def get_history_data(self, code_list, frequency="1min", n=1):
"""
获取历史数据
:param code_list:
:param frequency: k线数据级别
:param n: (当天)前n个交易日 n = QA_util_get_trade_gap(start_date, today_)
:return:
"""
# TODO 历史数据部分应放在策略计算，而不是数据采集部分
# TODO get history bar data
# TODO 调用QA_fetch_stock_min_adv(code, start, end) 从数据库获取数据
today = datetime.datetime(self.cur_year, self.cur_month,
self.cur_day).isoformat()[:10]
start_date = QA_util_get_pre_trade_date(cursor_date=today, n=n)[:10]
end_date = QA_util_get_pre_trade_date(cursor_date=today, n=1)[:10]
# start='2019-05-08', end='2019-05-09' means start from 2019-05-08 9:30 and end to 2019-05-09 15:00
data = None
try:
data = QA_fetch_stock_min_adv(code_list,
start=start_date,
end=end_date)
except Exception as e:
logger.error("fetch stock min history data failure. " +
e.__str__())
if data is not None:
for code in data.code.to_list():
qa_data = data.select_code(code)
if qa_data is not None:
# TODO 规定标准columns
self.publish_msg(qa_data.data.to_msgpack())
else:
lens = 0 # initial data len
if frequency in ['5', '5m', '5min', 'five']:
lens = 48 * n
elif frequency in ['1', '1m', '1min', 'one']:
lens = 240 * n
elif frequency in ['15', '15m', '15min', 'fifteen']:
lens = 16 * n
elif frequency in ['30', '30m', '30min', 'half']:
lens = 8 * n
elif frequency in ['60', '60m', '60min', '1h']:
lens = 4 * n
lens = 20800 if lens > 20800 else lens
# TODO 如果获取失败则在线获取 参考save stock min
# data = self.get_security_bar_concurrent(code_list, frequency, lens)
# TODO 规定标准columns
# self.publish_msg(qa_data.data.to_msgpack())
pass
def __init__(
self,
market_type,
frequence,
start,
end,
code_list,
commission_fee,
):
self.user = QA_User()
self.if_settled = False
self.account = None
self.portfolio = None
self.market = QA_Market()
self.market_type = market_type
self.frequence = frequence
self.broker = QA_BacktestBroker(commission_fee)
self.broker_name = 'backtest_broker'
self.start = start
self.end = end
self.code_list = code_list
if self.market_type is MARKET_TYPE.STOCK_CN and self.frequence is FREQUENCE.DAY:
self.ingest_data = QA_fetch_stock_day_adv(
self.code_list, self.start, self.end).to_qfq().panel_gen
elif self.market_type is MARKET_TYPE.STOCK_CN and self.frequence[
-3:] == 'min':
self.ingest_data = QA_fetch_stock_min_adv(
self.code_list, self.start, self.end,
self.frequence).to_qfq().panel_gen
def get(self):
"""
采用了get_arguents来获取参数
默认参数: code-->000001 start-->2017-01-01 09:00:00 end-->now
"""
code = self.get_argument('code', default='000001')
start = self.get_argument('start', default='2017-01-01 09:00:00')
end = self.get_argument('end', default=str(datetime.datetime.now()))
frequence = self.get_argument('frequence', default='1min')
if_fq = self.get_argument('if_fq', default=False)
if if_fq:
data = QA_util_to_json_from_pandas(
QA_fetch_stock_min_adv(code, start, end,
frequence).to_qfq().data)
self.write({'result': data})
else:
data = QA_util_to_json_from_pandas(
QA_fetch_stock_min(code,
start,
end,
format='pd',
frequence=frequence))
self.write({'result': data})
self.write({'result': data})
def __init__(
self,
market_type,
frequence,
start,
end,
code_list,
commission_fee,
username='******',
password='******',
portfolio_cookie='qatestportfolio'
):
"""
:param market_type: 回测的市场 MARKET_TYPE.STOCK_CN ，
:param frequence: 'day' '1min' '5min' '15min' '30min' '60min'
:param start: 开始日期
:param end: 结束日期
:param code_list: 股票代码池
:param commission_fee: 交易佣金
"""
self.user = QA_User(username=username, password=password)
self.if_settled = False
self.account = None
self.portfolio = self.user.new_portfolio(portfolio_cookie)
# 🛠todo market_type 应该放在 QA_Market对象里的一个属性
self.market = QA_Market(if_start_orderthreading=True)
self.market_type = market_type
self.frequence = frequence
self.broker = QA_BacktestBroker(commission_fee)
self.broker_name = 'backtest_broker'
self.start = start
self.end = end
self.code_list = code_list
# 🛠todo 检查start日期和结束end日期是否正确
# 🛠todo 检查code list 是否合法
# 根据 市场类型，回测周期频率， 和股票代码列表 获取回测数据
if self.market_type is MARKET_TYPE.STOCK_CN and self.frequence is FREQUENCE.DAY:
# 获取日线级别的回测数据
self.ingest_data = QA_fetch_stock_day_adv(
self.code_list,
self.start,
self.end
).to_qfq().panel_gen
elif self.market_type is MARKET_TYPE.STOCK_CN and self.frequence[
-3:] == 'min':
# 获取分钟级别的回测数据
self.ingest_data = QA_fetch_stock_min_adv(
self.code_list,
self.start,
self.end,
self.frequence
).to_qfq().panel_gen
else:
QA_util_log_info("{} 的市场类型没有实现！".format(market_type))
def __init__(
self,
market_type,
frequence,
start,
end,
code_list,
commission_fee,
):
"""
:param market_type: 回测的市场 MARKET_TYPE.STOCK_CN ，
:param frequence: 'day' '1min' '5min' '15min' '30min' '60min'
:param start: 开始日期
:param end: 结束日期
:param code_list: 股票代码池
:param commission_fee: 交易佣金
"""
self.user = QA_User()
self.if_settled = False
self.account = None
self.portfolio = None
self.market = QA_Market()
self.market_type = market_type
self.frequence = frequence
self.broker = QA_BacktestBroker(commission_fee)
self.broker_name = 'backtest_broker'
self.start = start
self.end = end
self.code_list = code_list
if self.market_type is MARKET_TYPE.STOCK_CN and self.frequence is FREQUENCE.DAY:
self.ingest_data = QA_fetch_stock_day_adv(
self.code_list, self.start, self.end).to_qfq().panel_gen
elif self.market_type is MARKET_TYPE.STOCK_CN and self.frequence[
-3:] == 'min':
self.ingest_data = QA_fetch_stock_min_adv(
self.code_list, self.start, self.end,
self.frequence).to_qfq().panel_gen
else:
QA_util_log_info("{} 的市场类型没有实现！".format(market_type))