ghzgod
commented
3 months ago I believe I fixed it by checking the datasource_class first and then adding polygone keys if needed
@classmethod
def backtest(
cls,
datasource_class, # Ensure datasource_class is passed as an argument
*args,
minutes_before_closing=1,
minutes_before_opening=60,
sleeptime=1,
stats_file=None,
risk_free_rate=None,
logfile=None,
config=None,
auto_adjust=False,
name=None,
budget=None,
benchmark_asset="SPY",
plot_file_html=None,
trades_file=None,
settings_file=None,
pandas_data=None,
quote_asset=Asset(symbol="USD", asset_type="forex"),
starting_positions=None,
show_plot=True,
tearsheet_file=None,
save_tearsheet=True,
show_tearsheet=True,
parameters={},
buy_trading_fees=[],
sell_trading_fees=[],
api_key=None,
polygon_api_key=None,
polygon_has_paid_subscription=None, # Deprecated, remove in future versions.
indicators_file=None,
show_indicators=True,
save_logfile=False,
**kwargs,
):
"""Backtest a strategy.
Parameters
----------
datasource_class : class
The datasource class to use. For example, if you want to use the yahoo finance datasource, then you
would pass YahooDataBacktesting as the datasource_class.
backtesting_start : datetime
The start date of the backtesting period.
backtesting_end : datetime
The end date of the backtesting period.
minutes_before_closing : int
The number of minutes before closing that the minutes_before_closing strategy method will be called.
minutes_before_opening : int
The number of minutes before opening that the minutes_before_opening strategy method will be called.
sleeptime : int
The number of seconds to sleep between each iteration of the backtest.
stats_file : str
The file to write the stats to.
risk_free_rate : float
The risk free rate to use.
logfile : str
The file to write the log to.
config : dict
The config to use to set up the brokers in live trading.
auto_adjust : bool
Whether or not to automatically adjust the strategy.
name : str
The name of the strategy.
budget : float
The initial budget to use for the backtest.
benchmark_asset : str or Asset
The benchmark asset to use for the backtest to compare to. If it is a string then it will be converted
to a stock Asset object.
plot_file_html : str
The file to write the plot html to.
trades_file : str
The file to write the trades to.
pandas_data : list
A list of Data objects that are used when the datasource_class object is set to PandasDataBacktesting.
This contains all the data that will be used in backtesting.
quote_asset : Asset (crypto)
An Asset object for the crypto currency that will get used
as a valuation asset for measuring overall porfolio values.
Usually USDT, USD, USDC.
starting_positions : dict
A dictionary of starting positions for each asset. For example,
if you want to start with $100 of SPY, and $200 of AAPL, then you
would pass in starting_positions={'SPY': 100, 'AAPL': 200}.
show_plot : bool
Whether to show the plot.
show_tearsheet : bool
Whether to show the tearsheet.
save_tearsheet : bool
Whether to save the tearsheet.
parameters : dict
A dictionary of parameters to pass to the strategy. These parameters
must be set up within the initialize() method.
buy_trading_fees : list of TradingFee objects
A list of TradingFee objects to apply to the buy orders during backtests.
sell_trading_fees : list of TradingFee objects
A list of TradingFee objects to apply to the sell orders during backtests.
api_key : str
The polygon api key to use for polygon data. Only required if you are using PolygonDataBacktesting as
the datasource_class.
polygon_api_key : str
The polygon api key to use for polygon data. Only required if you are using PolygonDataBacktesting as
the datasource_class. Depricated, please use 'api_key' instead.
indicators_file : str
The file to write the indicators to.
show_indicators : bool
Whether to show the indicators plot.
save_logfile : bool
Whether to save the logs to a file. If True, the logs will be saved to the logs directory. Defaults to False.
Turning on this option will slow down the backtest.
Returns
-------
result : dict
A dictionary of the backtest results. Eg.
Examples
--------
>>> from datetime import datetime
>>> from lumibot.backtesting import YahooDataBacktesting
>>> from lumibot.strategies import Strategy
>>>
>>> # A simple strategy that buys AAPL on the first day
>>> class MyStrategy(Strategy):
>>> def on_trading_iteration(self):
>>> if self.first_iteration:
>>> order = self.create_order("AAPL", quantity=1, side="buy")
>>> self.submit_order(order)
>>>
>>> # Create a backtest
>>> backtesting_start = datetime(2018, 1, 1)
>>> backtesting_end = datetime(2018, 1, 31)
>>>
>>> # The benchmark asset to use for the backtest to compare to
>>> benchmark_asset = Asset(symbol="QQQ", asset_type="stock")
>>>
>>> backtest = MyStrategy.backtest(
>>> datasource_class=YahooDataBacktesting,
>>> backtesting_start=backtesting_start,
>>> backtesting_end=backtesting_end,
>>> benchmark_asset=benchmark_asset,
>>> )
"""
"""Backtest a strategy."""
# Create a dictionary of keyword arguments to pass to the run_backtest method
run_backtest_kwargs = {
"minutes_before_closing": minutes_before_closing,
"minutes_before_opening": minutes_before_opening,
"sleeptime": sleeptime,
"stats_file": stats_file,
"risk_free_rate": risk_free_rate,
"logfile": logfile,
"config": config,
"auto_adjust": auto_adjust,
"name": name,
"budget": budget,
"benchmark_asset": benchmark_asset,
"plot_file_html": plot_file_html,
"trades_file": trades_file,
"settings_file": settings_file,
"pandas_data": pandas_data,
"quote_asset": quote_asset,
"starting_positions": starting_positions,
"show_plot": show_plot,
"tearsheet_file": tearsheet_file,
"save_tearsheet": save_tearsheet,
"show_tearsheet": show_tearsheet,
"parameters": parameters,
"buy_trading_fees": buy_trading_fees,
"sell_trading_fees": sell_trading_fees,
"api_key": api_key,
"indicators_file": indicators_file,
"show_indicators": show_indicators,
"save_logfile": save_logfile,
**kwargs,
}
# Include Polygon-specific arguments if the datasource_class is PolygonDataBacktesting
if datasource_class == PolygonDataBacktesting:
run_backtest_kwargs["polygon_api_key"] = polygon_api_key
run_backtest_kwargs["polygon_has_paid_subscription"] = polygon_has_paid_subscription
results, strategy = cls.run_backtest(
datasource_class, # Pass the datasource_class here
*args,
**run_backtest_kwargs,
)
return results, strategy
Al4ise
I did a pip upgrade and now If I run YahooDataBackTest for my strategy I get an error
Here is my code:
Here is my error
If I edit the _strategy.py file and comment out the polygone data (in the below example) it begins to work as intended. Is this a bug? Hopefully this is useful information.