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Why Blankly?
β Blankly is a live trading engine, backtest runner and development framework wrapped into one powerful open source package. Models can be instantly backtested, paper traded, sandbox tested and run live by simply changing a single line. We built blankly for every type of quant including training & running ML models in the same environment, cross-exchange/cross-symbol arbitrage, and even long/short positions on stocks (all with built-in websockets).
β Convert your existing model or build a new one - unlock the ability to run & optimize across all of our supported exchanges. Getting started is easy - just pip install blankly
and blankly init
.
Sponsored Promotion
Check out our website and our docs.
YouTube - Under 25 Lines Build an Alpaca RSI Trading Bot
Trade Stocks, Crypto, and Forex Seamlessly
from blankly import Alpaca, CoinbasePro
stocks = Alpaca()
crypto = CoinbasePro()
# Easily perform the same actions across exchanges & asset types
stocks.interface.market_order('AAPL', 'buy', 1)
crypto.interface.market_order('BTC-USD', 'buy', 1)
Backtest your trades, events, websockets, and custom data
import blankly
"""
This example shows how backtest over tweets
"""
class TwitterBot(blankly.Model):
def main(self, args):
while self.has_data:
self.backtester.value_account()
self.sleep('1h')
def event(self, type_: str, data: str):
# Now check if it's a tweet about Tesla
if 'tsla' in data.lower() or 'gme' in data.lower():
# Buy, sell or evaluate your portfolio
pass
if __name__ == "__main__":
exchange = blankly.Alpaca()
model = TwitterBot(exchange)
# Add the tweets json here
model.backtester.add_custom_events(blankly.data.EventReader('./tweets.json'))
# Now add some underlying prices at 1 month
model.backtester.add_prices('TSLA', '1h', start_date='3/20/22', stop_date='4/15/22')
# Backtest or run live
print(model.backtest(args=None, initial_values={'USD': 10000}))
Check out alternative data examples here
Accurate Backtest Holdings
Check out the demo link here.
Iterate & Train using your Metrics, Trades and Performance
Blankly Metrics:
Compound Annual Growth Rate (%): 54.0%
Cumulative Returns (%): 136.0%
Max Drawdown (%): 60.0%
Variance (%): 26.15%
Sortino Ratio: 0.9
Sharpe Ratio: 0.73
Calmar Ratio: 0.99
Volatility: 0.05
Value-at-Risk: 358.25
Conditional Value-at-Risk: 34.16
Go Live in One Line
Seamlessly run your model live!
# Just turn this
strategy.backtest(to='1y')
# Into this
strategy.start()
Dates, times, and scheduling adjust on the backend to make the experience instant.
Quickstart
Installation
- First install Blankly using
pip
. Blankly is hosted on PyPi.
$ pip install blankly
- Next, just run:
$ blankly init
This will initialize your working directory.
The command will create the files keys.json
, settings.json
, backtest.json
, blankly.json
and an example script called bot.py
.
If you don't want to use our init
command, you can find the same files in the examples
folder under settings.json
and keys_example.json
- From there, insert your API keys from your exchange into the generated
keys.json
file or take advantage of the CLI keys prompt.
More information can be found on our docs
Directory format
The working directory format should have at least these files:
Project
|-bot.py
|-keys.json
|-settings.json
Additional Info
Make sure you're using a supported version of python. The module is currently tested on these versions:
- Python 3.7
- Python 3.8
- Python 3.9
- Python 3.10
For more info, and ways to do more advanced things, check out our getting started docs.
Supported Exchanges
Exchange | Live Trading | Websockets | Paper Trading | Backtesting |
---|---|---|---|---|
Coinbase Pro | π’ | π’ | π’ | π’ |
Binance | π’ | π’ | π’ | π’ |
Alpaca | π’ | π’ | π’ | π’ |
OANDA | π’ | π’ | π’ | |
FTX | π’ | π’ | π’ | π’ |
KuCoin | π’ | π’ | π’ | π’ |
Okx | π’ | π’ | π’ | π’ |
Kraken | π‘ | π‘ | π‘ | π‘ |
Keyless Backtesting | π’ | |||
TD Ameritrade | π΄ | π΄ | π΄ | π΄ |
Webull | π΄ | π΄ | π΄ | π΄ |
Robinhood | π΄ | π΄ | π΄ | π΄ |
π’ = working
π‘ = in development, some or most features are working
π΄ = planned but not yet in development
RSI Example
We have a pre-built cookbook examples that implement strategies such as RSI, MACD, and the Golden Cross found in our examples.
The model below will run an RSI check every 30 minutes - buying below 30 and selling above 70. Try switching the exchange and assets and see how it instantly works on Binance, Coinbase Pro or anything else you trade on.
import blankly
from blankly import StrategyState
def price_event(price, symbol, state: StrategyState):
""" This function will give an updated price every 15 seconds from our definition below """
state.variables['history'].append(price)
rsi = blankly.indicators.rsi(state.variables['history'])
if rsi[-1] < 30 and not state.variables['has_bought']:
# Dollar cost average buy
state.variables['has_bought'] = True
state.interface.market_order(symbol, side='buy', size=1)
elif rsi[-1] > 70 and state.variables['has_bought']:
# Dollar cost average sell
state.variables['has_bought'] = False
state.interface.market_order(symbol, side='sell', size=1)
def init(symbol, state: StrategyState):
# Download price data to give context to the algo
state.variables['history'] = state.interface.history(symbol, to='1y', return_as='list')['open']
state.variables['has_bought'] = False
if __name__ == "__main__":
# Authenticate on alpaca to create a strategy
alpaca = blankly.Alpaca()
# Use our strategy helper on alpaca
strategy = blankly.Strategy(alpaca)
# Run the price event function every time we check for a new price - by default that is 15 seconds
strategy.add_price_event(price_event, symbol='NCLH', resolution='30m', init=init)
strategy.add_price_event(price_event, symbol='CRBP', resolution='1h', init=init)
strategy.add_price_event(price_event, symbol='D', resolution='15m', init=init)
strategy.add_price_event(price_event, symbol='GME', resolution='30m', init=init)
# Start the strategy. This will begin each of the price event ticks
# strategy.start()
# Or backtest using this
strategy.backtest(to='1y')
Other Info
Subscribe to our news!
https://blankly.substack.com/p/coming-soon
Bugs
Please report any bugs or issues on the GitHub's Issues page.
Disclaimer
Trading is risky. We are not responsible for losses incurred using this software, software fitness for any particular purpose, or responsibility for any issues or bugs. This is free software.
Contributing
If you would like to support the project, pull requests are welcome. You can also contribute just by telling us what you think of Blankly: https://forms.gle/4oAjG9MKRTYKX2hP9
Licensing
Blankly is distributed under the LGPL License. See the LICENSE for more details.
New updates every day πͺ.