'host': 'localhost',
    'port': 9200,
    'user': 'essa',
    'password': '4hOaLaf41y2VuI8y',
    'index': 'search_products_tenant_170'
}

def get_es_client():
    """创建ES客户端"""
    return Elasticsearch(
        [f"http://{ES_CONFIG['host']}:{ES_CONFIG['port']}"],
        basic_auth=(ES_CONFIG['user'], ES_CONFIG['password']),
        verify_certs=False,
        ssl_show_warn=False,
        request_timeout=30,
        max_retries=3,
        retry_on_timeout=True
    )

def split_field(value, delimiter):
    """拆分字段并去重"""
    if not value or not value.strip():
        return []
    parts = [part.strip() for part in value.split(delimiter) if part.strip()]
    # 过滤掉无效值
    invalid_values = ['-', '—', 'N/A', 'NA', 'null', 'None', '无']
    parts = [part for part in parts if part not in invalid_values and len(part) > 0]

    # 去重并保持顺序
    seen = set()
    result = []
    for part in parts:
        if part not in seen:
            seen.add(part)
            result.append(part)
    return result

def read_clothing_data(file_path):
    """读取clothing数据"""
    products = []

    with open(file_path, 'r', encoding='utf-8') as f:
        # 读取第一行来检查是否有表头
        first_line = f.readline().strip()
        f.seek(0)  # 重置文件指针

        # 检查第一行是否是数据行（以数字ID开头）
        if first_line.split(',')[0].isdigit():
            # 没有表头，手动构建字段名
            fieldnames = ['id', 'title', 'title_cn', 'category_path', 'tags',
                         'target_audience', 'usage_scene', 'season',
                         'key_attributes', 'material', 'features', 'selling_points']
            reader = csv.DictReader(f, fieldnames=fieldnames)
        else:
            # 有表头，使用正常读取
            reader = csv.DictReader(f)

        for row in reader:
            # 跳过空行
            if not row or not row.get('id'):
                continue

            products.append(row)

    return products

def extract_all_tags(product):
    """从产品中提取所有标签"""
    all_tags = []

    # 1. Category Path (按 > 分隔)
    category_path = product.get('category_path', '')
    if category_path:
        category_tags = split_field(category_path, '>')
        all_tags.extend(category_tags)

    # 2. Tags (按 , 分隔)
    tags = product.get('tags', '')
    if tags:
        tag_items = split_field(tags, ',')
        all_tags.extend(tag_items)

    # 3. Target Audience (按 , 分隔)
    target_audience = product.get('target_audience', '')
    if target_audience:
        audience_items = split_field(target_audience, ',')
        all_tags.extend(audience_items)

    # 4. Usage Scene (按 , 分隔)
    usage_scene = product.get('usage_scene', '')
    if usage_scene:
        scene_items = split_field(usage_scene, ',')
        all_tags.extend(scene_items)

    # 5. Season (按 , 分隔)
    season = product.get('season', '')
    if season:
        season_items = split_field(season, ',')
        all_tags.extend(season_items)

    # 6. Key Attributes (按 , 分隔)
    key_attributes = product.get('key_attributes', '')
    if key_attributes:
        attribute_items = split_field(key_attributes, ',')
        all_tags.extend(attribute_items)

    # 7. Material (按 , 分隔)
    material = product.get('material', '')
    if material:
        material_items = split_field(material, ',')
        all_tags.extend(material_items)

    # 8. Features (按 , 分隔)
    features = product.get('features', '')
    if features:
        feature_items = split_field(features, ',')
        all_tags.extend(feature_items)

    # 去重
    seen = set()
    unique_tags = []
    for tag in all_tags:
        if tag not in seen:
            seen.add(tag)
            unique_tags.append(tag)

    return unique_tags

def build_spu_id_mapping(file_path='output_logs/products_analyzed.csv'):
    """从完整的products_analyzed.csv构建spu_id映射

    Returns:
        dict: {product_id: spu_id}
    """
    mapping = {}

    try:
        with open(file_path, 'r', encoding='utf-8') as f:
            reader = csv.DictReader(f)

            for row in reader:
                product_id = row.get('id', '').strip()

                if product_id:
                    try:
                        # 直接使用product_id作为spu_id
                        mapping[product_id] = int(product_id)
                    except ValueError:
                        continue

        print(f"✅ 从 {file_path} 构建了 {len(mapping)} 个ID映射")
        return mapping

    except FileNotFoundError:
        print(f"⚠️  警告: 找不到文件 {file_path},将直接使用clothing文件的ID")
        return {}

def update_document_by_spu_id(es, spu_id, tags):
    """通过spu_id更新文档"""
    # 首先查询文档ID
    query = {
        "size": 1,
        "_source": False,
        "query": {
            "bool": {
                "filter": [
                    {"term": {"spu_id": spu_id}},
                    {"term": {"tenant_id": "170"}}
                ]
            }
        }
    }

    try:
        response = es.search(index=ES_CONFIG['index'], body=query)

        if response['hits']['total']['value'] > 0:
            doc_id = response['hits']['hits'][0]['_id']

            # 更新文档
            update_doc = {
                "doc": {
                    "tags": tags,
                    "keyword.zh": tags
                }
            }

            es.update(index=ES_CONFIG['index'], id=doc_id, body=update_doc)
            return True, doc_id
        else:
            return False, None

    except Exception as e:
        print(f"❌ 更新失败 spu_id={spu_id}: {e}")
        return False, None

def update_elasticsearch(products, spu_id_mapping=None):
    """批量更新ES"""
    es = get_es_client()

    print(f"📤 准备更新 {len(products)} 条文档到ES索引: {ES_CONFIG['index']}")

    success_count = 0
    failed_count = 0
    not_found_count = 0

    # 统计信息
    stats = {
        'total': len(products),
        'success': 0,
        'failed': 0,
        'not_found': 0
    }

    for i, product in enumerate(products):
        product_id = product.get('id', '').strip()

        if not product_id:
            continue

        # 提取所有标签
        all_tags = extract_all_tags(product)

        # 确定spu_id
        if spu_id_mapping and product_id in spu_id_mapping:
            spu_id = spu_id_mapping[product_id]
        else:
            try:
                spu_id = int(product_id)
            except ValueError:
                print(f"⚠️  跳过无效的product_id: {product_id}")
                continue

        # 更新文档
        success, doc_id = update_document_by_spu_id(es, spu_id, all_tags)

        if success:
            stats['success'] += 1
            if (stats['success'] % 100 == 0) or (stats['success'] == 1):
                print(f"   进度: {stats['success']}/{stats['total']} (spu_id={spu_id})")
        else:
            stats['not_found'] += 1
            if stats['not_found'] <= 5:  # 只打印前5个
                print(f"   ⚠️  未找到文档: spu_id={spu_id}")

    print(f"\n✅ 更新完成统计:")
    print(f"   总数: {stats['total']}")
    print(f"   成功: {stats['success']}")
    print(f"   未找到: {stats['not_found']}")
    print(f"   失败: {stats['failed']}")

    return stats

def verify_updates(sample_size=10):
    """验证更新结果"""
    es = get_es_client()

    print(f"\n🔍 验证更新结果 (随机抽查 {sample_size} 条)...")
    print("-" * 80)

    # 随机查询几条数据验证
    query = {
        "size": sample_size,
        "_source": ["spu_id", "tags", "keyword.zh"],
        "query": {
            "bool": {
                "must": [
                    {"exists": {"field": "tags"}},
                    {"term": {"tenant_id": "170"}}
                ]
            }
        }
    }

    try:
        response = es.search(index=ES_CONFIG['index'], body=query)

        if response['hits']['total']['value'] == 0:
            print("⚠️  没有找到任何包含tags的文档")
            return

        for hit in response['hits']['hits']:
            source = hit['_source']
            print(f"\nSPU_ID: {source.get('spu_id', 'N/A')}")
            print(f"Tags数量: {len(source.get('tags', []))}")
            print(f"Keyword.zh数量: {len(source.get('keyword.zh', []))}")
            if source.get('tags'):
                print(f"Tags示例: {source['tags'][:5]}...")

        print("\n✅ 验证完成!")

    except Exception as e:
        print(f"❌ 验证失败: {e}")

def test_connection():
    """测试ES连接"""
    es = get_es_client()

    print("🔗 测试ES连接...")
    try:
        # 测试连接
        info = es.info()
        print(f"✅ ES连接成功!")
        print(f"   版本: {info['version']['number']}")

        # 测试索引是否存在
        if es.indices.exists(index=ES_CONFIG['index']):
            print(f"✅ 索引 {ES_CONFIG['index']} 存在")

            # 获取文档数量
            count = es.count(index=ES_CONFIG['index'])['count']
            print(f"   文档总数: {count:,}")
        else:
            print(f"❌ 索引 {ES_CONFIG['index']} 不存在")
            return False

        return True

    except Exception as e:
        print(f"❌ ES连接失败: {e}")
        return False

def main():
    input_file = 'output_logs/products_analyzed.csv.clothing'

    print("=" * 80)
    print("📦 将Clothing数据字段写入ES索引")
    print("=" * 80)
    print()

    # 0. 测试ES连接
    if not test_connection():
        print("\n❌ 无法连接到ES,退出")
        return

    # 1. 读取clothing数据
    print(f"\n📂 读取Clothing数据: {input_file}")
    products = read_clothing_data(input_file)
    print(f"✅ 读取了 {len(products)} 条产品数据")

    if not products:
        print("❌ 没有读取到产品数据,退出")
        return

    # 2. 构建spu_id映射
    print("\n🔗 构建SPU_ID映射...")
    spu_id_mapping = build_spu_id_mapping()

    # 显示示例
    print(f"\n📋 数据示例 (第1条):")
    if products:
        example_product = products[0]
        example_tags = extract_all_tags(example_product)
        print(f"   Product ID: {example_product.get('id')}")
        print(f"   Category Path: {example_product.get('category_path', 'N/A')}")
        print(f"   Tags: {example_product.get('tags', 'N/A')}")
        print(f"   提取的标签数量: {len(example_tags)}")
        print(f"   标签示例: {example_tags[:10]}")

    # 3. 确认
    print(f"\n⚠️  准备更新 {len(products)} 条文档到ES索引")
    confirm = input("是否继续? (yes/no): ").strip().lower()

    if confirm not in ['yes', 'y']:
        print("❌ 取消更新")
        return

    # 4. 执行更新
    print("\n🚀 开始更新ES...")
    stats = update_elasticsearch(products, spu_id_mapping)

    # 5. 验证
    if stats['success'] > 0:
        verify = input("\n是否验证更新结果? (yes/no): ").strip().lower()
        if verify in ['yes', 'y']:
            verify_updates()

    print("\n" + "=" * 80)
    print("✅ 处理完成!")
    print("=" * 80)

if __name__ == '__main__':
    try:
        main()
    except KeyboardInterrupt:
        print("\n\n❌ 用户中断")
        sys.exit(1)
    except Exception as e:
        print(f"\n❌ 错误: {e}")
        import traceback
        traceback.print_exc()
        sys.exit(1)