import asyncio
import aiohttp
import traceback
import time
from Util.random_util import RandomUtil  # 保证该模块中提供了生成随机数字和随机日期的函数
from Util.dingtalk_helper import DingTalkHelper
from tqdm import tqdm  # 导入进度条库

# 钉钉机器人 access_token 和 secret
ACCESS_TOKEN = '4625f6690acd9347fae5b3a05af598be63e73d604b933a9b3902425b8f136d4d'
SECRET = 'SEC3b6937550bd297b5491855f6f40c2ff1b41bc8c495e118ba9848742b1ddf8f19'

# 请求URL和请求头
apiname = "我的动物"
url = "http://tsinghua.baoyizn.com:9906/api/escrow/animal/escrowAnimal/save"
headers = {
    "token": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJleHAiOjE3NDUwMzExNjAsInVzZXJuYW1lIjoiZ2x5In0.zra2vwwvl-NQKN_tyNzRbiF3kzfUQovXBuSmEGcXPFY",
    "Content-Type": "application/json"
}

dingtalk_helper = DingTalkHelper(ACCESS_TOKEN, SECRET)

gender = "1"
mother_id = ""
mother_wholeCode = ""
father_id = ""
father_wholeCode = ""
algebra = 1
preCode = "性能测试"

# 生成请求体
def create_animal_data():
    random_code = RandomUtil.generate_random_number_string(0, 999999999)
    random_date = RandomUtil.generate_random_date("2023-01-01", "2025-03-25")
    return {
        "bac": {"id": ""},
        "cage": {"id": "", "code": ""},
        "code": random_code,
        "room": {"id": ""},
        "user": {
            "id": "1780483551554764801",
            "name": "hyb实验人员"
        },
        "color": "4",
        "ethic": {
            "id": "1790288720729997312",
            "apCode": "24- Hybktfzr23.G24-4"
        },
        "shelf": {
            "id": "",
            "variety": {"id": ""}
        },
        "father": {
            "id": father_id,
            "wholeCode": father_wholeCode
        },
        "gender": gender,
        "mother": {
            "id": mother_id,
            "wholeCode": mother_wholeCode
        },
        "strain": {
            "id": "1846491449918550017",
            "bac": {"id": "", "name": "转基因"},
            "name": "hyb无需鉴定基因型，求求勿动",
            "type": "1",
            "maxNum": 5,
            "geneIds": {"id": "1810583565757919233,1810583743961313281,1810583743961313281,1810583743961313281,1860972233362567169"},
            "variety": {
                "id": "",
                "name": "SPF级基因鼠（荧光蛋白标记小鼠）",
                "isChip": "1"
            }
        },
        "algebra": algebra,
        "preCode": preCode ,
        "variety": {"id": "1661975536839733250"},
        "weaning": "2",
        "chipCode": random_code,
        "genotype": "hyb管理员创建共享，求求勿动 +/-/Tg/WT,hyb管理员创建使用者为课题负责人共享，求求勿动 +/-/Homo/Heter/WT",
        "transfer": "0",
        "birthDate": random_date,
        "wholeCode": f"{preCode}-{random_code}",
        "algebraWay": "1",
        "animalStatus": "0",
        "escrowStatus": "1",
        "researchGroup": {"id": "1699404304041828353"}
    }


# 异步发送单个请求，并返回是否成功
async def create_animal(session: aiohttp.ClientSession, index: int, max_retries: int = 3):
    data = create_animal_data()
    attempt = 0
    while attempt < max_retries:
        try:
            async with session.post(url, json=data, headers=headers) as response:
                resp_text = await response.text()
                if response.status == 200:
                    print(f"[INFO] 第 {index} 个动物创建成功，响应：{resp_text}")
                    return True
                else:
                    print(f"[ERROR] 第 {index} 个动物创建失败，状态码：{response.status}，响应：{resp_text}")
                    return False
        except Exception as e:
            attempt += 1
            status_code = getattr(e, 'status', 'N/A')
            error_trace = traceback.format_exc()
            full_log = (
                f"请求URL: {url}\n"
                f"请求头: {headers}\n"
                f"请求数据: {data}\n"
                f"状态码: {status_code}\n"
                f"异常信息: {str(e)}\n"
                f"堆栈跟踪:\n{error_trace}\n"
                f"重试次数: {attempt}/{max_retries}"
            )
            print(f"[EXCEPTION] 第 {index} 个动物请求异常：\n{full_log}\n")
            if attempt < max_retries:
                # 重试前等待 1 秒
                await asyncio.sleep(1)
            else:
                return False


# 批量异步创建动物信息，同时显示进度条
async def batch_create_animals(batch_size: int):
    tasks = []
    # 设置超时时间为60秒（可根据需要调整）
    timeout = aiohttp.ClientTimeout(total=60)
    async with aiohttp.ClientSession(timeout=timeout) as session:
        for i in range(1, batch_size + 1):
            task = asyncio.ensure_future(create_animal(session, i))
            tasks.append(task)

        success_count = 0
        # 使用 asyncio.as_completed 逐个等待任务完成，并更新进度条
        with tqdm(total=batch_size, desc="创建动物进度") as pbar:
            for finished in asyncio.as_completed(tasks):
                result = await finished
                if result:
                    success_count += 1
                pbar.update(1)
        summary = f"\n[SUMMARY] 成功创建 {success_count}/{batch_size} 只动物"
        print(summary)
        dingtalk_helper.send_message(
            f"你的批量创建{apiname}模块数据已完成：成功创建 {success_count}/{batch_size} 只动物")


# 主入口
if __name__ == '__main__':
    n = 10  # 可根据需要调整批量创建数量
    asyncio.run(batch_create_animals(n))