alpaca-backtrader-api is a python library for the Alpaca trade API within backtrader framework. It allows rapid trading algo development easily, with support for the both REST and streaming interfaces. For details of each API behavior, please see the online API document.

Note this module supports only python version 3.5 and above, due to the underlying library alpaca-trade-api.

$ pip3 install alpaca-backtrader-api

you can find example strategies in the samples folder.

remember to add you credentials.

you can toggle between backtesting and paper trading by changing ALPACA_PAPER

In order to call Alpaca's trade API, you need to obtain API key pairs. Replace <key_id> and <secret_key> with what you get from the web console.

import alpaca_backtrader_api
import backtrader as bt
from datetime import datetime

ALPACA_API_KEY = <key_id>
ALPACA_SECRET_KEY = <secret_key>
ALPACA_PAPER = True


class SmaCross(bt.SignalStrategy):
  def __init__(self):
    sma1, sma2 = bt.ind.SMA(period=10), bt.ind.SMA(period=30)
    crossover = bt.ind.CrossOver(sma1, sma2)
    self.signal_add(bt.SIGNAL_LONG, crossover)


cerebro = bt.Cerebro()
cerebro.addstrategy(SmaCross)

store = alpaca_backtrader_api.AlpacaStore(
    key_id=ALPACA_API_KEY,
    secret_key=ALPACA_SECRET_KEY,
    paper=ALPACA_PAPER
)

if not ALPACA_PAPER:
  broker = store.getbroker()  # or just alpaca_backtrader_api.AlpacaBroker()
  cerebro.setbroker(broker)

DataFactory = store.getdata  # or use alpaca_backtrader_api.AlpacaData
data0 = DataFactory(dataname='AAPL', historical=True, fromdate=datetime(
    2015, 1, 1), timeframe=bt.TimeFrame.Days)
cerebro.adddata(data0)

print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.run()
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.plot()

The HTTP API document is located in https://docs.alpaca.markets/

The Alpaca API requires API key ID and secret key, which you can obtain from the web console after you sign in. You can set them in the AlpacaStore constructor, using 'key_id' and 'secret_key'.

The 'paper' parameter is default to False, which allows live trading. If you set it to True, then you are in the paper trading mode.

There's a way to execute an algorithm with multiple datas or/and execute more than one algorithm.
The websocket connection is limited to 1 connection per account. Alpaca backtrader opens a websocket connection for each data you define.
For that exact purpose this was created
The steps to execute this are:

• Run the Alpaca Proxy Agent as described in the project's README
• Define this env variable: DATA_PROXY_WS to be the address of the proxy agent. (e.g: DATA_PROXY_WS=ws://192.168.99.100:8765)
• execute your algorithm. it will connect to the servers through the proxy agent allowing you to execute multiple datas/strategies

For technical issues particular to this module, please report the issue on this GitHub repository. Any API issues can be reported through Alpaca's customer support.

New features, as well as bug fixes, by sending pull request is always welcomed.