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

# ================= 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，只获取前 200 条数据进行测试
# False: 关闭调试模式，处理所有数据 (2万条+)
DEBUG_MODE = False
DEBUG_LIMIT = 1000

# --- 文件配置 ---
TEMPLATE_FILE = "产品-导入模板.csv"  # 你的 CSV 模板文件
OUTPUT_FILE = "最终导出数据.xlsx"  # 生成的 Excel 文件
MAX_WORKERS = 10  # 并发线程数


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

class CRMFetcher:
    def __init__(self):
        self.session = requests.Session()
        # 优化连接池
        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):
        """执行登录"""
        print("[*] 正在登录系统...")
        payload = {
            "module": "Users", "action": "Authenticate", "return_module": "Users",
            "return_action": "Login", "user_name": USERNAME, "user_password": PASSWORD,
            "login_theme": "newskin"
        }
        try:
            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("[-] 登录失败，请检查账号密码。")
                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

        print(f"\n[*] 第一阶段：开始获取产品列表 (调试模式: {'开启' if DEBUG_MODE else '关闭'})...")

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

            payload = {
                "module": "Products", "action": "ProductsAjax", "file": "ListViewData",
                "start": str(page), "pagesize": str(page_size),
                "isFilter": "true", "search[viewname]": "28",
                "filter[Fields0]": "cf_2318", "filter[Condition0]": "is", "filter[Srch_value0]": "否",
                "filter[type0]": "opts", "filter[search_cnt]": "1", "filter[matchtype]": "all"
            }

            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 or len(page_items) == 0:
                    print(f"    第 {page} 页为空，列表获取结束。")
                    break

                all_products.extend(page_items)
                print(f"    已获取第 {page} 页 - 总计: {len(all_products)}条")

                page += 1
                time.sleep(0.2)

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

        return all_products

    def check_single_product(self, item):
        """
        核心检查逻辑
        返回：{'产品名称': name, '产品编码': code} 如果符合条件
        返回：None 如果不符合
        """
        crm_id = item.get("crmid")
        raw_name = item.get("productname", "")
        product_code = item.get("productcode", "")

        # === 优化步骤 0: 检查 salesnum (销量) ===
        # 获取销量，处理可能的逗号 (如 "1,000.00") 和空值
        sales_str = str(item.get("salesnum", "0")).replace(",", "")
        try:
            sales_num = float(sales_str)
        except ValueError:
            sales_num = 0.0

        # 如果销量不为0，说明是“保留”产品，不需要进行后续检查，直接跳过（返回 None）
        # 从而极大减少 API 请求
        if sales_num != 0:
            return None

        # -------------------------------------------------------
        # 下面是销量为 0 时，进行的严格验证 (验证是否为废弃/空闲数据)
        # -------------------------------------------------------

        if not crm_id:
            return None

        try:
            # === 步骤 1: 检查关联列表 (Key 36 是否为 0) ===
            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)
            data1 = resp1.json()

            val_36 = data1.get("36") or data1.get(36)

            # 如果不等于0，跳过
            if str(val_36) != "0":
                return None

            # === 步骤 2: 检查仓库历史 (是否为空) ===
            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()

            entity_value = data2.get("entity", {}).get("value")

            # 如果有历史记录，跳过
            if entity_value and len(entity_value) > 0:
                return None

            # === 步骤 3: 所有条件满足（销量0 + 无关联 + 无历史），写入 Excel ===
            clean_name = re.sub(r'<[^>]+>', '', raw_name).strip()

            return {
                "产品名称": clean_name,
                "产品编码": product_code
            }

        except Exception as e:
            # 网络超时或其他错误，跳过
            return None


def get_template_columns(filename):
    """读取 CSV 模板的表头"""
    if not os.path.exists(filename):
        print(f"[-] 错误：找不到模板文件 '{filename}'")
        return None

    try:
        # 兼容 utf-8 和 gbk
        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():
    # 1. 读取模板表头
    columns = get_template_columns(TEMPLATE_FILE)
    if not columns:
        return
    print(f"[*] 成功读取模板表头，目标 Excel 将包含这 {len(columns)} 列。")

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

    # 2. 获取数据列表
    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：智能筛选 {total_count} 条数据 (利用销量数据加速)...")

    valid_rows = []
    processed_count = 0
    skipped_by_sales = 0  # 统计优化了多少条
    start_time = time.time()

    # 3. 开启线程池
    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()

            # 这里的统计逻辑稍微模糊，因为 result_dict 为 None 可能是因为销量不为0，也可能是因为 API 检查不通过
            # 但不影响核心功能
            if result_dict:
                row_data = {col: None for col in columns}
                if "产品名称" in columns:
                    row_data["产品名称"] = result_dict["产品名称"]
                if "产品编码" in columns:
                    row_data["产品编码"] = result_dict["产品编码"]
                valid_rows.append(row_data)

            # 进度条
            if processed_count % 50 == 0 or processed_count == total_count:
                percent = (processed_count / total_count) * 100
                elapsed = time.time() - start_time
                speed = processed_count / elapsed if elapsed > 0 else 0
                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[*] 筛选完成！")

    # 4. 生成 Excel
    try:
        if not valid_rows:
            print("[!] 警告：没有筛选出符合条件的数据，生成的 Excel 将为空。")

        df_output = pd.DataFrame(valid_rows, columns=columns)
        print(f"[*] 正在保存为 Excel 文件 '{OUTPUT_FILE}'...")
        df_output.to_excel(OUTPUT_FILE, index=False)

        print(f"[+] 成功！结果已写入 '{OUTPUT_FILE}'")
        print(f"[+] 提示：请务必检查 '调试模式' (DEBUG_MODE) 是否已根据需要关闭。")

    except Exception as e:
        print(f"[-] 写入 Excel 失败: {e}")


if __name__ == "__main__":
    main()