vnpy/prod/jobs/refill_bao_stock_bars.py

# 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, extract_vt_symbol
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'

if __name__ == "__main__":

    # 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}')

    symbol_dict = get_stock_base()
    if len(sys.argv) >= 2 and sys.argv[1].lower() == 'all':
        stock_list = list(symbol_dict.keys())
        print('使用全量股票，共{}个'.format(len(stock_list)))
    else:
        # 更新本地合约缓存信息
        stock_list = load_json('stock_list.json')
        print('读取本地stock_list.json文件，共{}个'.format(len(stock_list)))


    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"

    count = 0
    # 逐一股票下载并更新
    for stock_code in stock_list:
        count += 1
        print('下载进度:{}%'.format(round(count* 100/len(stock_list), 4)))
        if '.' not in stock_code:
            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 = stock_code
            vt_symbol = f'{stock_code}.{exchange.value}'
        else:
            vt_symbol = stock_code
            symbol, exchange = extract_vt_symbol(vt_symbol)
            if exchange == Exchange.SSE:
                exchange_name = '上交所'
                exchange_code = 'sh'
            else:
                exchange_name = '深交所'
                exchange_code = 'sz'

        symbol_info = symbol_dict.get(vt_symbol)
        if symbol_info['类型'] == '指数':
            continue
        stock_name = symbol_info.get('name')
        print(f'开始更新:{exchange_name}/{stock_name}, 代码:{symbol}')
        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'{symbol}_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_dt}')
        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_dt}')

        rs = bs.query_history_k_data_plus(
            code=f'{exchange_code}.{symbol}',
            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': symbol,
                '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{vt_symbol}数据 => 文件{bar_file_path}, 最后记录:{bars[-1]}')


    print('更新完毕')
    bs.logout()
    os._exit(0)