import requests
import json
import re
import time
import os
import pandas as pd
from concurrent.futures import ThreadPoolExecutor, as_completed
from requests.adapters import HTTPAdapter
import threading

# ================= 配置区域 =================
BASE_URL = "http://111.198.24.44:88/index.php"
USERNAME = "TEST"
PASSWORD = "test"  # <--- 请在此填入真实密码

# --- 调试配置 ---
# True: 开启调试模式，只处理前 200 条
# False: 关闭调试模式，跑全量
DEBUG_MODE = False
DEBUG_LIMIT = 200

# --- 并发配置 ---
MAX_WORKERS = 10

# --- 文件配置 ---
TEMPLATE_FILE = "产品-导入模板.csv"
OUTPUT_FILE = "最终导出数据_含供应商厂家.xlsx"

# ===========================================

# 统计计数器
STATS = {
    "total_processed": 0,
    "skipped_no_id": 0,
    "skipped_has_sales": 0,  # 销量不为0
    "skipped_has_relations": 0,  # 关联 Key (36/37/325/523/561) 任意一个不为0
    "skipped_has_history": 0,  # 【恢复】有仓库历史记录
    "skipped_api_error": 0,
    "success": 0
}
STATS_LOCK = threading.Lock()


class CRMFetcher:
    def __init__(self):
        self.session = requests.Session()
        # 优化连接池，防止高并发报错
        adapter = HTTPAdapter(pool_connections=MAX_WORKERS, pool_maxsize=MAX_WORKERS)
        self.session.mount('http://', adapter)
        self.headers = {
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
            "X-Requested-With": "XMLHttpRequest"
        }

    def login(self):
        print("[*] 正在登录系统...")
        try:
            payload = {
                "module": "Users", "action": "Authenticate", "return_module": "Users",
                "return_action": "Login", "user_name": USERNAME, "user_password": PASSWORD,
                "login_theme": "newskin"
            }
            resp = self.session.post(BASE_URL, data=payload, headers=self.headers)
            if "logout" in resp.text.lower() or "退出" in resp.text:
                print("[+] 登录成功！")
                return True
            else:
                print(f"[-] 登录失败: {resp.status_code}")
                return False
        except Exception as e:
            print(f"[-] 登录异常: {e}")
            return False

    def fetch_all_products(self):
        """自动翻页获取产品列表"""
        all_products = []
        page = 1
        page_size = 100
        last_page_ids = []

        print(f"\n[*] 第一阶段：开始获取产品列表 (viewname=397)...")
        if DEBUG_MODE:
            print(f"    [提示] 调试模式开启，仅获取前 {DEBUG_LIMIT} 条。")

        while True:
            # 调试限制
            if DEBUG_MODE and len(all_products) >= DEBUG_LIMIT:
                print(f"    [调试] 已达到 {DEBUG_LIMIT} 条限制，停止获取。")
                all_products = all_products[:DEBUG_LIMIT]
                break

            payload = {
                "module": "Products", "action": "ProductsAjax", "file": "ListViewData",
                "sorder": "", "start": str(page), "order_by": "", "pagesize": str(page_size),
                "actionId": "1769042712624", "isFilter": "true", "search[viewname]": "397"
            }

            try:
                resp = self.session.post(BASE_URL, data=payload, headers=self.headers)
                data = resp.json()
                page_items = data.get("data", []) if isinstance(data, dict) else data

                if not page_items:
                    print(f"    第 {page} 页为空，结束。")
                    break

                # 死循环检测
                current_page_ids = [item.get('crmid') for item in page_items]
                if current_page_ids == last_page_ids:
                    print(f"    第 {page} 页重复，停止。")
                    break
                last_page_ids = current_page_ids

                all_products.extend(page_items)
                print(f"    已获取第 {page} 页 (本页{len(page_items)}条) - 总计: {len(all_products)}条")
                page += 1
                time.sleep(0.2)

            except Exception as e:
                print(f"[-] 获取第 {page} 页出错: {e}")
                break

        return all_products

    def check_single_product(self, item):
        """
        核心筛选逻辑：
        1. 检查销量 (SalesNum) -> 必须为0
        2. 检查关联 (Key 36, 37, 325, 523, 561) -> 必须全为0
        3. 【恢复】检查历史 (CangkuHistory) -> 必须为空
        """
        with STATS_LOCK:
            STATS["total_processed"] += 1

        # 1. 获取基础信息
        crm_id = item.get("crmid") or item.get("productid")
        raw_name = item.get("productname", "")
        product_code = item.get("productcode", "")

        if not crm_id:
            with STATS_LOCK: STATS["skipped_no_id"] += 1
            return None

        # 2. 筛选第一步：检查销量 (必须为0)
        sales_str = str(item.get("salesnum", "0")).replace(",", "")
        try:
            sales_num = float(sales_str)
        except ValueError:
            sales_num = 0.0

        if sales_num != 0:
            with STATS_LOCK: STATS["skipped_has_sales"] += 1
            return None

        try:
            # 3. 筛选第二步：检查关联列表
            # 获取所有关联模块的计数值
            check1_params = {
                "module": "Users", "action": "UsersAjax", "file": "setRelatedListCount",
                "modulename": "Products", "record": crm_id
            }
            resp1 = self.session.post(BASE_URL, data=check1_params, headers=self.headers, timeout=10)
            if not resp1.text:
                with STATS_LOCK: STATS["skipped_api_error"] += 1
                return None

            data1 = resp1.json()  # 拿到完整的 JSON 字典

            # 定义需要检查的 Key 列表
            target_keys = ["36", "37", "325", "523", "561"]

            # 只要这些 Key 中有一个值不为 "0"，就直接判定为“有关联”，立即跳过
            for key in target_keys:
                val = data1.get(key)
                if val is None:
                    try:
                        val = data1.get(int(key))
                    except:
                        pass

                val_str = str(val) if val is not None else "0"

                if val_str != "0":
                    with STATS_LOCK: STATS["skipped_has_relations"] += 1
                    return None

            # 4. 【恢复】筛选第三步：检查仓库历史 (必须为空)
            check2_params = {
                "module": "Products", "action": "ProductsAjax", "file": "getCangkuHistoryInfo",
                "productid": crm_id, "currpage": "1"
            }
            resp2 = self.session.post(BASE_URL, data=check2_params, headers=self.headers, timeout=10)
            data2 = resp2.json()

            # 获取 entity -> value 列表
            entity_value = data2.get("entity", {}).get("value")

            # 如果列表存在且长度大于0，说明有历史记录，跳过
            if entity_value and len(entity_value) > 0:
                with STATS_LOCK: STATS["skipped_has_history"] += 1
                return None

            # === 全部通过，提取详细数据 ===
            with STATS_LOCK:
                STATS["success"] += 1

            # --- 数据清洗与提取 ---

            # 1. 产品名称 (去除 HTML)
            clean_name = re.sub(r'<[^>]+>', '', str(raw_name)).strip()

            # 2. 厂家 (cf_2128) - 直接获取文本
            manufacturer = str(item.get("cf_2128", "")).strip()

            # 3. 供应商名称 (vendorid) - 去除 HTML 标签，提取文本
            raw_vendor = item.get("vendorid", "")
            clean_vendor = re.sub(r'<[^>]+>', '', str(raw_vendor)).strip()

            # 4. 产品类别 (catalogid) - 根据要求，不含HTML，直接获取文本
            clean_catalog = str(item.get("catalogid", "")).strip()

            return {
                "产品名称": clean_name,
                "产品编码": product_code,
                "厂家": manufacturer,
                "供应商名称": clean_vendor,
                "产品类别": clean_catalog
            }

        except Exception as e:
            with STATS_LOCK:
                STATS["skipped_api_error"] += 1
            return None


def get_template_columns(filename):
    if not os.path.exists(filename):
        print(f"[-] 错误：找不到模板文件 '{filename}'")
        return None
    try:
        try:
            df = pd.read_csv(filename, encoding='utf-8-sig', nrows=0)
        except UnicodeDecodeError:
            df = pd.read_csv(filename, encoding='gbk', nrows=0)
        return df.columns.tolist()
    except Exception as e:
        print(f"[-] 读取模板表头失败: {e}")
        return None


def main():
    columns = get_template_columns(TEMPLATE_FILE)
    if not columns:
        return

    fetcher = CRMFetcher()
    if not fetcher.login():
        return

    all_data = fetcher.fetch_all_products()
    total_count = len(all_data)

    if total_count == 0:
        print("[-] 未获取到数据。")
        return

    print(f"\n[*] 第二阶段：并发筛选 {total_count} 条数据 (含多重关联与历史记录验证)...")

    valid_rows = []
    processed_count = 0
    start_time = time.time()

    with ThreadPoolExecutor(max_workers=MAX_WORKERS) as executor:
        future_to_item = {executor.submit(fetcher.check_single_product, item): item for item in all_data}

        for future in as_completed(future_to_item):
            processed_count += 1
            result_dict = future.result()

            if result_dict:
                # 动态映射：只有模板里有的列，才会被写入
                row_data = {col: None for col in columns}

                # 映射关系配置 (Excel列名 : 数据字典Key)
                # 请确保您的CSV模板中包含 "厂家", "供应商名称", "产品类别" 这几列，否则不会写入
                mapping = {
                    "产品名称": "产品名称",
                    "产品编码": "产品编码",
                    "厂家": "厂家",
                    "供应商名称": "供应商名称",
                    "产品类别": "产品类别"
                }

                for col_name in columns:
                    if col_name in mapping:
                        row_data[col_name] = result_dict.get(mapping[col_name])

                valid_rows.append(row_data)

            if processed_count % 20 == 0 or processed_count == total_count:
                percent = (processed_count / total_count) * 100
                speed = processed_count / (time.time() - start_time + 0.01)
                print(
                    f"\r进度: {processed_count}/{total_count} ({percent:.1f}%) - 选中: {len(valid_rows)} - 速度: {speed:.1f}条/秒",
                    end="")

    print("\n\n" + "=" * 40)
    print("       筛选结果统计")
    print("=" * 40)
    print(f"总处理条数     : {STATS['total_processed']}")
    print(f"[-] 因缺失ID跳过   : {STATS['skipped_no_id']}")
    print(f"[-] 因有销量跳过   : {STATS['skipped_has_sales']}")
    print(f"[-] 因有关联跳过   : {STATS['skipped_has_relations']} (Key 36/37/325/523/561 != 0)")
    print(f"[-] 因有历史跳过   : {STATS['skipped_has_history']} (Has History)")
    print(f"[-] 因API错误跳过  : {STATS['skipped_api_error']}")
    print(f"[+] 最终成功保留   : {STATS['success']}")
    print("=" * 40)

    if valid_rows:
        try:
            df_output = pd.DataFrame(valid_rows, columns=columns)
            print(f"[*] 正在写入 Excel '{OUTPUT_FILE}'...")
            df_output.to_excel(OUTPUT_FILE, index=False)
            print(f"[+] 成功！")
        except Exception as e:
            print(f"[-] 写入失败: {e}")
    else:
        print("[-] 没有数据被选中。")


if __name__ == "__main__":
    main()