🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package.
Home Page: https://package.blankly.finance
License: GNU Lesser General Public License v3.0
It appears that pip installs blankly under the folder Blankly (capitalized).
However, the documentation and the internal python scripts reference blankly with a lower letter.
A quickfix is to rename the Blankly folder in site-packages to blankly.
Traceback (most recent call last):
File "C:\Users\....\blankly\script.py", line 1, in <module>
import blankly
ModuleNotFoundError: No module named 'blankly'When trying to inter-operate the same strategy with various currencies, it'd be great to get a helper (a la trunc) to default to minimum possible resolution. For instance, BTC-USD resolution may be higher than SOL-USD.
blankly.utils.exceptions.InvalidOrder: Size resolution is too high, the highest resolution allowed for this symbol is: 0.01. You specified 60.405. Try using blankly.trunc(size, decimal_number) to match the exchange resolution.
Currently it seems it's only possible to trade Crypto/Forex with Blankly if you're located outside the US.
N/A
Connection to Interactive Brokers, maybe?
There is a problem with the current calculation.
account.pop('makerCommission') / 100
When makerCommission is 15, the maker_fee_rate value is 0.15. This is patently untrue.
Should It use the binance GET /sapi/v1/asset/tradeFee api to fetch the trade fee.
Hello,
I didn't find mentions about futures or shorting. Is it possible ?
I tried this
state.interface.limit_order(symbol, 'sell', price, quantity)
blankly.utils.exceptions.InvalidOrder: Not enough base currency. Available: 0.0. hold: 0. requested: 100
In our strategy_usage_example.py, the current implementation utilizes the local interface as a method to submit orders. This method of submitting orders is unpythonic and isn't as fit for development (for example when running in a jupyter notebook, unless the interface is defined before the function, the price_event function will not compile). Instead, the implementation should utilize the Order class that is defined in strategy/order.py of which the strategy_base should evaluate the order and make the necessary purchase for the user.
The fix should be to make sure that price_event returns a value (otherwise throw a ValueError) and translate the order into the necessary order types.
import Blankly
from Blankly.strategy.strategy_base import Strategy, Order
prices = []
def price_event(price, currency_pair):
prices.append(price)
sma50 = Blankly.analysis.calculate_sma(price, window=10)
if price > sma50:
return Order('market', currency_pair, 'buy', 10)
else:
return Order('market', currency_pair, 'sell', 10)
if __name__ == "__main__":
# Authenticate coinbase pro strategy
coinbase_pro = Blankly.Coinbase_Pro()
coinbase_strategy = Strategy(coinbase_pro)
coinbase_strategy.add_price_event(price_event, currency_pair='BTC-USD', resolution='15m')
coinbase_strategy.add_price_event(price_event, currency_pair='XLM-USD', resolution='15m')
coinbase_strategy.add_price_event(price_event, currency_pair='COMP-USD', resolution='15m')I'm trying the RSI code in colab and desktop pc, but I'm getting this error.
#RSI KODLARI
import blankly
def price_event(price, symbol, state: blankly.StrategyState):
""" This function will give an updated price every 15 seconds from our definition below """
state.variables['history'].append(price) # appends to the deque of historical prices
rsi = blankly.indicators.rsi(state.variables['history'])
if rsi[-1] < 30 and not state.variables['owns_position']:
buy = int(state.interface.cash / price)
state.interface.market_order(symbol, side='buy', size=buy)
state.variables['owns_position'] = True
elif rsi[-1] > 70 and state.variables['owns_position']:
curr_value = int(state.interface.account[state.base_asset].available)
state.interface.market_order(symbol, side='sell', size=curr_value)
state.variables['owns_position'] = False
def init(symbol, state: blankly.StrategyState):
# Download price data to give context to the algo
state.variables['history'] = state.interface.history(symbol, to=150, return_as='deque')['close']
state.variables['owns_position'] = False
if __name__ == "__main__":
exchange = blankly.Binance(portfolio_name="ATD Binance")
strategy = blankly.Strategy(exchange)
strategy.add_price_event(price_event, symbol='ETH-BUSD', resolution='15m', init=init)
# Start the strategy. This will begin each of the price event ticks
# strategy.start()
# Or backtest using this
results = strategy.backtest(to='1y', initial_values={'BUSD': 1000})
print(results)JSONDecodeError: Expecting value: line 10 column 5 (char 364)
I'm struggling with setting risk_free_return_rate and see it propagated when printing results from a backtest. Could you please help?
{
"price_data": {
...
},
"settings": {
...
"risk_free_return_rate": 0.01
}
}
Blankly Metrics:
Compound Annual Growth Rate (%): 661.0%
Cumulative Returns (%): 64.0%
Max Drawdown (%): 8.0%
Variance (%): 6.36%
Sortino Ratio: 4.92
Sharpe Ratio: 3.68
Calmar Ratio: 19.29
Volatility: 0.03
Value-at-Risk: 654.94
Conditional Value-at-Risk: 24.68
Risk Free Return Rate: 0.0
Resampled Time: 86400.0
Tested on last main branch installed using pip.
I am not sure if some in the financial services industry would be comfortable with a *GPL license. I think something like AL 2.0, MIT, BSD would be better for wider usage and adaptation. Is there a particular reason a *GPL license has been used?
First of all, congratz on your work on Blankly. I've also used Freqtrade and Backtrader and even though they provide other capabilities that you don't, you rock on making this framework simple to use.
I'm developing a strategy using Artificial Neural Networks trained using Genetic Algorithms. In here, I need to run multiple back tests in order to calculate the fitness of each individual. For this, I'm using Blankly backtest where I need to initialize an Exchange. I was using Alpaca but during initialization and execution, it performs some HTTPS calls that slows down the training (even if they are just a few). I switched to KeyLess exchange but I noticed that it mocks the OHCLV data (reference).
Would be nice to have this Exchange (or maybe another exchange) to provide all the OHCLV data. Maybe one exchange that requires a directory with multiple CSV files, one per Symbol (maybe similar to the ones generated by the backtests on the price_cache folder).
Maybe other people needs this feature to perform offline trainings and backtests using the full OHCLV data. Just as a silly example, I want to code while I'm flying without internet connectivity and be able to tests my strategy which uses volume indicators.
I would like to provide a folder that will contains all the CSV files that can be consumed by this Exchange. For instance:
if __name__ == "__main__":
exchange = blankly.CSVExchange(folder='price_caches', initial_account_values={'USD': 100000})
strategy = blankly.Strategy(exchange)
strategy.add_bar_event(self.bar_event, 'AAPL', resolution='1d', init=self.init)
strategy.backtest(start_date="20/10/2021", end_date="01/03/2022")
In here, the folder might have the following files:
AAPL,1614793059,1646329059,86400.csvTSLA,1634688000,1641168000,1800.csvHow would you implement this?
As mentioned, I'll probably do something quite similar to the KeylessExchange but instead of providing a file, I'll read each file on a folder looking for CSV files that follows the cached prices format and in their header have the high,low,volume,close,open,time. Then I'll somehow do a lazy load of those files (depending the symbols and date range that is needed)
Additional Information
whatever I do, I can't get past the "symbol not found" error.
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:
# Dollar cost average buy
state.interface.market_order(symbol, side='buy', funds=10)
elif rsi[-1] > 70:
# Dollar cost average sell
state.interface.market_order(symbol, side='sell', funds=10)
def init(symbol, state: StrategyState):
# Download price data to give context to the algo
state.variables['history'] = state.interface.history(symbol, start_date = "2021-08-01", end_date = "2021-08-28", return_as='list')['close']
if __name__ == "__main__":
binance = blankly.Binance(portfolio_name="ATD Binance")
binance_strategy = blankly.Strategy(binance)
binance_strategy.add_price_event(price_event, symbol='ETH-USDT', resolution='1h', init=init)
# Start the strategy. This will begin each of the price event ticks
# binance_strategy.start()
# Or backtest using this
binance_strategy.backtest(start_date = "2021-08-01", end_date = "2021-08-28",
initial_values={'USDT': 100}){
"settings": {
"account_update_time": 5000,
"use_sandbox": false,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "com"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD"
}
}
}{
"price_data": {
"assets": [
[ "ETH-USDT", 1546290000, 1630270800, 300.0 ],
[ "ETH-USDT", 1546290000, 1630270800, 900.0 ],
[ "ETH-USDT", 1546290000, 1630270800, 1800.0 ],
[ "ETH-USDT", 1546290000, 1630270800, 3600.0 ],
[ "ETH-USDT", 1546290000, 1630270800, 14400.0 ],
[ "ETH-USDT", 1546290000, 1630270800, 21600.0 ],
[ "ETH-USDT", 1546290000, 1630270800, 86400.0 ]
]
},
"settings": {
"use_price": "close",
"smooth_prices": false,
"GUI_output": true,
"show_tickers_with_zero_delta": false,
"save_initial_account_value": true,
"show_progress_during_backtest": true,
"cache_location": "./price_caches",
"resample_account_value_for_metrics": "1d",
"quote_account_value_in": "USDT",
"ignore_user_exceptions": false
}
}Including: ETH-USDT,1546290000,1630270800,300.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,900.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,1800.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,3600.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,14400.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,21600.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,86400.0.csv in backtest.
Including: ETH-USDT,1627776000.0,1630108800.0,3600.0.csv in backtest.
Including: ETH-USDT,1598774943.8658986,1630310943.8658986,3600.0.csv in backtest.
No exact cache exists for ETH-USDT from 1630310996.5534158 to 1630311056.5534158 at 3600.0s resolution. Downloading...
already identified
Initializing...
1630098000.0
Traceback (most recent call last):
File "C:\Blankly\RSI-strategy.py", line 30, in <module>
binance_strategy.backtest(start_date = "2021-08-01", end_date = "2021-08-28",
File "c:\python39\lib\site-packages\blankly\strategy\strategy_base.py", line 473, in backtest
results = self.backtesting_controller.run()
File "c:\python39\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 397, in run
available_dict, no_trade_dict = self.format_account_data(self.initial_time)
File "c:\python39\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 221, in format_account_data
true_account[i] = self.interface.get_account(i)
File "c:\python39\lib\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade_interface.py", line 298, in get_account
raise KeyError("Symbol not found.")
KeyError: 'Symbol not found.'C:\Blankly>RSI-strategy.py
Including: ETH-USDT,1546290000,1630270800,300.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,900.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,1800.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,3600.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,14400.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,21600.0.csv in backtest.
Including: ETH-USDT,1546290000,1630270800,86400.0.csv in backtest.
Including: ETH-USDT,1627776000.0,1630108800.0,3600.0.csv in backtest.
Initializing...
1630098000.0
Traceback (most recent call last):
File "C:\Python39\lib\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade_interface.py", line 296, in get_account
return trade_local.get_account(symbol)
File "C:\Python39\lib\site-packages\blankly\exchanges\interfaces\paper_trade\local_account\trade_local.py", line 125, in get_account
return copy.deepcopy(utils.AttributeDict(local_account.account[asset_id]))
KeyError: 'USD'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Blankly\RSI-strategy.py", line 30, in <module>
binance_strategy.backtest(start_date = "2021-08-01", end_date = "2021-08-28",
File "C:\Python39\lib\site-packages\blankly\strategy\strategy_base.py", line 473, in backtest
results = self.backtesting_controller.run()
File "C:\Python39\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 397, in run
available_dict, no_trade_dict = self.format_account_data(self.initial_time)
File "C:\Python39\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 221, in format_account_data
true_account[i] = self.interface.get_account(i)
File "C:\Python39\lib\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade_interface.py", line 298, in get_account
raise KeyError("Symbol not found.")
KeyError: 'Symbol not found.'I am trying to run sample code from docs using Alpaca paper trading account:
from blankly import Strategy, StrategyState, Interface
from blankly import Alpaca
from blankly.indicators import rsi
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')['close']
def price_event(price, symbol, state: StrategyState):
# we'll come back to this soon
print("New price event: " + str(price) + ".")
pass
alpaca = Alpaca()
s = Strategy(alpaca)
s.add_price_event(price_event, 'MSFT', resolution='1m', init=init)
s.start()
but I a getting an error below.
{
"settings": {
"account_update_time": 5000,
"use_sandbox": false,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "us"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD"
}
}
}INFO: No portfolio name to load specified, defaulting to the first in the file: (another cool portfolio). This is fine if there is only one portfolio in use.
Traceback (most recent call last):
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\alpaca_trade_api\rest.py", line 208, in _one_request
resp.raise_for_status()
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\requests\models.py", line 953, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 401 Client Error: Unauthorized for url: https://api.alpaca.markets/v2/account
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\blankly\exchanges\interfaces\alpaca\alpaca_interface.py", line 48, in init_exchange
account_info = self.calls.get_account()
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\alpaca_trade_api\rest.py", line 246, in get_account
resp = self.get('/account')
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\alpaca_trade_api\rest.py", line 224, in get
return self._request('GET', path, data)
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\alpaca_trade_api\rest.py", line 187, in _request
return self._one_request(method, url, opts, retry)
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\alpaca_trade_api\rest.py", line 216, in _one_request
raise APIError(error, http_error)
alpaca_trade_api.rest.APIError: request is not authorized
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\Mislav\Documents\blankly_projects\intro.py", line 16, in <module>
alpaca = Alpaca()
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\blankly\exchanges\interfaces\alpaca\alpaca.py", line 26, in __init__
Exchange.__init__(self, 'alpaca', portfolio_name, keys_path, settings_path)
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\blankly\exchanges\exchange.py", line 41, in __init__
self.calls, self.interface = self.__direct_calls_factory.create(self.__type, self.__auth, preferences_path)
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\blankly\exchanges\interfaces\direct_calls_factory.py", line 57, in create
return calls, AlpacaInterface(calls, preferences_path)
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\blankly\exchanges\interfaces\alpaca\alpaca_interface.py", line 43, in __init__
super().__init__('alpaca', authenticated_API, preferences_path, valid_resolutions=[60, 60*5, 60*15, 60*60*24])
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\blankly\exchanges\interfaces\exchange_interface.py", line 49, in __init__
self.init_exchange()
File "C:\ProgramData\Anaconda3\envs\blankly\lib\site-packages\blankly\exchanges\interfaces\alpaca\alpaca_interface.py", line 50, in init_exchange
raise APIException(e.__str__() + ". Are you trying to use your normal exchange keys "
blankly.utils.exceptions.APIException: request is not authorized. Are you trying to use your normal exchange keys while in sandbox mode?
Try toggling the 'use_sandbox' setting in your settings.json or check if the keys were input correctly into your keys.json.I'm trying to build de package from source using python3 setup.py install but I'm getting some problems....
First it did not find Numpy on my virtual environment, so I installed it. Then it could not find Cython. Installed it again.
Now it gives me an error message when running the setup.
Traceback (most recent call last):
File "/Users/vitoreller/Desktop/Projects/open-repos/Blankly/venv/lib/python3.9/site-packages/setuptools/sandbox.py", line 152, in save_modules
yield saved
File "/Users/vitoreller/Desktop/Projects/open-repos/Blankly/venv/lib/python3.9/site-packages/setuptools/sandbox.py", line 193, in setup_context
yield
File "/Users/vitoreller/Desktop/Projects/open-repos/Blankly/venv/lib/python3.9/site-packages/setuptools/sandbox.py", line 254, in run_setup
_execfile(setup_script, ns)
File "/Users/vitoreller/Desktop/Projects/open-repos/Blankly/venv/lib/python3.9/site-packages/setuptools/sandbox.py", line 43, in _execfile
exec(code, globals, locals)
File "/var/folders/q8/6drbgp5d02zg2z91trgq193c0000gn/T/easy_install-vjxyib74/pandas-1.4.0/setup.py", line 651, in <module>
File "/var/folders/q8/6drbgp5d02zg2z91trgq193c0000gn/T/easy_install-vjxyib74/pandas-1.4.0/setup.py", line 424, in maybe_cythonize
File "/Users/vitoreller/Desktop/Projects/open-repos/Blankly/venv/lib/python3.9/site-packages/Cython/Build/Dependencies.py", line 1079, in cythonize
pool = multiprocessing.Pool(
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/context.py", line 119, in Pool
return Pool(processes, initializer, initargs, maxtasksperchild,
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py", line 212, in __init__
self._repopulate_pool()
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py", line 303, in _repopulate_pool
return self._repopulate_pool_static(self._ctx, self.Process,
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/pool.py", line 326, in _repopulate_pool_static
w.start()
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/process.py", line 121, in start
self._popen = self._Popen(self)
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/context.py", line 284, in _Popen
return Popen(process_obj)
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/popen_spawn_posix.py", line 32, in __init__
super().__init__(process_obj)
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/popen_fork.py", line 19, in __init__
self._launch(process_obj)
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/multiprocessing/popen_spawn_posix.py", line 61, in _launch
with open(parent_w, 'wb', closefd=False) as f:
File "/Users/vitoreller/Desktop/Projects/open-repos/Blankly/venv/lib/python3.9/site-packages/setuptools/sandbox.py", line 421, in _open
if mode not in ('r', 'rt', 'rb', 'rU', 'U') and not self._ok(path):
File "/Users/vitoreller/Desktop/Projects/open-repos/Blankly/venv/lib/python3.9/site-packages/setuptools/sandbox.py", line 432, in _ok
realpath = os.path.normcase(os.path.realpath(path))
File "/usr/local/Cellar/[email protected]/3.9.7_1/Frameworks/Python.framework/Versions/3.9/lib/python3.9/posixpath.py", line 391, in realpath
filename = os.fspath(filename)
TypeError: expected str, bytes or os.PathLike object, not intAdditional context
From my experiences on other open-source repositories, I would say that you need a requirements.txt file on root, so that users can install it in an easier way when trying to build from source.
Btw, I want to build from source so I can see if I can contribute to your repository! Really loved it!
When I'm running a Signal similar to the example RSI Screener, it requires me to have a notify.json even if I don't actually want to send an email with a local SMTP server. Is there a way to not require this and simply output the formatted results to the terminal?
{
"settings": {
"account_update_time": 5000,
"use_sandbox": true,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "us"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD",
"enable_shorting": true,
"use_yfinance": true
},
"oanda": {
"cash": "USD"
}
}
}Traceback (most recent call last):
File "/opt/anaconda3/envs/blankly/lib/python3.9/site-packages/blankly/utils/utils.py", line 153, in load
preferences = load_json_file(self.__default_path)
File "/opt/anaconda3/envs/blankly/lib/python3.9/site-packages/blankly/utils/utils.py", line 100, in load_json_file
f = open(override_path, )
FileNotFoundError: [Errno 2] No such file or directory: './notify.json'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/weigfan/code/blankly/blankly-package/examples/rsi_screener.py", line 25, in <module>
signal.notify()
File "/opt/anaconda3/envs/blankly/lib/python3.9/site-packages/blankly/frameworks/signal/signal.py", line 148, in notify
blankly.reporter.email(use_str)
File "/opt/anaconda3/envs/blankly/lib/python3.9/site-packages/blankly/deployment/reporter_headers.py", line 172, in email
self.__send_email(email)
File "/opt/anaconda3/envs/blankly/lib/python3.9/site-packages/blankly/deployment/reporter_headers.py", line 148, in __send_email
notify_preferences = load_notify_preferences()
File "/opt/anaconda3/envs/blankly/lib/python3.9/site-packages/blankly/utils/utils.py", line 200, in load_notify_preferences
return notify_settings.load(override_path)
File "/opt/anaconda3/envs/blankly/lib/python3.9/site-packages/blankly/utils/utils.py", line 155, in load
raise FileNotFoundError(self.__not_found_err)
FileNotFoundError: To send emails locally, make sure a notify.json file is placed in the same folder as the project working directory. This is not necessary when deployed live on blankly cloud.
The code throws an exception - KeyError: 'maxNumOrders' when running backtests on Binance.
I think I have found out the root cause of the issue - Binance might have changed their response file. The code worked after I modified as below. There are other places in the file where filter is fetched in the code using indexes; I feel they need to be modified to fetch data based on the filterType.
# max_orders = int(filters[6]["maxNumOrders"])
max_orders = int(next(filter for filter in filters if filter["filterType"] == "MAX_NUM_ORDERS")["maxNumOrders"])[{'filterType': 'PRICE_FILTER', 'minPrice': '0.01000000', 'maxPrice': '1000000.00000000', 'tickSize': '0.01000000'},
{'filterType': 'PERCENT_PRICE', 'multiplierUp': '5', 'multiplierDown': '0.2', 'avgPriceMins': 5},
{'filterType': 'LOT_SIZE', 'minQty': '0.00001000', 'maxQty': '9000.00000000', 'stepSize': '0.00001000'},
{'filterType': 'MIN_NOTIONAL', 'minNotional': '10.00000000', 'applyToMarket': True, 'avgPriceMins': 5},
{'filterType': 'ICEBERG_PARTS', 'limit': 10},
{'filterType': 'MARKET_LOT_SIZE', 'minQty': '0.00000000', 'maxQty': '148.34869255', 'stepSize': '0.00000000'},
{'filterType': 'TRAILING_DELTA', 'minTrailingAboveDelta': 10, 'maxTrailingAboveDelta': 2000, 'minTrailingBelowDelta': 10, 'maxTrailingBelowDelta': 2000},
{'filterType': 'MAX_NUM_ORDERS', 'maxNumOrders': 200},
{'filterType': 'MAX_NUM_ALGO_ORDERS', 'maxNumAlgoOrders': 5}]
Traceback (most recent call last):
File "/Users/rohitsathyanathan/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 771, in run
self.price_events[0]['function'](self.interface.get_price(self.price_events[0]['asset_id']),
File "/Users/rohitsathyanathan/Desktop/ML/GitHub/blankly/examples/golden_cross.py", line 36, in price_event
interface.market_order(symbol, 'buy', int(interface.cash/price))
File "/Users/rohitsathyanathan/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/paper_trade_interface.py", line 359, in market_order
market_limits = self.get_order_filter(symbol)
File "/Users/rohitsathyanathan/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/paper_trade_interface.py", line 640, in get_order_filter
self.get_order_filter_cache[symbol] = self.calls.get_order_filter(symbol)
File "/Users/rohitsathyanathan/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/binance/binance_interface.py", line 776, in get_order_filter
max_orders = int(filters[6]["maxNumOrders"])
KeyError: 'maxNumOrders'
When using Binance interface in backtesting, calling cancel_order on a sell limit order does not move the value of the asset from hold to available.
settings.json herebacktest.json hereError here
Additional context
Add any other context about the problem here.
I want to implement OCO orders for Binance but it's not found in the document. Should I implement it manually?
To build it manually, I plan to:
Is there a better way to do this?
Currently, the cached data needs to be networked. Can we configure to turn off networking and use local default data. Because of the country firewall limit. Don't want to keep VPN on
Oh, sorry, maybe networking is to get trade fees? I don't know much about the code here.
When i try my test binance api it is work correctly but my real binance account doesnt work! I use my api in wunderbit and other services.
Python 3.9.6 (tags/v3.9.6:db3ff76, Jun 28 2021, 15:26:21) on Windows (64 bits).
GetInfo.py
import blankly
exchange = blankly.Binance(portfolio_name="Blankly Binance")
interface = exchange.get_interface() # Use the getter
print(interface.get_account())keys.json
{
"binance": {
"Blankly Binance": {
"API_KEY": "y*********************************************************************",
"API_SECRET": "yx*********************************************************************"
},
"ATD Test": {
"API_KEY": "x*********************************************************************",
"API_SECRET": "xx*********************************************************************"
}
}
}settings.json
{
"settings": {
"account_update_time": 5000,
"use_sandbox": true,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "com"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD"
}
}
}
Error
>>> (executing file "GetInfo.py")
Traceback (most recent call last):
File "C:\Blankly\GetInfo.py", line 2, in <module>
exchange = blankly.Binance(portfolio_name="Blankly Binance")
File "c:\python39\lib\site-packages\blankly\exchanges\interfaces\binance\binance.py", line 27, in __init__
Exchange.__init__(self, "binance", portfolio_name, keys_path, settings_path)
File "c:\python39\lib\site-packages\blankly\exchanges\exchange.py", line 41, in __init__
self.calls, self.interface = self.__direct_calls_factory.create(self.__type, self.__auth, preferences_path)
File "c:\python39\lib\site-packages\blankly\exchanges\interfaces\direct_calls_factory.py", line 51, in create
return calls, BinanceInterface(exchange_name, calls)
File "c:\python39\lib\site-packages\blankly\exchanges\interfaces\binance\binance_interface.py", line 34, in __init__
super().__init__(exchange_name, authenticated_API)
File "c:\python39\lib\site-packages\blankly\exchanges\interfaces\exchange_interface.py", line 43, in __init__
self.init_exchange()
File "c:\python39\lib\site-packages\blankly\exchanges\interfaces\binance\binance_interface.py", line 40, in init_exchange
raise exceptions.APIException("Invalid API Key, IP, or permissions for action - are you trying "
blankly.utils.exceptions.APIException: Invalid API Key, IP, or permissions for action - are you trying to use your normal exchange keys while in sandbox mode?Not a bug, not a feature request - just a quick note saying that I can't wait for Blankly Platform early access and wanted to applaud the entire team for their outstanding work! Keep it up!
It has nothing to do with the number of indicators, mainly to discuss data related issues.
Blankly Metrics:
cagr: 0.05496190946315571
cum_returns: 0.10125999999999999
sortino: 0.015965089446707815
sharpe: 0.041373845807941685
calmar: 5.896585739465047e-50
volatility: 0.6150518619211591
variance: 0.37828879285268463
var: 0.06339999993087986
cvar: 41.08448129311799
max_drawdown: -4.315592692015137e+47
There are two problems at present.
cagr: 5.496% (using a full name may be better. Compound Annual Growth Rate)
cum_returns: 10.126%
the jeese report as a reference
Total Closed Trades | 221
Total Net Profit | 1,699,245.56 (1699.25%)
Starting => Finishing Balance | 100,000 => 1,799,245.56
Total Open Trades | 0
Open PL | 0
Total Paid Fees | 331,480.93
Max Drawdown | -22.42%
Annual Return | 80.09%
Expectancy | 7,688.89 (7.69%)
Avg Win | Avg Loss | 31,021.9 | 8,951.7
Ratio Avg Win / Avg Loss | 3.47
Percent Profitable | 42%
Longs | Shorts | 60% | 40%
Avg Holding Time | 3.0 days, 22.0 hours, 50.0 minutes
Winning Trades Avg Holding Time | 6.0 days, 14.0 hours, 9.0 minutes
Losing Trades Avg Holding Time | 2.0 days, 1.0 hour, 41.0 minutes
Sharpe Ratio | 1.88
Calmar Ratio | 3.57
Sortino Ratio | 3.51
Omega Ratio | 1.49
Winning Streak | 5
Losing Streak | 10
Largest Winning Trade | 205,575.89
Largest Losing Trade | -50,827.92
Total Winning Trades | 92
Total Losing Trades | 129
max_drawdown: -4.315592692015137e+47
Hello,
The following error pops up when I try to test one of the examples with the Binance interface:
INFO: No portfolio name to load specified, defaulting to the first in the file: (Pompom). This is fine if there is only one portfolio in use. Invalid API Key, IP, or permissions for action - are you trying to use your normal exchange keys while in sandbox mode? Try toggling the 'use_sandbox' setting in your settings.json or check if the keys were input correctly into your keys.json.
Any idea what it could be?
My api keys appear to be correct, because I get my account information using the following code (python-binance package):
from binance.client import Client
client = Client(keys['binance']["project"]["API_KEY"],
keys['binance']["project"]["API_SECRET"],
)
print(client.get_account())
If I look at the trace, it is on the self.calls.get_account() call, where the code breaks.
My settings file is as follows:
"settings": {
"account_update_time": 5000,
"use_sandbox": true, (I also tried it with this as false, but then it suggests to put it to true)
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "us"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD",
"enable_shorting": true
},
"oanda": {
"cash": "USD"
}
}
}
Thanks in advance!
I'm trying to work with google colab, but I get the error "ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject".
!pip install --upgrade numpy==1.19.2
I tried the numpy version with the above, still didn't work.
But it's very interesting, I got it working yesterday after repeating it a few times.
Additional context
I'll open a separate thread for windows :(
blankly.utils.exceptions.APIException: Invalid API Key, IP, or permissions for action - are you trying to use your normal exchange keys while in sandbox mode?
Support third party signal. Currently everything is soley based on market data
Adds more variety of trading strategies like integrating with newsfeed, sentiment scores, etc.
example:
add_price_event(data_handler, symbol, ...)
Give us some of your initial thoughts for implementing this.
Additional Information
Add any other context about the feature request here including what other packages have done, linked issues, and more.
My Code:
coinbase = CoinbasePro()
s = Strategy(coinbase)
s.add_price_event(price_event, 'BTC-USD', resolution='30m', init=init)
result = s.backtest(initial_values={'USD': 10000}, to='2y')
"settings": {
"account_update_time": 5000,
"use_sandbox": false,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "us"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD"
},
"oanda": {
"cash": "USD"
}
}
}
backtest.json hereTraceback (most recent call last):
File "H:\ProgramData\Anaconda3\lib\runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "H:\ProgramData\Anaconda3\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "c:\Users\xxxxxxxxxx\.vscode\extensions\ms-python.python-2021.12.1559732655\pythonFiles\lib\python\debugpy\__main__.py", line 45, in <module>
cli.main()
File "c:\Users\xxxxxxxxxx\.vscode\extensions\ms-python.python-2021.12.1559732655\pythonFiles\lib\python\debugpy/..\debugpy\server\cli.py", line 444, in main
run()
File "c:\Users\xxxxxxxxxx\.vscode\extensions\ms-python.python-2021.12.1559732655\pythonFiles\lib\python\debugpy/..\debugpy\server\cli.py", line 285, in run_file
runpy.run_path(target_as_str, run_name=compat.force_str("__main__"))
File "H:\ProgramData\Anaconda3\lib\runpy.py", line 265, in run_path
return _run_module_code(code, init_globals, run_name,
File "H:\ProgramData\Anaconda3\lib\runpy.py", line 97, in _run_module_code
_run_code(code, mod_globals, init_globals,
File "H:\ProgramData\Anaconda3\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "c:\git\crypto-test\src\macd\macd.py", line 57, in <module>
s = Strategy(coinbase)
File "C:\Users\xxxxxxxxxx\AppData\Roaming\Python\Python38\site-packages\blankly\frameworks\strategy\strategy_base.py", line 64, in __init__
self.__paper_trade_exchange = blankly.PaperTrade(self.__exchange)
File "C:\Users\xxxxxxxxxx\AppData\Roaming\Python\Python38\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade.py", line 28, in __init__
self.interface = PaperTradeInterface(authenticated_exchange.get_interface(),
File "C:\Users\xxxxxxxxxx\AppData\Roaming\Python\Python38\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade_interface.py", line 56, in __init__
ExchangeInterface.__init__(self, derived_interface.get_exchange_type(), derived_interface)
File "C:\Users\xxxxxxxxxx\AppData\Roaming\Python\Python38\site-packages\blankly\exchanges\interfaces\exchange_interface.py", line 135, in __init__
self.init_exchange()
File "C:\Users\xxxxxxxxxx\AppData\Roaming\Python\Python38\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade_interface.py", line 131, in init_exchange
"maker_fee_rate": fees['maker_fee_rate'],
KeyError: 'maker_fee_rate'
Additional context
Add any other context about the problem here.
state.interface.history should return history at state time during backtest.
At the moment, when called in an init function at the beginning of the backtest, it retrieves history relative to wall time.
Example:
The backtest goes from 2020-01-01 to 2020-12-31. When retrieving 5 days of history I'd expect it to get 2019-12-26 to 2019-12-31.
Instead it gets the last 5 days relative to the day when it is run, e.g., 2021-10-24 - 2021-10-29.
As a workaround I'm using something like this now:
def get_historic_candles_at_state_time(state, symbol, ncandles, resolution):
current_time = state.time
start = current_time - ncandles * time_interval_to_seconds(resolution)
end = current_time
history = state.interface.history(
symbol, start_date=start, end_date=end, resolution=resolution
)
return history{
"settings": {
"account_update_time": 5000,
"use_sandbox": false,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "EUR",
"binance_tld": "com"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD"
}
}
}{
"price_data": {
"assets": []
},
"settings": {
"use_price": "close",
"smooth_prices": false,
"GUI_output": false,
"show_tickers_with_zero_delta": false,
"save_initial_account_value": true,
"show_progress_during_backtest": true,
"cache_location": "./data/price_caches",
"continuous_caching": true,
"resample_account_value_for_metrics": "1d",
"quote_account_value_in": "USDT",
"ignore_user_exceptions": false
}As in the title. Provided examples throw errors during execution
Tested files: bot.py (generated by 'blankly init' command), examples/rsi.py, examples/mlp_model.py
{
"settings": {
"account_update_time": 5000,
"use_sandbox": true,
"use_sandbox_websockets": true,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "us"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD"
}
}
}{
"price_data": {
"assets": []
},
"settings": {
"use_price": "close",
"smooth_prices": false,
"GUI_output": true,
"show_tickers_with_zero_delta": false,
"save_initial_account_value": true,
"show_progress_during_backtest": true,
"cache_location": "./price_caches",
"continuous_caching": true,
"resample_account_value_for_metrics": "1d",
"quote_account_value_in": "USDT",
"ignore_user_exceptions": false,
"risk_free_return_rate": 0.0
}
}rsi.py
Traceback (most recent call last):
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 692, in run
raise e
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 685, in run
self.price_events[0]['function'](self.interface.get_price(self.price_events[0]['asset_id']),
File "/home/jakub/PycharmProjects/bot/blankly/rsi.py", line 7, in price_event
rsi = blankly.indicators.rsi(state.variables['history'])
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/blankly/indicators/oscillators.py", line 33, in rsi
rsi_values = ti.rsi(data, period)
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/tulipy/__init__.py", line 1003, in rsi
return lib.rsi([real], [period])
File "tulipy/lib/__init__.pyx", line 105, in tulipy.lib._Indicator.__call__
tulipy.lib.InvalidOptionErrormlp_model.py
Traceback (most recent call last):
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 692, in run
raise e
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 685, in run
self.price_events[0]['function'](self.interface.get_price(self.price_events[0]['asset_id']),
File "/home/jakub/PycharmProjects/bot/blankly/mlp_model.py", line 38, in price_event
rsi_values = rsi(variables['history'], period=14).reshape(-1, 1)
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/blankly/indicators/oscillators.py", line 33, in rsi
rsi_values = ti.rsi(data, period)
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/tulipy/__init__.py", line 1003, in rsi
return lib.rsi([real], [period])
File "tulipy/lib/__init__.pyx", line 105, in tulipy.lib._Indicator.__call__
tulipy.lib.InvalidOptionErrorbot.py
Traceback (most recent call last):
File "/home/jakub/PycharmProjects/bot/blankly2/bot.py", line 39, in <module>
results = strategy.backtest(to='1y', initial_values={'USDT': 10000})
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/blankly/frameworks/strategy/strategy_base.py", line 495, in backtest
results = self.backtesting_controller.run()
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 543, in run
self.interface.receive_price(k, v[use_price].iloc[0])
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/pandas/core/indexing.py", line 879, in __getitem__
return self._getitem_axis(maybe_callable, axis=axis)
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/pandas/core/indexing.py", line 1496, in _getitem_axis
self._validate_integer(key, axis)
File "/home/jakub/anaconda3/envs/cbot/lib/python3.9/site-packages/pandas/core/indexing.py", line 1437, in _validate_integer
raise IndexError("single positional indexer is out-of-bounds")
IndexError: single positional indexer is out-of-boundsAdditional context
Library installed as proposed in https://github.com/Blankly-Finance/Blankly#quickstart
All example scripts and json files were modified to use sandbox account and API for Binance, also USD was changed to USDT in symbols and portfolio.
A clear and concise description of what the bug is.
TypeError: cannot concatenate object of type '<class 'numpy.float64'>'; only Series and DataFrame objs are valid
My first time looking into Blankly.
My process is basically:
$ python3 -m venv .venv
$ source ./.venv/bin/activate
$ python3 -m pip install --upgrade blankly
$ blankly init
$ python3 example.pywhere example.py is the C&Pd code from https://docs.blankly.finance/examples/golden-cross/:
from blankly import Alpaca, Interface, Strategy, StrategyState
from blankly.indicators import sma
def init(symbol, state: StrategyState):
interface: Interface = state.interface
resolution: float = state.resolution
variables = state.variables
# initialize the historical data
variables["history"] = interface.history(symbol, 800, resolution)["close"]
variables["has_bought"] = False
def price_event(price, symbol, state: StrategyState):
interface: Interface = state.interface
# allow the resolution to be any resolution: 15m, 30m, 1d, etc.
resolution: float = state.resolution
variables = state.variables
variables["history"].append(price)
sma50 = sma(variables["history"], period=50)
sma200 = sma(variables["history"], period=200)
diff = sma200 - sma50
slope_sma50 = (
sma50[-1] - sma50[-5]
) / 5 # get the slope of the last 5 SMA50 Data Points
prev_diff = diff[-2]
curr_diff = diff[-1]
is_cross_up = slope_sma50 > 0 and curr_diff >= 0 and prev_diff < 0
is_cross_down = slope_sma50 < 0 and curr_diff <= 0 and prev_diff > 0
# comparing prev diff with current diff will show a cross
if is_cross_up and not variables["has_bought"]:
interface.market_order("buy", symbol, int(interface.cash / price))
variables["has_bought"] = True
elif is_cross_down and variables["has_bought"]:
interface.market_order(
"sell", symbol, int(interface.account[symbol].available)
)
variables["has_bought"] = False
alpaca = Alpaca()
s = Strategy(alpaca)
s.add_price_event(price_event, "MSFT", resolution="1d", init=init)
s.backtest(initial_values={"USD": 10000}, to="2y")In response, I get numerous rows of the error:
TypeError: cannot concatenate object of type '<class 'numpy.float64'>'; only Series and DataFrame objs are valid
The plot then opens in my browser and is flat -- looks like no data.
My only change to settings.json is setting use_sandbox to true for alpaca paper trading.
{
"settings": {
"account_update_time": 5000,
"use_sandbox": true,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "us"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD"
},
"oanda": {
"cash": "USD"
}
}
}Backtest.json is unchanged from default:
{
"price_data": {
"assets": []
},
"settings": {
"use_price": "close",
"smooth_prices": false,
"GUI_output": true,
"show_tickers_with_zero_delta": false,
"save_initial_account_value": true,
"show_progress_during_backtest": true,
"cache_location": "./price_caches",
"continuous_caching": true,
"resample_account_value_for_metrics": "1d",
"quote_account_value_in": "USD",
"ignore_user_exceptions": true,
"risk_free_return_rate": 0.0
}
}TypeError: cannot concatenate object of type '<class 'numpy.float64'>'; only Series and DataFrame objs are valid
Hi!
Around 50% of the time when starting a bot it will freeze up when using the broker interface and wait for thread lock. When killing the script i get
Traceback (most recent call last):
File "/usr/lib/python3.7/threading.py", line 1281, in _shutdown
t.join()
File "/usr/lib/python3.7/threading.py", line 1032, in join
self._wait_for_tstate_lock()
File "/usr/lib/python3.7/threading.py", line 1048, in _wait_for_tstate_lock
elif lock.acquire(block, timeout):
KeyboardInterrupt
restarting the script often solves the problem.
https://docs.blankly.finance/core/strategy
Because of this API interface.market_order change.
There are several areas that need to be changed, and the following is one of them.
from blankly import Strategy, StrategyState, Alpaca
import blankly
def init(symbol: str, state: StrategyState):
variables = state.variables # grab the variables dictionary
# initialize any variables here
variables['has_bought'] = True
# get 50 data points at specific resolution of event
variables['history'] = state.interface.history(symbol, 50, state.resolution)['close'].to_list()
def price_event(price, symbol, state: StrategyState):
""" This buys and sells whenever the boolean is true or false """
interface: blankly.Interface = state.interface
state.variables['history'].append(price) # add new price to history
# buy the symbol using available cash
if not state.variables['has_bought']:
interface.market_order(symbol, 'buy', blankly.trunc(interface.cash, 2))
state.variables['has_bought'] = True
else:
interface.market_order(symbol, 'sell', blankly.trunc(interface.account[state.base_asset]['available'], 2))
state.variables['has_bought'] = False
a = Alpaca()
s = Strategy(a)
s.add_price_event(price_event, 'MSFT', resolution='15m', init=init)
s.start()
interface.market_order(symbol, 'buy', blankly.trunc(interface.cash, 2)) --> interface.market_order(symbol, 'buy', blankly.trunc(interface.cash / price, 2))
One of the main use cases of trading models is for arbitrage events that rely on the simultaneous reading of two data streams. Say for example that you want to trade Coke (NYSE:KO) and Pepsi (NYSE:PEP), we want to be able to read from both and generate a synthetic price from each.
I would think that within a Strategy we could add an add_arbitrage_event(event_handler, <ticker_1>, <ticker_2>, resolution) that uses the same interface to get the price data simultaneously.
from blankly import Alpaca, Strategy
def mean_reversion(price_symbol_1, price_symbol_2, state):
ratio = price_symbol_2 / price_symbol_1
if ratio > 1:
# do something
else:
# do something else
a = Alpaca()
s = Strategy(a)
s.add_arbitrage_event(mean_reversion, 'MSFT', 'AAPL', '15m')
s.backtest(to='2y')Great job. Keep getting errors while using example rsi files.
from blankly import Oanda, Strategy, StrategyState
#from blankly.utils import trunc
from blankly.indicators import rsi
def init(symbol, state: StrategyState):
state.variables['history'] = state.interface.history(symbol, 150, resolution=state.resolution, return_as='deque')['close']
state.variables['own_position'] = False
def price_event(price, symbol, state: StrategyState):
state.variables['history'].append(price)
rsi_output = rsi(state.variables['history'])
print(rsi_output)
if rsi_output[-1] < 30 and not state.variables['own_position']:
qty = int(state.interface.cash / price)
state.interface.market_order(symbol, side='buy', size=qty)
state.variables['own_position'] = True
elif rsi_output[-1] > 70 and state.variables['own_position']:
qty = int(state.interface.account[symbol].available)
state.interface.market_order(symbol, side='sell', size=qty)
state.variables['own_position'] = False
exchange = Oanda()
s = Strategy(exchange)
s.add_price_event(price_event, symbol='EUR-USD', resolution='15m', init=init)
results = s.backtest(to='1M')
print(results)
{
"settings": {
"account_update_time": 5000,
"use_sandbox": true,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "us"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD",
"enable_shorting": true
},
"oanda": {
"cash": "USD"
}
}
}{
"price_data": {
"assets": []
},
"settings": {
"use_price": "close",
"smooth_prices": false,
"GUI_output": true,
"show_tickers_with_zero_delta": false,
"save_initial_account_value": true,
"show_progress_during_backtest": true,
"cache_location": "./price_caches",
"continuous_caching": true,
"resample_account_value_for_metrics": "1d",
"quote_account_value_in": "USD",
"ignore_user_exceptions": true,
"risk_free_return_rate": 0.0
}
}#Error with int
Traceback (most recent call last):
File "C:\..\blankly\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 769, in run
'state_object'])
File "C:/../blankly/rsi_bot_old.py", line 20, in price_event
qty = int(state.interface.account[symbol].available)
KeyError: 'EUR-USD'
#Error with trunc with 2 decimals
Traceback (most recent call last):
File "C:\..\blankly\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 769, in run
'state_object'])
File "C:/../blankly/rsi_bot_old.py", line 17, in price_event
state.interface.market_order(symbol, side='buy', size=qty)
File "C:\..\blankly\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade_interface.py", line 378, in market_order
". Try using blankly.trunc(size, decimal_number) to match the exchange resolution.")
blankly.utils.exceptions.InvalidOrder: Size resolution is too high, the highest resolution allowed for this symbol is: 1. You specified 88357.95. Try using blankly.trunc(size, decimal_number) to match the exchange resolution.
Traceback (most recent call last):
File "C:\..\blankly\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 769, in run
'state_object'])
File "C:/../blankly/rsi_bot_old.py", line 17, in price_event
state.interface.market_order(symbol, side='buy', size=qty)
File "C:\..\blankly\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade_interface.py", line 378, in market_order
". Try using blankly.trunc(size, decimal_number) to match the exchange resolution.")
blankly.utils.exceptions.InvalidOrder: Size resolution is too high, the highest resolution allowed for this symbol is: 1. You specified 88361.07. Try using blankly.trunc(size, decimal_number) to match the exchange resolution.
Traceback (most recent call last):
File "C:\..\blankly\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 769, in run
'state_object'])
File "C:/../blankly/rsi_bot_old.py", line 17, in price_event
state.interface.market_order(symbol, side='buy', size=qty)
File "C:\..\blankly\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade_interface.py", line 378, in market_order
". Try using blankly.trunc(size, decimal_number) to match the exchange resolution.")
blankly.utils.exceptions.InvalidOrder: Size resolution is too high, the highest resolution allowed for this symbol is: 1. You specified 88390.75. Try using blankly.trunc(size, decimal_number) to match the exchange resolution.
Traceback (most recent call last):
File "C:\..\blankly\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 769, in run
'state_object'])
File "C:/../blankly/rsi_bot_old.py", line 17, in price_event
state.interface.market_order(symbol, side='buy', size=qty)
File "C:\..\blankly\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\paper_trade_interface.py", line 378, in market_order
". Try using blankly.trunc(size, decimal_number) to match the exchange resolution.")
blankly.utils.exceptions.InvalidOrder: Size resolution is too high, the highest resolution allowed for this symbol is: 1. You specified 88397.79. Try using blankly.trunc(size, decimal_number) to match the exchange resolution.
...
C:\..\blankly\venv\lib\site-packages\blankly\metrics\portfolio.py:55: RuntimeWarning: invalid value encountered in double_scalars
return mean / std
C:\..\blankly\venv\lib\site-packages\blankly\metrics\portfolio.py:60: RuntimeWarning: invalid value encountered in double_scalars
return return_series.mean() * n / abs(max_drawdown(return_series))
Additional context
I see it's not currently supported, this would be a big boost. Very cumbersome to implement manually.
Love the project!
I was backtesting my custom logic (exchange=Binance) but I keep getting the below error frequently. I have seen this error in the example code also. It works fine for some of resolution/duration. It seems to be a floating point/rounding/truncate issue.
Could you please take a look?
Traceback (most recent call last):
File "/Users/rs/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 771, in run
self.price_events[0]['function'](self.interface.get_price(self.price_events[0]['asset_id']),
File "/Users/rs/Desktop/ML/GitHub/blankly/examples/rolling_window_breakout.py", line 84, in price_event
interface.market_order(symbol, 'sell', state.interface.account[state.base_asset].available)
File "/Users/rs/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/paper_trade_interface.py", line 391, in market_order
self.local_account.test_trade(symbol, side, qty, price, market_limits['market_order']["quote_increment"],
File "/Users/rs/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/local_account/trade_local.py", line 192, in test_trade
raise InvalidOrder("Not enough base currency. Available: " +
blankly.utils.exceptions.InvalidOrder: Not enough base currency. Available: 0.02037. hold: 0. requested: 0.02038.
import blankly
from blankly import Strategy, StrategyState, Interface
from blankly import Binance
from blankly.indicators import sma
#import math
my_stop_loss = 0
my_target = 0
my_winning_trades =0
my_losing_trades = 0
my_stop_loss_percent = 1
my_target_percent = 1.5
def init(symbol, state: StrategyState):
interface: Interface = state.interface
resolution = state.resolution
variables = state.variables
# initialize the historical data
variables['history'] = interface.history(symbol, 25, resolution, end_date=state.time, return_as='deque')['close']
variables['owns_position'] = False
def price_event(price, symbol, state: StrategyState):
interface: Interface = state.interface
variables = state.variables
window_max_price = max(variables['history'])
window_min_price = min(variables['history'])
action = 'Hold'
global my_stop_loss
global my_target
global my_winning_trades
global my_losing_trades
if window_max_price > price > window_min_price:
action = 'Hold'
elif price > window_max_price:
action = 'Buy'
elif price < window_min_price:
action = 'Sell'
# trailing stoploss and target
if my_stop_loss < price*(100-my_stop_loss_percent)/100:
my_stop_loss = price*(100-my_stop_loss_percent)/100
my_target = my_target+ 0.5 * price*(my_target_percent) / 100
#print(f'{action} --- price:{price}, max:{window_max_price}, min:{window_min_price}')
variables['history'].append(price)
# comparing prev diff with current diff will show a cross
if action == 'Buy' and not variables['owns_position']:
interface.market_order(symbol, 'buy', blankly.trunc(interface.cash / price, 5))
variables['owns_position'] = True
my_stop_loss = price * (100-my_stop_loss_percent)/100
my_target = price * (100+my_target_percent)/100
print(f'My Buy:{price}')
# Stop Loss Handling
# elif price < my_stop_loss and variables['owns_position']:
# interface.market_order(symbol, 'sell', state.interface.account[state.base_asset].available)
# variables['owns_position'] = False
# my_stop_loss = 0
#elif action == 'Sell' and variables['owns_position']:
elif (price > my_target or price < my_stop_loss) and variables['owns_position']:
if(price < my_stop_loss):
print(f'SL Hit:{price} Target{my_target} SL {my_stop_loss}')
my_losing_trades +=1
elif (price > my_target):
my_winning_trades +=1
print(f'Target Hit:{price} Target{my_target} SL {my_stop_loss}')
# use strategy.base_asset if on CoinbasePro or Binance
# interface.market_order(symbol, 'sell', int(interface.account[symbol].available))
interface.market_order(symbol, 'sell', state.interface.account[state.base_asset].available)
variables['owns_position'] = False
my_stop_loss = 0
my_target = 0
# sma200 = sma(variables['history'], period=200)
# # match up dimensions
# sma50 = sma(variables['history'], period=50)[-len(sma200):]
# diff = sma200 - sma50
# slope_sma50 = (sma50[-1] - sma50[-5]) / 5 # get the slope of the last 5 SMA50 Data Points
# prev_diff = diff[-2]
# curr_diff = diff[-1]
# is_cross_up = slope_sma50 > 0 and curr_diff >= 0 and prev_diff < 0
# is_cross_down = slope_sma50 < 0 and curr_diff <= 0 and prev_diff > 0
#
# # comparing prev diff with current diff will show a cross
# if is_cross_up and not variables['owns_position']:
# interface.market_order(symbol, 'buy', blankly.trunc(interface.cash/price,5))
# variables['owns_position'] = True
# elif is_cross_down and variables['owns_position']:
# # use strategy.base_asset if on CoinbasePro or Binance
# # interface.market_order(symbol, 'sell', int(interface.account[symbol].available))
# interface.market_order(symbol, 'sell', state.interface.account[state.base_asset].available)
# variables['owns_position'] = False
if __name__ == "__main__":
ex = Binance()
s = Strategy(ex)
s.add_price_event(price_event, 'BTC-USDT', resolution='30m', init=init)
# s.add_price_event(price_event, 'GME', resolution='1h', init=init)
results = s.backtest(initial_values={'USDT': 1000}, to='3mo')
print(results)
print(f'Win Count:{my_winning_trades}, Loss Count:{my_losing_trades}')
# Or just run it directly on the exchange
# s.start()
{
"settings": {
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "com"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD",
"enable_shorting": true,
"use_yfinance": false
},
"oanda": {
"cash": "USD"
},
"keyless": {
"cash": "USD"
},
"kucoin": {
"cash": "USDT"
},
"ftx": {
"cash": "USD"
}
}
}{
"price_data": {
"assets": []
},
"settings": {
"use_price": "close",
"smooth_prices": false,
"GUI_output": true,
"show_tickers_with_zero_delta": false,
"save_initial_account_value": true,
"show_progress_during_backtest": true,
"cache_location": "./price_caches",
"continuous_caching": true,
"resample_account_value_for_metrics": "1d",
"quote_account_value_in": "USDT",
"ignore_user_exceptions": true,
"risk_free_return_rate": 0.0,
"benchmark_symbol" : null
}
}Additional context
Add any other context about the problem here.
I've been banging my head on a wall on why does backtesting show an error upon finishing:
/blankly/exchanges/interfaces/paper_trade/backtest_controller.py
AttributeError: 'Figure' object has no attribute 'step'
Upgrading to python 3.10.0 solved the issue, I was using 3.8.11.
Maybe this can be checked during installation for convnivence?
Thank you
Unable to pip3 install blankly on an M1 MacBook Big Sur.
Collecting scikit-learn
Downloading scikit-learn-1.0.1.tar.gz (6.6 MB)
|████████████████████████████████| 6.6 MB 3.8 MB/s
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: /Library/Frameworks/Python.framework/Versions/3.9/bin/python3.9 /private/var/folders/t9/2fb8pd6s41b0d41lk81pk_700000gn/T/pip-standalone-pip-ata6s47j/__env_pip__.zip/pip install --ignore-installed --no-user --prefix /private/var/folders/t9/2fb8pd6s41b0d41lk81pk_700000gn/T/pip-build-env-gp_u1yzv/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- setuptools wheel 'Cython>=0.28.5' 'oldest-supported-numpy; python_version!='"'"'3.7'"'"' or platform_machine=='"'"'aarch64'"'"' or platform_system=='"'"'AIX'"'"' or platform_python_implementation == '"'"'PyPy'"'"'' 'numpy==1.14.6; python_version=='"'"'3.7'"'"' and platform_machine!='"'"'aarch64'"'"' and platform_system!='"'"'AIX'"'"' and platform_python_implementation != '"'"'PyPy'"'"'' 'scipy>=1.1.0'
cwd: None
Complete output (55279 lines):
Ignoring numpy: markers 'python_version == "3.7" and platform_machine != "aarch64" and platform_system != "AIX" and platform_python_implementation != "PyPy"' don't match your environmentalso
clang: error: the clang compiler does not support 'faltivec', please use -maltivec and include altivec.h explicitlyIt would make no sense to keep selling and buying an instrument if price fluctuations are smaller than the trading fees. Do backtests use the functionality built into MarketOrder and LimitOrder? Do we need to explicitly implement fee impact analysis in our price events?
While backtesting golden_cross.py example in BInance with asset = BTC-USTD, the code was able buy but not sell.
The code only worked when I modified the below line (as given in rsi.py).
interface.market_order(symbol, 'sell', int(interface.account[symbol].available))to
interface.market_order(symbol, 'sell', state.interface.account[state.base_asset].available)Could you please check why this is happening?
{
"settings": {
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "com"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD",
"enable_shorting": true,
"use_yfinance": false
},
"oanda": {
"cash": "USD"
},
"keyless": {
"cash": "USD"
},
"kucoin": {
"cash": "USDT"
},
"ftx": {
"cash": "USD"
}
}
}{
"price_data": {
"assets": []
},
"settings": {
"use_price": "close",
"smooth_prices": false,
"GUI_output": true,
"show_tickers_with_zero_delta": false,
"save_initial_account_value": true,
"show_progress_during_backtest": true,
"cache_location": "./price_caches",
"continuous_caching": true,
"resample_account_value_for_metrics": "1d",
"quote_account_value_in": "USDT",
"ignore_user_exceptions": true,
"risk_free_return_rate": 0.0,
"benchmark_symbol" : null
}
}Progress: [#####-----] 47.6% Traceback (most recent call last):
File "/Users/rohitsathyanathan/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 771, in run
self.price_events[0]['function'](self.interface.get_price(self.price_events[0]['asset_id']),
File "/Users/rs/Desktop/ML/GitHub/blankly/examples/golden_cross.py", line 40, in price_event
interface.market_order(symbol, 'sell', int(interface.account[symbol].available))
KeyError: 'BTC-USDT'
Progress: [######----] 55.89% Traceback (most recent call last):
File "/Users/rs/Desktop/ML/GitHub/blankly/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 771, in run
self.price_events[0]['function'](self.interface.get_price(self.price_events[0]['asset_id']),
File "/Users/rohitsathyanathan/Desktop/ML/GitHub/blankly/examples/golden_cross.py", line 40, in price_event
interface.market_order(symbol, 'sell', int(interface.account[symbol].available))
KeyError: 'BTC-USDT'
Progress: [##########] 100% Done...
When I try the RSI code on the Google Colab Jupyter, I get the following error.
TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''INFO: "use_yfinance" not specified in preferences, defaulting to: "False"
No cached data found for ETH-USDT from: 1642515960 to 1642524144 at a resolution of 3600 seconds.
Initializing...
Backtesting...
Progress: [#---------] 14.87% Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 706, in run
'state_object'])
File "<ipython-input-3-1733380c8989>", line 10, in price_event
state.interface.market_order(symbol, side='buy', size=buy)
File "/usr/local/lib/python3.7/dist-packages/blankly/exchanges/interfaces/paper_trade/paper_trade_interface.py", line 363, in market_order
raise InvalidOrder(f"Size is too small. Minimum is: {min_size}. You requested {size}.")
blankly.utils.exceptions.InvalidOrder: Size is too small. Minimum is: 0.0001. You requested 0.
Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 706, in run
'state_object'])
File "<ipython-input-3-1733380c8989>", line 10, in price_event
state.interface.market_order(symbol, side='buy', size=buy)
File "/usr/local/lib/python3.7/dist-packages/blankly/exchanges/interfaces/paper_trade/paper_trade_interface.py", line 363, in market_order
raise InvalidOrder(f"Size is too small. Minimum is: {min_size}. You requested {size}.")
blankly.utils.exceptions.InvalidOrder: Size is too small. Minimum is: 0.0001. You requested 0.
Traceback (most recent call last):
...
/usr/local/lib/python3.7/dist-packages/blankly/metrics/portfolio.py:55: RuntimeWarning: invalid value encountered in double_scalars
return mean / std
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-3-1733380c8989> in <module>()
30 # strategy.start()
31 # Or backtest using this
---> 32 results = strategy.backtest(to='1y', initial_values={'USDT': 10000})
33 print(results)
1 frames
/usr/local/lib/python3.7/dist-packages/blankly/exchanges/interfaces/paper_trade/backtest_controller.py in run(self)
908 # Lastly remove Nan values in the metrics
909 for i in metrics_indicators:
--> 910 if np.isnan(metrics_indicators[i]):
911 metrics_indicators[i] = None
912
TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
When I try the RSI code on the Windows desktop, I get the following error.
c:\python38\lib\site-packages\blankly\metrics\portfolio.py:60: RuntimeWarning: invalid value encountered in double_scalars
return return_series.mean() * n / abs(max_drawdown(return_series))
Hello, it seems that the work continues at full speed. An update is required for the line below.
examples/custom_model.py
....
from models import OrderPricingModel, OrderDecisionModel
....While using Coinbase Pro I made a typo and used "XRP-USD" as the price_event symbol, blankly raised a generic error message (thrown at https://github.com/Blankly-Finance/Blankly/blob/main/blankly/exchanges/interfaces/coinbase_pro/coinbase_pro_interface.py#L463) which didn't really help.
I'm willing to help adding a more fine-grained exception control and helpful error messages wherever needed.
We can add listener to a ticker stream via
strategy.add_price_event(price_event, symbol='BTC-USD', resolution='1d', init=init)
How to remove a subscribed ticker?
This would enabled dynamic ticker selection in our strategy
strategy.delete_price_event()
or
strategy.all_subscribed_events.delete(id)
Give us some of your initial thoughts for implementing this.
Additional Information
Add any other context about the feature request here including what other packages have done, linked issues, and more.
Hi,
Thank you for the very useful package!
I'm trying to backtest a strategy that involves shorting a stock/crypto. This means I make a call like:
interface.market_order('MSFT', 'sell', 1)
in a price_event function.
This results in an error message such as:
*** blankly.utils.exceptions.InvalidOrder: Not enough base currency. Available: 0.0. hold: 0. requested: 1.
I'd expect to be able to short on Alpaca, as doing a 'sell' market order (e.g. through their web console) with 0 position is successful.
Note: I've gotten the same results with
alpaca = Alpaca()
s = Strategy(alpaca)
and
coinbase = CoinbasePro()
crypto = Strategy(coinbase)
Is this intentional? Thanks so much!
Returns in results.metrics["Cumulative Returns (%)"] don't match charted returns in Bokehplot or Account Value (USD) in Account History
2dAdditional context
A clear and concise description of what the bug is.
Your default issue template suggests wrongish syntax highlighting for the codeblocks, which is a little confusing:
For example:
## settings.json
```python
settings.json here
```
Should probably be:
## settings.json
```json
settings.json here
```
Similarly:
## backtest.json (if applicable)
```python
backtest.json here
```
Also
## Error (if applicable)
```python
Error here
```
Should probably be
## Error (if applicable)
```plaintext
Error here
```
I have issues when backtesting with Binance api
{
"settings": {
"use_sandbox": false,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "com"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD",
"enable_shorting": true,
"use_yfinance": false
},
"oanda": {
"cash": "USD"
}
}
}{
"price_data": {
"assets": []
},
"settings": {
"use_price": "close",
"smooth_prices": false,
"GUI_output": true,
"show_tickers_with_zero_delta": false,
"save_initial_account_value": true,
"show_progress_during_backtest": true,
"cache_location": "./price_caches",
"continuous_caching": true,
"resample_account_value_for_metrics": "1d",
"quote_account_value_in": "USDT",
"ignore_user_exceptions": true,
"risk_free_return_rate": 0.0,
"benchmark_symbol" : null
}
}Traceback (most recent call last):
File "C:\Users\me\PycharmProjects\bot-v2\venv\lib\site-packages\blankly\exchanges\interfaces\paper_trade\backtest_controller.py", line 771, in run
self.price_events[0]['function'](self.interface.get_price(self.price_events[0]['asset_id']),
File "C:\Users\me\PycharmProjects\bot-v2\stonks.py", line 20, in price_event
quantity = int(state.interface.account[symbol].available)
KeyError: 'ALGO-USDT'
Additional context
I copied the code in the youtube tutorial
Some problem with the order size. Seems like we can't buy fractional coins?
Of course it can easily happen that I misunderstood something, but then a more verbose error would be better
{
"settings": {
"account_update_time": 5000,
"use_sandbox": false,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "EUR"
}
}
}{
"price_data": {
"assets": []
},
"settings": {
"use_price": "close",
"smooth_prices": false,
"GUI_output": false,
"show_tickers_with_zero_delta": false,
"save_initial_account_value": true,
"show_progress_during_backtest": true,
"cache_location": "./price_caches",
"continuous_caching": true,
"resample_account_value_for_metrics": "1d",
"quote_account_value_in": "EUR",
"ignore_user_exceptions": false
}
}blankly.utils.exceptions.InvalidOrder: Size resolution is too high, the highest resolution allowed for this symbol is: 1e-08. You specified 0.008585614459548448.
Traceback (most recent call last):
File "bot.py", line 36, in <module>
results = strategy.backtest(to="1y", initial_values={"EUR": 100})
File "/Users/gabor.vecsei/anaconda3/lib/python3.8/site-packages/blankly/frameworks/strategy/strategy_base.py", line 493, in backtest
results = self.backtesting_controller.run()
File "/Users/gabor.vecsei/anaconda3/lib/python3.8/site-packages/blankly/exchanges/interfaces/paper_trade/backtest_controller.py", line 878, in run
metrics_indicators['Compound Annual Growth Rate (%)'] = metrics.cagr(dataframes)
File "/Users/gabor.vecsei/anaconda3/lib/python3.8/site-packages/blankly/exchanges/interfaces/paper_trade/metrics.py", line 26, in cagr
return round(metrics.cagr(account_values['value'].iloc[0], account_values['value'].iloc[-1], years), 2) * 100
File "/Users/gabor.vecsei/anaconda3/lib/python3.8/site-packages/blankly/metrics/portfolio.py", line 31, in cagr
return (end_value / start_value) ** (1 / years) - 1
ZeroDivisionError: division by zeroThis was the quick test code which produced the error:
import blankly
def price_event(price, symbol, state: blankly.StrategyState):
state.variables["step_count"] += 1
if state.variables["step_count"] == 1:
buy = state.interface.cash / price
state.interface.market_order(symbol, side="buy", size=buy)
if state.variables["step_count"] == 30:
curr_value = state.interface.account[symbol].available
state.interface.market_order(symbol, side='sell', size=curr_value)
def init(symbol, state: blankly.StrategyState):
# Download price data to give context to the algo
state.variables["history"] = state.interface.history(symbol, to=150, return_as="deque")["close"]
state.variables["owns_position"] = False
state.variables["step_count"] = 0
if __name__ == "__main__":
# Authenticate coinbase pro strategy
exchange = blankly.CoinbasePro(portfolio_name="algotrade_test_portfolio")
# Use our strategy helper on coinbase pro
strategy = blankly.Strategy(exchange)
# 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="BTC-EUR", resolution="1d", init=init)
# Start the strategy. This will begin each of the price event ticks
# strategy.start()
# Or backtest using this
results = strategy.backtest(to="1y", initial_values={"EUR": 100})
print(results)Hi!
I'm trying to paper trade an algorithm with Alpaca. When I fill an order with blankly, it prints Paper Trading... in the terminal, but if i log into my Alpaca account, nothing has happened.
In keys.json I added the API keys to my Alpaca paper account.
my settings are
{
"settings": {
"account_update_time": 5000,
"use_sandbox": true,
"use_sandbox_websockets": false,
"websocket_buffer_size": 10000,
"test_connectivity_on_auth": true,
"coinbase_pro": {
"cash": "USD"
},
"binance": {
"cash": "USDT",
"binance_tld": "us"
},
"alpaca": {
"websocket_stream": "iex",
"cash": "USD",
"enable_shorting": true
},
"oanda": {
"cash": "USD"
}
}
}
Thanks.
Running a backtest of 1 month with 60 seconds resolution strategy.backtest(to="1M", ...) on Binance XRP-USDT pair crashes when calculating RSI.
24h, 48h and 96h works fine but going up to 168h/1w causes same crash.
File "F:\Trunk\wine\blankly-test\models\RelativeStrengthIndexDecisionModel.py", line 16, in __call__
rsi = blankly.indicators.rsi(state.variables["history"], self.period)
File "C:\Users\ian\AppData\Local\Programs\Python\Python39\lib\site-packages\blankly\indicators\oscillators.py", line 33, in rsi
rsi_values = ti.rsi(data, period)
File "C:\Users\ian\AppData\Local\Programs\Python\Python39\lib\site-packages\tulipy\__init__.py", line 1003, in rsi
return lib.rsi([real], [period])
File "tulipy\lib\__init__.pyx", line 105, in tulipy.lib._Indicator.__call__
tulipy.lib.InvalidOptionErrorXRP-USDT pair on Binance' LOT_SIZE from https://api.binance.com/api/v1/exchangeInfo:
{
"filterType": "LOT_SIZE",
"minQty": "1.00000000",
"maxQty": "9222449.00000000",
"stepSize": "1.00000000"
},Calculating amount of decimals like this:
filter = state.interface.get_order_filter(symbol)
increment = filter["market_order"]["base_increment"]
decimals = abs(Decimal(str(increment)).as_tuple().exponent() # I forget from where; but this is taken from the Blankly sourceDecimals is 1 but should be 0 (?)
size = state.interface.cash / price
size = blankly.trunc(size, decimals)When creating a market buy order Binance returns LOT_SIZE error.
My current solution is wrapping the market buy order in two try/except statements like this:
try:
state.interface.market_order(symbol, "buy", size)
except:
try:
state.interface.market_order(symbol, "buy", blankly.trunc(size, decimals - 1))
except Exception as e:
print(e)Is there a more proper/elegant way of doing this?
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