i can't figure out extending lines
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hell all,
no matter how many examples i try, i can't seem to get my columns to use.
i must have an error in what exactly i am calling to use on the bt.indicators because they don't match with the values in my dataframe...
and i think processing would be a lot faster if i only needed to calculate from my already known values..
this is for monitoring right now....sorry, again, i tried pasting but it came out like below..
here is my code..
data = pd.read_sql("""
select datetime, open, high, low, close, volume, sma_20, sma_50, ema_8, mom, lin_ang
from stock_price_15
where symbol = :symbol
and sma_50 is not 0
and datetime > '2021-01-26'
and strftime('%H:%M:%S', datetime) >= '09:30:00'
and strftime('%H:%M:%S', datetime) < '16:00:00'
order by datetime asc
""", conn, params={"symbol": stock['symbol']}, index_col='datetime', parse_dates=['datetime'])data = bt.feeds.PandasDirectData(dataname=data) cerebro.adddata(data)#CREATES THIS DF
== Analysing A ==
open high low close volume sma_20 sma_50 ema_8 mom
datetime
2021-01-26 09:30:00 125.50 125.95 124.550 125.040 92435 125.072505 125.919682 125.203493 0
2021-01-26 09:45:00 125.09 125.16 124.430 125.005 88188 125.070255 125.887382 125.159384 0
2021-01-26 10:00:00 125.04 125.36 124.740 124.845 39486 125.055005 125.850682 125.089521 0
2021-01-26 10:15:00 124.82 125.29 124.630 125.210 29410 125.072005 125.819482 125.116294 0
2021-01-26 10:30:00 125.24 125.66 125.170 125.550 43447 125.119005 125.791882 125.212673 0
... ... ... ... ... ... ... ... ... ...
2021-01-28 10:45:00 121.18 121.68 121.180 121.400 40882 120.019275 121.871370 120.669654 0
2021-01-28 11:00:00 121.43 121.89 121.340 121.870 43707 120.081025 121.810170 120.936397 0
2021-01-28 11:15:00 121.87 122.04 121.390 121.640 53618 120.141025 121.746970 121.092753 0
2021-01-28 11:30:00 121.65 122.25 121.550 122.195 37105 120.213775 121.691670 121.337697 0
2021-01-28 11:45:00 122.25 122.67 122.115 122.500 54387 120.31then.............
create a Strategy
class OpeningRangeBreakout(bt.Strategy):
#class TestStrategy(bt.Strategy):
params = (
dict(num_opening_bars=15)
)def log(self, txt, dt=None): ''' Logging function for this strategy''' if dt is None: dt = self.datas[0].datetime.datetime(0) print('%s, %s' % (dt, txt)) ########## DEFINING THE TEMPLATE AND VARIABLES TO USE def __init__(self): self.dataclose = self.datas[0].close self.opening_range_low = 0 self.opening_range_high = 0 self.opening_range = 0 self.bought_today = False self.order = None self.buyprice = None self.buycomm = None ## ADD INDICATORS ########### self.sma_20 = bt.indicators.SimpleMovingAverage( self.datas[0], period=20) self.sma_50 = bt.indicators.SimpleMovingAverage( self.datas[0], period=50) # Indicators for the plotting show self.ema_8 = bt.indicators.ExponentialMovingAverage(self.datas[0], period=8)def next(self):
######### THE CURRENT SESSION ######################################### current_bar_ = self.data.num2date(self.data.datetime[0]) previous_bar = self.data.num2date(self.data.datetime[-1]) two__bars_back = self.data.num2date(self.data.datetime[-2]) three_bars_back = self.data.num2date(self.data.datetime[-3]) -
@bobaleaux said in i can't figure out extending lines:
sorry, again, i tried pasting but it came out like below..
Use backticks as stated on top of the page to make code and output blocks readable.
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@ab_trader
thanks... wish extending lines was so straight forward...i am so new to coding withthe volume of information i'm trying digest i skim over way too many details that make things work...
and end up here....any assistance will be greatly appreciated
data = pd.read_sql(""" select datetime, open, high, low, close, volume, sma_20, sma_50, ema_8, mom, lin_ang from stock_price_15 where symbol = :symbol and sma_50 is not 0 and datetime > '2021-01-26' and strftime('%H:%M:%S', datetime) >= '09:30:00' and strftime('%H:%M:%S', datetime) < '16:00:00' order by datetime asc """, conn, params={"symbol": stock['symbol']}, index_col='datetime', parse_dates=['datetime']) data = bt.feeds.PandasDirectData(dataname=data) cerebro.adddata(data)
class OpeningRangeBreakout(bt.Strategy): params = ( dict(num_opening_bars=15) ) def log(self, txt, dt=None): ''' Logging function for this strategy''' if dt is None: dt = self.datas[0].datetime.datetime(0) print('%s, %s' % (dt, txt)) def __init__(self): self.dataclose = self.datas[0].close # To keep track of self.opening_range_low = 0 self.opening_range_high = 0 self.opening_range = 0 self.bought_today = False self.order = None self.buyprice = None self.buycomm = None ## ADD INDICATORS ########### self.sma_20 = bt.indicators.SimpleMovingAverage( self.datas[0], period=20) self.sma_50 = bt.indicators.SimpleMovingAverage( self.datas[0], period=50) # Indicators for the plotting show self.ema_8 = bt.indicators.ExponentialMovingAverage(self.datas[0], period=8) def next(self): current_bar_datetime = self.data.num2date(self.data.datetime[0]) previous_bar_datetime = self.data.num2date(self.data.datetime[-1]) two_bars_back = self.data.num2date(self.data.datetime[-2]) three_bars_back = self.data.num2date(self.data.datetime[-3]) self.log(self.data.close[0]) #self.log(self.datavolume[0]) #print(f'dataclose',(self.dataclose[0]) ) #print(f'ema_8', self.ema_8[0]) #print(f'sma_20', self.sma_20[0]) #print(f'sma_50', self.sma_50[0]) ############## THE FIRST SESSION OF THE NEW DAY ROUTE 1#################### if current_bar_datetime.date() != previous_bar_datetime.date(): self.opening_range_high = self.data.high[0] opening_high = self.data.high #print(f'opening high', opening_high[0]) self.opening_range_low = self.data.low[0] #print(f'opening range low',self.data.low[0]) #### OPENING RANGE ### opening_range_start_time = time(9, 30, 0) dt = datetime.combine(datetime.today(), opening_range_start_time) + timedelta(minutes=self.p.num_opening_bars) opening_range_end_time = dt.time() ################### print(f'opening close', self.dataclose[0]) -
@bobaleaux
I'm enclosing below as full sample of loading OHLCV from csv, adding in 20 adn 50 SMA, and then loading it into backtrader. I hope this helps you on your way.import backtrader as bt import pandas as pd import btalib class CustomDataLoader(bt.feeds.PandasData): """ An example of a pandas extraline loader. """ lines = ( "sma_20", "sma_50", ) params = ( ("sma_20", 5), ("sma_50", 6), ) datafields = bt.feeds.PandasData.datafields + (["sma_20", "sma_50",]) class Strategy(bt.Strategy): def log(self, txt, dt=None): """ Logging function fot this strategy""" dt = dt or self.data.datetime[0] if isinstance(dt, float): dt = bt.num2date(dt) print("%s, %s" % (dt, txt)) def print_signal(self): self.log( "o {:5.2f}\th {:5.2f}\tl {:5.2f}\tc {:5.2f}\tv {:5.0f}\t20 {:5.2f}\t50 {:5.2f}".format( self.datas[0].open[0], self.datas[0].high[0], self.datas[0].low[0], self.datas[0].close[0], self.datas[0].volume[0], self.datas[0].sma_20[0], self.datas[0].sma_50[0], ) ) def next(self): self.print_signal() if __name__ == "__main__": cerebro = bt.Cerebro() # Create dataframe with extended lines. datapath = "data/dev.csv" dataframe = pd.read_csv(datapath, header=None, parse_dates=True, index_col=0) dataframe.columns = ["high", "low", "open", "close", "cumvol", "volume"] dataframe["sma_20"] = btalib.sma(dataframe, period=20).df dataframe["sma_50"] = btalib.sma(dataframe, period=50).df dataframe = dataframe.dropna() dataframe = dataframe.iloc[:20, :] data = CustomDataLoader(dataname=dataframe) cerebro.adddata(data) cerebro.addstrategy(Strategy) # Execute cerebro.run() -
@run-out on this note.. what happens to the values of additional lines if one resample this input data ?
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resampling will ignore any non OHLC extra lines by default. See the following post ( and linked posts inside it ) for more info: https://community.backtrader.com/topic/2812/resample-for-extra-information-in-lines/2
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@vladisld Thanks.. very helpful
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@rajanprabu Thank you, Thank you, thank you!
