vnpy/prod/jobs/refill_bao_stock_bars.py

138 lines
4.5 KiB
Python

# flake8: noqa
"""
下载证券宝5分钟bar => vnpy项目目录/bar_data/
"""
import os
import sys
import csv
import json
from collections import OrderedDict
import pandas as pd
from datetime import datetime, timedelta
vnpy_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
if vnpy_root not in sys.path:
sys.path.append(vnpy_root)
os.environ["VNPY_TESTING"] = "1"
import baostock as bs
from vnpy.trader.constant import Exchange
from vnpy.data.tdx.tdx_common import get_tdx_market_code
from vnpy.trader.utility import load_json, get_csv_last_dt
from vnpy.data.stock.stock_base import get_stock_base
# 保存的1分钟指数 bar目录
bar_data_folder = os.path.abspath(os.path.join(vnpy_root, 'bar_data'))
# 开始日期(每年大概需要几分钟)
start_date = '20060101'
# 证券宝连接
login_msg = bs.login()
if login_msg.error_code != '0':
print(f'证券宝登录错误代码:{login_msg.error_code}, 错误信息:{login_msg.error_msg}')
# 更新本地合约缓存信息
stock_list = load_json('stock_list.json')
symbol_dict = get_stock_base()
day_fields = "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST"
min_fields = "date,time,code,open,high,low,close,volume,amount,adjustflag"
# 逐一股票下载并更新
for stock_code in stock_list:
market_id = get_tdx_market_code(stock_code)
if market_id == 0:
exchange_name = '深交所'
exchange = Exchange.SZSE
exchange_code = 'sz'
else:
exchange_name = '上交所'
exchange = Exchange.SSE
exchange_code = 'sh'
symbol_info = symbol_dict.get(f'{stock_code}.{exchange.value}')
stock_name = symbol_info.get('name')
print(f'开始更新:{exchange_name}/{stock_name}, 代码:{stock_code}')
bar_file_folder = os.path.abspath(os.path.join(bar_data_folder, f'{exchange.value}'))
if not os.path.exists(bar_file_folder):
os.makedirs(bar_file_folder)
# csv数据文件名
bar_file_path = os.path.abspath(os.path.join(bar_file_folder, f'{stock_code}_{start_date}_5m.csv'))
# 如果文件存在,
if os.path.exists(bar_file_path):
# df_old = pd.read_csv(bar_file_path, index_col=0)
# df_old = df_old.rename(lambda x: pd.to_datetime(x, format="%Y-%m-%d %H:%M:%S"))
# 取最后一条时间
# last_dt = df_old.index[-1]
last_dt = get_csv_last_dt(bar_file_path)
start_dt = last_dt - timedelta(days=1)
print(f'文件{bar_file_path}存在,最后时间:{start_date}')
else:
last_dt = None
start_dt = datetime.strptime(start_date, '%Y%m%d')
print(f'文件{bar_file_path}不存在,开始时间:{start_date}')
rs = bs.query_history_k_data_plus(
code=f'{exchange_code}.{stock_code}',
fields=min_fields,
start_date=start_dt.strftime('%Y-%m-%d'), end_date=datetime.now().strftime('%Y-%m-%d'),
frequency="5",
adjustflag="3"
)
if rs.error_code != '0':
print(f'证券宝获取沪深A股历史K线数据错误代码:{rs.error_code}, 错误信息:{rs.error_msg}')
continue
# [dict] => dataframe
bars = []
while (rs.error_code == '0') and rs.next():
row = rs.get_row_data()
dt = datetime.strptime(row[1], '%Y%m%d%H%M%S%f')
if last_dt and last_dt > dt:
continue
bar = {
'datetime': dt,
'open': float(row[3]),
'close': float(row[6]),
'high': float(row[4]),
'low': float(row[5]),
'volume': float(row[7]),
'amount': float(row[8]),
'symbol': stock_code,
'trading_date': row[0],
'date': row[0],
'time': dt.strftime('%H:%M:%S')
}
bars.append(bar)
# 获取标题
if len(bars) == 0:
continue
headers = list(bars[0].keys())
if headers[0] != 'datetime':
headers.remove('datetime')
headers.insert(0, 'datetime')
bar_count = 0
# 写入所有大于最后bar时间的数据
with open(bar_file_path, 'a', encoding='utf8', newline='\n') as csvWriteFile:
writer = csv.DictWriter(f=csvWriteFile, fieldnames=headers, dialect='excel',
extrasaction='ignore')
if last_dt is None:
writer.writeheader()
for bar in bars:
bar_count += 1
writer.writerow(bar)
print(f'更新{stock_code}数据 => 文件{bar_file_path}, 最后记录:{bars[-1]}')
print('更新完毕')
bs.logout()
os._exit(0)