#STEP2：log
logger.info("Starting yiboduo strategy for: %s"%SYMBOL)
api = TqApi(TqSim())
klines = api.get_kline_serial(SYMBOL, duration_seconds=60*60*24, data_length=20)
#ticks = api.get_tick_serial(SYMBOL)
quote = api.get_quote(SYMBOL)
while True:
api.wait_update()
# 跟踪log信息，日k数据会产生两个信号：一个是开盘时，另一个时收盘；如果想根据收盘k线分析前期趋势，用第二个信号
# 这样就没有之前认为必须开盘才能分析之前所存在的趋势型机会了。
# 实盘是只要14：59或盘后任何时间触发运行即可，一次退出；
# 想尾盘参与策略型机会则收盘前运行回报策略型机会，次日择机参与则盘后任何时间运行即可
if api.is_changing(klines):
df = klines.to_dataframe()
#logger.info("DATE: %s, close: %f"%(get_market_day(klines[-1]["datetime"]), klines[-1]["close"]))
trading_date = bases.get_market_day(klines[-1]["datetime"])
#STEP3-策略型机会判定
#logger.info("DEBUG: high is %s, close is %fLIANGBODUO"%(klines[-1]["high"], klines[-1]["close"]))
is_yiboduo = stgy4zd.yi_bo_duo(quote, klines, logger)
if is_yiboduo:
logger.info("MYSTRATEGY - YIBODUO date: %s, for %s" %(trading_date, SYMBOL))
#实盘只要收盘后跑一次即可确定
break
api.close()
logger.removeHandler(fh)
# 交易预警参数
k_count = 0
signal_interval = 10
short_price = 0.0
sum_profit = 0.0
last_kong_index = 0
kaipan_di = False
while True:
api.wait_update()
# 新产生一根K线计算分时均价，判断滞涨止跌信号
if api.is_changing(klines[-1], "datetime"):
df = klines.to_dataframe()
trading_date = bases.get_market_day(klines[-1]["datetime"])
if trading_date != cur_trading_date:
current_volume = 0
traded_volume = 0
#logger.info("###%s, %s",trading_date, cur_trading_date)
cur_trading_date = trading_date
# workaround: ignore the first signal for kline with last day's close
df["date"] = df.datetime.apply(lambda x: bases.get_market_day(x))
df = df[(df["date"] == cur_trading_date)]
if len(df) > 1:
continue
df["time"] = df.datetime.apply(lambda x: bases.get_kline_time(x))
df["date"] = df.datetime.apply(lambda x: bases.get_market_day(x))
df = df[(df["date"] == cur_trading_date)]
