@巴罗斯 我这测试是有的
```
# 导入函数库
import jqdata
# 初始化函数，设定基准等等
def initialize(context):
# 设定沪深300作为基准
set_benchmark('000300.XSHG')
# 开启动态复权模式(真实价格)
set_option('use_real_price', True)
df = get_fundamentals(query(
valuation.code, valuation.market_cap, valuation.pe_ratio, income.total_operating_revenue
).filter(
valuation.market_cap > 1000,
valuation.pe_ratio < 10,
income.total_operating_revenue > 2e10
).order_by(
# 按市值降序排列
valuation.market_cap.desc()
))
log.info('1:', len(df))
# 过滤掉order系列API产生的比error级别低的log
# log.set_level('order', 'error')
### 股票相关设定 ###
# 股票类每笔交易时的手续费是：买入时佣金万分之三，卖出时佣金万分之三加千分之一印花税, 每笔交易佣金最低扣5块钱
set_order_cost(OrderCost(close_tax=0.001, open_commission=0.0003, close_commission=0.0003, min_commission=5), type='stock')
## 运行函数（reference_security为运行时间的参考标的；传入的标的只做种类区分，因此传入'000300.XSHG'或'510300.XSHG'是一样的）
# 开盘前运行
run_daily(before_market_open, time='before_open', reference_security='000300.XSHG')
# 开盘时或每分钟开始时运行
run_daily(market_open, time='every_bar', reference_security='000300.XSHG')
# 收盘后运行
run_daily(after_market_close, time='after_close', reference_security='000300.XSHG')
def before_trading_start(context):
df = get_fundamentals(query(
valuation.code, valuation.market_cap, valuation.pe_ratio, income.total_operating_revenue
).filter(
valuation.market_cap > 1000,
valuation.pe_ratio < 10,
income.total_operating_revenue > 2e10
).order_by(
# 按市值降序排列
valuation.market_cap.desc()
))
log.info('2:', len(df))
def before_market_open(context):
df = get_fundamentals(query(
valuation.code, valuation.market_cap, valuation.pe_ratio, income.total_operating_revenue
).filter(
valuation.market_cap > 1000,
valuation.pe_ratio < 10,
income.total_operating_revenue > 2e10
).order_by(
# 按市值降序排列
valuation.market_cap.desc()
))
log.info('3:', len(df))
## 开盘时运行函数
def market_open(context):
pass
## 收盘后运行函数
def after_market_close(context):
pass
```
![TIM截图20171013094220.png][1]
[1]: https://image.joinquant.com/c3f0f07e3eb67272ab750fead6124b74
2017-10-13
雪球
