import json
import time
import os
import shutil
import random
import pandas as pd
from datetime import datetime

class InternalApiClient:
    """
    内部接口客户端桩代码 (Mock)
    """
    def __init__(self):
        self.api_url = "http://internal-system.local/api"
        
    def get_internal_product_id(self, scbank_goods_name):
        """
        Mock: 根据商城商品名查询内部商品编号
        """
        # 模拟延时
        time.sleep(0.1)
        if not scbank_goods_name: return None
        
        # 简单模拟
        if "iPhone" in scbank_goods_name: return "P_APPLE_001"
        if "华为" in scbank_goods_name: return "P_HUAWEI_002"
        return "P_UNKNOWN_999"

    def upload_order(self, order_detail):
        """
        Mock: 上传订单
        返回: (Success: bool, Message: str)
        """
        time.sleep(0.2)
        # 模拟随机成功率 90%
        if random.random() < 0.9:
            return True, "上传成功"
        else:
            return False, "模拟网络超时"

class SCBankProcessor:
    def __init__(self):
        self.data_dir = "data"
        self.archive_dir = "data/archive"
        self.output_dir = "output"
        self.client = InternalApiClient()
        
    def log(self, msg):
        print(f"[{datetime.now().strftime('%H:%M:%S')}] {msg}")

    def run(self):
        # 1. 扫描文件
        files = [f for f in os.listdir(self.data_dir) if f.startswith("raw_") and f.endswith(".jsonl")]
        if not files:
            self.log("没有待处理的数据文件。")
            return

        self.log(f"发现 {len(files)} 个待处理文件: {files}")

        for file_name in files:
            file_path = os.path.join(self.data_dir, file_name)
            self._process_file(file_path, file_name)

    def _process_file(self, file_path, file_name):
        self.log(f"正在处理文件: {file_name}")
        
        # 2. 读取与清洗
        raw_records = []
        try:
            with open(file_path, "r", encoding="utf-8") as f:
                for line in f:
                    if line.strip():
                        try:
                            raw_records.append(json.loads(line))
                        except: pass
        except Exception as e:
            self.log(f"读取文件失败: {e}")
            return

        if not raw_records:
            self.log("文件内容为空，跳过")
            return

        # 3. 数据结构化
        # 提取详情数据 (以此为主)
        details = []
        for r in raw_records:
            if r.get("type") == "detail":
                payload = r.get("payload", {})
                # 根据真实数据结构: payload -> body -> orderNo
                body = payload.get("body", {})
                if body and "orderNo" in str(body):
                    # 如果 body 是字符串，尝试解析
                    if isinstance(body, str):
                        try: body = json.loads(body)
                        except: pass
                    
                    details.append(body)
        
        # 去重 (按 orderNo)
        # 注意：这里假设 payload 是 dict，如果已经是 dict 则直接用
        # 如果是字符串则需要 json.loads
        unique_details = {}
        for d in details:
            # 兼容 payload 可能是字符串的情况 (虽然 Collector 存的是 dict)
            if isinstance(d, str):
                try: d = json.loads(d)
                except: continue
            
            order_no = d.get("orderNo") or d.get("orderId")
            if order_no:
                unique_details[order_no] = d

        self.log(f"解析出 {len(unique_details)} 条有效唯一订单详情")

        # 4. 业务处理与同步
        results = []
        for order_no, detail in unique_details.items():
            # 解析商品信息
            # goodsInfoList 是一个列表，这里取第一个商品作为主商品
            goods_list = detail.get("goodsInfoList", [])
            goods_name = "未知商品"
            if goods_list and len(goods_list) > 0:
                goods_name = goods_list[0].get("spuName", "未知商品")
            
            # Step 1: 查内部 ID
            internal_pid = self.client.get_internal_product_id(goods_name)
            
            # Step 2: 上传
            success, msg = self.client.upload_order(detail)
            
            # 时间格式化: 2026-03-10T00:50:37.000+0000 -> 2026-03-10 00:50:37
            order_time = detail.get("orderCreateTime")
            if order_time:
                try:
                    # 尝试解析 ISO 8601 格式
                    # 注意: python 3.7+ 的 fromisoformat 处理带时区的比较麻烦，这里用 strptime
                    # 格式: 2026-03-10T14:42:28.000+0000
                    # %z 只能解析 +0000 这种无冒号的时区
                    dt = datetime.strptime(order_time, "%Y-%m-%dT%H:%M:%S.%f%z")
                    order_time = dt.strftime("%Y-%m-%d %H:%M:%S")
                except ValueError:
                    try:
                        # 备用: 如果是 +00:00 这种格式，或者其他微秒位数不同
                         dt = datetime.strptime(order_time.split('.')[0], "%Y-%m-%dT%H:%M:%S")
                         order_time = dt.strftime("%Y-%m-%d %H:%M:%S")
                    except:
                        pass

            results.append({
                "处理状态": "成功" if success else "失败",
                "失败原因": "" if success else msg,
                "下单时间": order_time,
                "订单编号": order_no,
                "下单用户手机号码": detail.get("orderMobile"),
                "商户名称": detail.get("exMerchant"),
                "订单金额": detail.get("orderAmt"),
                "商品名称": goods_name,
                "内部商品ID": internal_pid,
            })

        # 5. 导出 Excel
        if results:
            ts = file_name.replace("raw_", "").replace(".jsonl", "")
            output_file = os.path.join(self.output_dir, f"result_{ts}.xlsx")
            df = pd.DataFrame(results)
            df.to_excel(output_file, index=False)
            self.log(f"结果已导出至: {output_file}")
        
        # 6. 归档
        try:
            shutil.move(file_path, os.path.join(self.archive_dir, file_name))
            self.log(f"源文件已归档至: {self.archive_dir}")
        except Exception as e:
            self.log(f"归档失败: {e}")

if __name__ == "__main__":
    processor = SCBankProcessor()
    processor.run()