# import pandas as pd
# import datetime
# from sqlalchemy import create_engine
# # 转换股票代码
# def tranTicker(tick):
#     tick = str(tick)
#
#     if len(tick) == 8:
#         tick = tick.strip('SH').strip('SZ')
#         if tick.startswith('6') or tick.startswith('11') or tick.startswith('10') or tick.startswith('51'):
#             tick = 'SH' + tick
#         elif tick.startswith('0') or tick.startswith('3') or tick.startswith('15') or tick.startswith(
#                 '16') or tick.startswith(
#                 '12'):
#             tick = 'SZ' + tick
#         else:
#             pass
#     elif len(tick) == 6:
#         if tick.startswith('6') or tick.startswith('11') or tick.startswith('10') or tick.startswith('51'):
#             tick = 'SH' + tick
#         elif tick.startswith('0') or tick.startswith('15') or tick.startswith('12') or tick.startswith(
#                 '16') or tick.startswith('3'):
#             tick = 'SZ' + tick
#         else:
#             pass
#     else:
#         num = 6 - len(tick)
#         tick = 'SZ' + num * '0' + tick
#
#     return tick
# engine_auto_update_web_strategy = create_engine(
#             'mysql+pymysql://ainvest:JRLeiYD423!@rm-2zewagytttzk6f24xno.mysql.rds.aliyuncs.com:3306/auto_update_web_strategy',
#             encoding="utf-8", echo=False)
# # df = pd.read_excel(fr'C:\Users\EDY\Documents\20250403 历史成交查询.xls')
# df = pd.read_csv(fr'C:\Users\EDY\Documents\20250411 历史成交查询.xls', encoding='gbk', sep='\t',
#                              error_bad_lines=False).applymap(
#             lambda x: x.replace('"', '').replace('=', '') if isinstance(x, str) else x)
# df.columns = [i.replace('"', '').replace('=', '') for i in list(df.columns)]
# df = df[['成交时间', '证券代码', '证券名称', '买卖标志', '成交数量', '成交价格']]
# print(df)
# df['As_Of_Date'] = datetime.date(2025,4,10)
# df.rename(columns={'成交时间': 'Trade_time', '证券代码': 'Ticker', '证券名称': 'Ticker_name', '买卖标志': 'Operate',
#                    '成交数量': 'Number_transactions',
#                    '成交价格': 'Average_price'}, inplace=True)
# df['Operate'] = df['Operate'].apply(lambda x: '卖' if '卖' in x else '买')
#
# df['Ticker'] = df['Ticker'].apply(lambda x: tranTicker(str(x)))
# df['Account_Name'] = '13834890033'
# print(df)
# df.to_sql('daily_transaction_record_detail', engine_auto_update_web_strategy,
#                           if_exists='append',
#                           index=False, chunksize=100)




# import pandas as pd
# import datetime
# from sqlalchemy import create_engine
# # 转换股票代码
# def tranTicker(tick):
#     tick = str(tick)
#
#     if len(tick) == 8:
#         tick = tick.strip('SH').strip('SZ')
#         if tick.startswith('6') or tick.startswith('11') or tick.startswith('10') or tick.startswith('51'):
#             tick = 'SH' + tick
#         elif tick.startswith('0') or tick.startswith('3') or tick.startswith('15') or tick.startswith(
#                 '16') or tick.startswith(
#                 '12'):
#             tick = 'SZ' + tick
#         else:
#             pass
#     elif len(tick) == 6:
#         if tick.startswith('6') or tick.startswith('11') or tick.startswith('10') or tick.startswith('51'):
#             tick = 'SH' + tick
#         elif tick.startswith('0') or tick.startswith('15') or tick.startswith('12') or tick.startswith(
#                 '16') or tick.startswith('3'):
#             tick = 'SZ' + tick
#         else:
#             pass
#     else:
#         num = 6 - len(tick)
#         tick = 'SZ' + num * '0' + tick
#
#     return tick
# engine_auto_update_web_strategy = create_engine(
#             'mysql+pymysql://ainvest:JRLeiYD423!@rm-2zewagytttzk6f24xno.mysql.rds.aliyuncs.com:3306/auto_update_web_strategy',
#             encoding="utf-8", echo=False)
# df = pd.read_csv(fr'C:\Users\EDY\Documents\table.xls',encoding='gbk',sep = '\t').applymap(
#             lambda x: x.replace('"', '').replace('=', '') if isinstance(x, str) else x)
# print(df)
# # df = df[['成交时间', '证券代码', '证券名称', '方向', '成交数量', '成交价格']]
# df = df[['成交时间', '证券代码', '证券名称', '操作', '成交数量', '成交价格']]
# df['As_Of_Date'] = datetime.date(2025,4,2)
# df.rename(columns={'成交时间': 'Trade_time', '证券代码': 'Ticker', '证券名称': 'Ticker_name', '操作': 'Operate',
#                    '成交数量': 'Number_transactions',
#                    '成交价格': 'Average_price'}, inplace=True)
# df['Operate'] = df['Operate'].apply(lambda x: '卖' if '卖' in x else '买')
#
# df['Ticker'] = df['Ticker'].apply(lambda x: tranTicker(str(x)))
# df['Account_Name'] = '15935144173'
# print(df)
# df.to_sql('daily_transaction_record_detail', engine_auto_update_web_strategy,
#                           if_exists='append',
#                           index=False, chunksize=100)
#
# from tools import *
#
# mac_info = subprocess.check_output('GETMAC /v /FO list', stderr=subprocess.STDOUT)
# mac_info = mac_info.decode('gbk')
# # 想要匹配的连接名
# target_connection_name = "WLAN 2"
#
# # 构建正则表达式模式
# pattern = re.compile(
#     r"连接名:\s+" + re.escape(target_connection_name) + r".*?物理地址:\s+([0-9A-Fa-f-]+)",
#     re.DOTALL
# )
# # 执行搜索
# match = pattern.search(mac_info).group(1)
# print(match)
# mac_info = subprocess.check_output('GETMAC /v /FO list', stderr=subprocess.STDOUT)
# mac_info = mac_info.decode('gbk')
# search = re.search(r'WLAN 2\s+物理地址: (.+)\s+传输名称', mac_info)
# mac = (search.group(1).strip()) if search else ('', '')
# print(search)
project_name = 'auto_trade_20230130'
import pyautogui
import pywinauto
from PIL import ImageGrab
from pywinauto import clipboard
from pywinauto import keyboard
from skimage import io
import time
import io as mio
import pytesseract
import warnings
import datetime
from tools import *
from connect_wifi import connect_wifi
from iptest import get_proxy_ip,set_global_proxy,get_ip_data
scripts_path = os.path.dirname(os.path.realpath(__file__))
root_path = scripts_path[:scripts_path.find(project_name)+len(project_name)]
im = io.imread(f'{root_path}/imgs/temp123.png')
# print(')))))',im)
id_code = pytesseract.image_to_string(im, lang='chi_sim',config='--psm 7').strip()

id_code = id_code.replace(' ', '')
print(id_code)