99 lines
3.1 KiB
Python
99 lines
3.1 KiB
Python
# flake8: noqa
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"""
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下载rqdata股票合约1分钟bar => vnpy项目目录/bar_data/
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"""
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import os
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import sys
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import json
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from collections import OrderedDict
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import pandas as pd
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vnpy_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
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if vnpy_root not in sys.path:
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sys.path.append(vnpy_root)
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os.environ["VNPY_TESTING"] = "1"
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from vnpy.data.tdx.tdx_stock_data import *
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from vnpy.trader.utility import load_json
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from vnpy.trader.rqdata import RqdataClient
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# 保存的1分钟指数 bar目录
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bar_data_folder = os.path.abspath(os.path.join(vnpy_root, 'bar_data'))
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# 开始日期（每年大概需要几分钟）
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start_date = '20160101'
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# 创建API对象
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api_01 = TdxStockData()
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rq = RqdataClient()
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rq.init(username='incenselee@hotmail.com', password='123456')
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# 更新本地合约缓存信息
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stock_list = load_json('stock_list.json')
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symbol_dict = api_01.symbol_dict
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# 逐一指数合约下载并更新
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for stock_code in stock_list:
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market_id = get_tdx_market_code(stock_code)
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if market_id == 0:
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exchange_name = '深交所'
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exchange = Exchange.SZSE
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else:
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exchange_name = '上交所'
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exchange = Exchange.SSE
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symbol_info = symbol_dict.get(f'{stock_code}_{market_id}')
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stock_name = symbol_info.get('name')
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print(f'开始更新:{exchange_name}/{stock_name}, 代码:{stock_code}')
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bar_file_folder = os.path.abspath(os.path.join(bar_data_folder, f'{exchange.value}'))
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if not os.path.exists(bar_file_folder):
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os.makedirs(bar_file_folder)
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# csv数据文件名
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bar_file_path = os.path.abspath(os.path.join(bar_file_folder, f'{stock_code}_{start_date}_1m.csv'))
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# 如果文件存在，
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if os.path.exists(bar_file_path):
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df_old = pd.read_csv(bar_file_path, index_col=0)
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df_old = df_old.rename(lambda x: pd.to_datetime(x, format="%Y-%m-%d %H:%M:%S"))
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# 取最后一条时间
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last_dt = df_old.index[-1]
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start_dt = last_dt - timedelta(days=1)
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print(f'文件{bar_file_path}存在，最后时间:{start_date}')
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else:
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df_old = None
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start_dt = datetime.strptime(start_date, '%Y%m%d')
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print(f'文件{bar_file_path}不存在，开始时间:{start_date}')
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result, bars = api_01.get_bars(symbol=stock_code,
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period='1min',
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callback=None,
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start_dt=start_dt,
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return_bar=False)
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# [dict] => dataframe
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if not result or len(bars) == 0:
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continue
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df_extern = pd.DataFrame(bars)
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df_extern.set_index('datetime', inplace=True)
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if df_old is not None:
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# 扩展数据
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print('扩展数据')
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data_df = pd.concat([df_old, df_extern], axis=0)
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else:
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data_df = df_extern
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# 数据按时间戳去重
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print('按时间戳去重')
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data_df = data_df[~data_df.index.duplicated(keep='first')]
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# 排序
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data_df = data_df.sort_index()
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# print(data_df.head())
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print(data_df.tail())
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data_df.to_csv(bar_file_path, index=True)
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print(f'更新{stock_name} {stock_code}数据 => 文件{bar_file_path}')
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print('更新完毕')
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os._exit(0)
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