GenericCSVData does not take time, only takes date

bng

import backtrader as bt

class Database:

def __init__(self, timeStamp):
    self.timeStamp= timeStamp.upper()
    
def getBtCSVdata(self):
    '''
    This method will return backtrader CSV data to feed directly
    '''
    fn = 'D://Data//your_csv_file.csv'
    if self.timeStamp == 'DAY':
        # For daily data
        dateformat = '%Y-%m-%d'
        timeformat = None
    else:
        # For 1min or 5min or 15min or 30min data
        dateformat = '%Y-%m-%d %H:%M:%S'
        timeformat = '%H:%M:%S'
    
    btCSVData = bt.feeds.GenericCSVData(dataname=fn,
                                   header = False,
                                   dtformat = dateformat,
                                   tmformat = timeformat,
                                   nullvalue = 0.0,
                                   datetime = 0,
                                   open = 1,
                                   high = 2,
                                   low = 3,
                                   close = 4,
                                   volume = 5,
                                   openinterest = -1)
    
    return btCSVData

#==========================================================

class TestStrategy(bt.Strategy):

def log(self, txt, dt=None):
    ''' Logging function for this strategy'''
    dt = dt or self.datas[0].datetime.datetime(0)
    print('%s, %s' % (dt.isoformat(), txt))

def __init__(self):
    # Keep a reference to the "close" line in the data[0] dataseries
    self.dataclose = self.datas[0].close

def next(self):
    # Simply log the closing price of the series from the reference
    self.log('Close, %.2f' % self.dataclose[0])

if name == 'main':

cerebro = bt.Cerebro()

# Add a strategy
cerebro.addstrategy(TestStrategy)

# Create a Data Feed
ds = Database('1min')
#ds.updateFromAlphavantage()

data1 = ds.getBtCSVdata()

# Add the Data Feed to Cerebro
cerebro.adddata(data1)

# Set our desired cash start
cerebro.broker.setcash(100000.0)

# Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

# Run over everything
cerebro.run()

# Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())

#=================================
My CSV data are as follows:

2019-03-13 15:25:00,148.70,148.80,148.70,148.70,92180,0.00
2019-03-13 15:26:00,148.55,148.65,148.55,148.60,102998,0.00
2019-03-13 15:27:00,148.55,148.60,148.45,148.45,98636,0.00
2019-03-13 15:28:00,148.50,148.60,148.50,148.55,73246,0.00
2019-03-13 15:29:00,148.55,148.75,148.45,148.75,75646,0.00
#=======================================
The output of backtrader is follows:

Starting Portfolio Value: 100000.00
2019-03-13T23:59:59.999989, Close, 148.60
2019-03-13T23:59:59.999989, Close, 148.45
2019-03-13T23:59:59.999989, Close, 148.55
2019-03-13T23:59:59.999989, Close, 148.75
Final Portfolio Value: 100000.00
#====================
How do I import the CORRECT time data in my programme?

ab_trader

You need to specify timeframe and compression for data feed added.

bng

Thank you @ab_trader very much to help me.

benmercerdev

@ab_trader where do you add these parameters?

run-out

Have a look here.

benmercerdev

@run-out great, thank you.

P Jr G

@benmercerdev I had same problem. I solved it by following the suggestion of ab_trader. Now my custom csv method looks like:

class my_custom_csv(bt.feeds.GenericCSVData):
    params = (
        ('dtformat', '%Y-%m-%d %H:%M:%S'),
        ...
        ('timeframe', bt.TimeFrame.Minutes),
        ('compression', 1),
    )

Adding timeframe and compression solved it for me.

ab_trader

@P-Jr-G these parameters are already in the data feed class, no need to add them one more time when you define your own data feed class. You just need to call your data feed as follows:

data = my_custom_csv(path_to_data_file, timeframe=bt.TimeFrame.YourTimeFrame_here)