150 lines
6.3 KiB
Python
150 lines
6.3 KiB
Python
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# import pandas as pd
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# import datetime
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# from sqlalchemy import create_engine
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# # 转换股票代码
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# def tranTicker(tick):
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# tick = str(tick)
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#
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# if len(tick) == 8:
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# tick = tick.strip('SH').strip('SZ')
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# if tick.startswith('6') or tick.startswith('11') or tick.startswith('10') or tick.startswith('51'):
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# tick = 'SH' + tick
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# elif tick.startswith('0') or tick.startswith('3') or tick.startswith('15') or tick.startswith(
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# '16') or tick.startswith(
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# '12'):
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# tick = 'SZ' + tick
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# else:
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# pass
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# elif len(tick) == 6:
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# if tick.startswith('6') or tick.startswith('11') or tick.startswith('10') or tick.startswith('51'):
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# tick = 'SH' + tick
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# elif tick.startswith('0') or tick.startswith('15') or tick.startswith('12') or tick.startswith(
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# '16') or tick.startswith('3'):
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# tick = 'SZ' + tick
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# else:
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# pass
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# else:
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# num = 6 - len(tick)
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# tick = 'SZ' + num * '0' + tick
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#
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# return tick
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# engine_auto_update_web_strategy = create_engine(
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# 'mysql+pymysql://ainvest:JRLeiYD423!@rm-2zewagytttzk6f24xno.mysql.rds.aliyuncs.com:3306/auto_update_web_strategy',
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# encoding="utf-8", echo=False)
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# # df = pd.read_excel(fr'C:\Users\EDY\Documents\20250403 历史成交查询.xls')
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# df = pd.read_csv(fr'C:\Users\EDY\Documents\20250411 历史成交查询.xls', encoding='gbk', sep='\t',
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# error_bad_lines=False).applymap(
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# lambda x: x.replace('"', '').replace('=', '') if isinstance(x, str) else x)
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# df.columns = [i.replace('"', '').replace('=', '') for i in list(df.columns)]
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# 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']]
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# print(df)
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# df['As_Of_Date'] = datetime.date(2025,4,10)
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# 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',
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# '成交数量': 'Number_transactions',
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# '成交价格': 'Average_price'}, inplace=True)
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# df['Operate'] = df['Operate'].apply(lambda x: '卖' if '卖' in x else '买')
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#
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# df['Ticker'] = df['Ticker'].apply(lambda x: tranTicker(str(x)))
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# df['Account_Name'] = '13834890033'
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# print(df)
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# df.to_sql('daily_transaction_record_detail', engine_auto_update_web_strategy,
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# if_exists='append',
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# index=False, chunksize=100)
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# import pandas as pd
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# import datetime
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# from sqlalchemy import create_engine
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# # 转换股票代码
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# def tranTicker(tick):
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# tick = str(tick)
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#
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# if len(tick) == 8:
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# tick = tick.strip('SH').strip('SZ')
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# if tick.startswith('6') or tick.startswith('11') or tick.startswith('10') or tick.startswith('51'):
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# tick = 'SH' + tick
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# elif tick.startswith('0') or tick.startswith('3') or tick.startswith('15') or tick.startswith(
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# '16') or tick.startswith(
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# '12'):
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# tick = 'SZ' + tick
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# else:
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# pass
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# elif len(tick) == 6:
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# if tick.startswith('6') or tick.startswith('11') or tick.startswith('10') or tick.startswith('51'):
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# tick = 'SH' + tick
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# elif tick.startswith('0') or tick.startswith('15') or tick.startswith('12') or tick.startswith(
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# '16') or tick.startswith('3'):
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# tick = 'SZ' + tick
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# else:
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# pass
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# else:
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# num = 6 - len(tick)
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# tick = 'SZ' + num * '0' + tick
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#
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# return tick
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# engine_auto_update_web_strategy = create_engine(
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# 'mysql+pymysql://ainvest:JRLeiYD423!@rm-2zewagytttzk6f24xno.mysql.rds.aliyuncs.com:3306/auto_update_web_strategy',
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# encoding="utf-8", echo=False)
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# df = pd.read_csv(fr'C:\Users\EDY\Documents\table.xls',encoding='gbk',sep = '\t').applymap(
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# lambda x: x.replace('"', '').replace('=', '') if isinstance(x, str) else x)
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# print(df)
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# # df = df[['成交时间', '证券代码', '证券名称', '方向', '成交数量', '成交价格']]
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# df = df[['成交时间', '证券代码', '证券名称', '操作', '成交数量', '成交价格']]
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# df['As_Of_Date'] = datetime.date(2025,4,2)
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# df.rename(columns={'成交时间': 'Trade_time', '证券代码': 'Ticker', '证券名称': 'Ticker_name', '操作': 'Operate',
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# '成交数量': 'Number_transactions',
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# '成交价格': 'Average_price'}, inplace=True)
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# df['Operate'] = df['Operate'].apply(lambda x: '卖' if '卖' in x else '买')
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#
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# df['Ticker'] = df['Ticker'].apply(lambda x: tranTicker(str(x)))
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# df['Account_Name'] = '15935144173'
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# print(df)
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# df.to_sql('daily_transaction_record_detail', engine_auto_update_web_strategy,
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# if_exists='append',
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# index=False, chunksize=100)
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#
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# from tools import *
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#
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# mac_info = subprocess.check_output('GETMAC /v /FO list', stderr=subprocess.STDOUT)
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# mac_info = mac_info.decode('gbk')
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# # 想要匹配的连接名
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# target_connection_name = "WLAN 2"
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#
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# # 构建正则表达式模式
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# pattern = re.compile(
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# r"连接名:\s+" + re.escape(target_connection_name) + r".*?物理地址:\s+([0-9A-Fa-f-]+)",
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# re.DOTALL
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# )
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# # 执行搜索
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# match = pattern.search(mac_info).group(1)
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# print(match)
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# mac_info = subprocess.check_output('GETMAC /v /FO list', stderr=subprocess.STDOUT)
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# mac_info = mac_info.decode('gbk')
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# search = re.search(r'WLAN 2\s+物理地址: (.+)\s+传输名称', mac_info)
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# mac = (search.group(1).strip()) if search else ('', '')
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# print(search)
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project_name = 'auto_trade_20230130'
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import pyautogui
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import pywinauto
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from PIL import ImageGrab
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from pywinauto import clipboard
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from pywinauto import keyboard
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from skimage import io
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import time
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import io as mio
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import pytesseract
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import warnings
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import datetime
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from tools import *
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from connect_wifi import connect_wifi
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from iptest import get_proxy_ip,set_global_proxy,get_ip_data
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scripts_path = os.path.dirname(os.path.realpath(__file__))
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root_path = scripts_path[:scripts_path.find(project_name)+len(project_name)]
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im = io.imread(f'{root_path}/imgs/temp123.png')
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# print(')))))',im)
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id_code = pytesseract.image_to_string(im, lang='chi_sim',config='--psm 7').strip()
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id_code = id_code.replace(' ', '')
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print(id_code)
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