Importing orders #219

backtrader

From #219

Hello,
Is there a way to import orders from an array? I have them in an array that looks like [0,0,1,0,0,-1,-1...], length of this array is the same as the length of the data(one signal for each timeframe).

This is for backtesting only, the calculations are done outside of the testing script.

Or simpler, signals are saved in a csv with lines like this

2016-01-09;100200;-1
2016-01-09;110200;1

etc

backtrader

As explained above order importing is not a feature of the the platform.

If you have the data in that format:

....
2016-01-09;100200;-1
2016-01-10;110200;1
...

there are several approaches:

Make a custom data feed with it containing only 2 fields
- datetime
- trigger (or any other name you wish)
In this case you would add the data feed to the system and could at each moment in time and synchronized with the data read if an order has to be executed or not
Read that input with something like a pandas.read_csv module and during each call to next in the strategy, look for the corresponding datetime index in the dataframe to see if an order has to be executed or not.

muhammad haseeb

Initialize an empty list to store the orders.

Loop through each signal in the array. If the signal is not equal to zero, append a tuple to the list with the timestamp, price, and signal value.

Here's some sample code to illustrate this approach:

signals = [0, 0, 1, 0, 0, -1, -1, ...]
orders = []

for i in range(len(signals)):
if signals[i] != 0:
timestamp = # calculate the timestamp based on the index i
price = # calculate the price based on the index i and your data
signal = signals[i]
orders.append((timestamp, price, signal))

import csv

orders = []

with open('signals.csv', 'r') as f:
reader = csv.reader(f, delimiter=';')
for row in reader:
timestamp = row[0]
price = float(row[1])
signal = int(row[2])
orders.append((timestamp, price, signal))