The provided code snippet appears to be a partial implementation of a backtesting strategy for trading on the Binance exchange. Here's a short description of what the strategy does:
The strategy is implemented as a class named "BinanceStream" that inherits from the "IStrategy" class. It also uses another class named "BasePairInfo" and an "OrderBook" class.
The strategy has the following methods: populate_indicators: This method takes a DataFrame and metadata as input and returns the updated DataFrame.
However, in the given code snippet, it simply returns the original DataFrame without any modifications.
populate_buy_trend: This method takes a DataFrame and metadata as input and returns the updated DataFrame. It checks whether the current pair should be bought by calling the check_buy() method of the corresponding pair in the BasePairInfo class. If the pair should be bought, it sets the "buy" column of the DataFrame at the latest index to 1; otherwise, it sets it to 0. populate_sell_trend: This method is similar to populate_buy_trend but checks whether the current pair should be sold by calling the check_sell() method of the corresponding pair in the BasePairInfo class. If the pair should be sold, it sets the "sell" column of the DataFrame at the latest index to 1; otherwise, it sets it to 0. Other methods: There are several other methods and statements in the code snippet, but their purpose and functionality are not clear due to the incomplete code. Additionally, the code snippet includes a commented message format representing a Kline event, which might be used for handling real-time market data. The code also defines a list named ohlcv which contains the column names for Open, High, Low, Close, and Volume in the order book. Lastly, there is an OrderBook class, but its implementation is not provided in the code snippet. Please note that the provided code is incomplete and lacks essential details to fully understand the strategy's functionality.
The strategy has the following methods: populate_indicators: This method takes a DataFrame and metadata as input and returns the updated DataFrame.
However, in the given code snippet, it simply returns the original DataFrame without any modifications.
populate_buy_trend: This method takes a DataFrame and metadata as input and returns the updated DataFrame. It checks whether the current pair should be bought by calling the check_buy() method of the corresponding pair in the BasePairInfo class. If the pair should be bought, it sets the "buy" column of the DataFrame at the latest index to 1; otherwise, it sets it to 0. populate_sell_trend: This method is similar to populate_buy_trend but checks whether the current pair should be sold by calling the check_sell() method of the corresponding pair in the BasePairInfo class. If the pair should be sold, it sets the "sell" column of the DataFrame at the latest index to 1; otherwise, it sets it to 0. Other methods: There are several other methods and statements in the code snippet, but their purpose and functionality are not clear due to the incomplete code. Additionally, the code snippet includes a commented message format representing a Kline event, which might be used for handling real-time market data. The code also defines a list named ohlcv which contains the column names for Open, High, Low, Close, and Volume in the order book. Lastly, there is an OrderBook class, but its implementation is not provided in the code snippet. Please note that the provided code is incomplete and lacks essential details to fully understand the strategy's functionality.
stoploss: 0 timeframe: 5m hash(sha256): f61d09e0c6b48c2ed04b717a95871c11a7dc00af0664945cb7d4c861d25fb765
Was not able to fetch indicators from Strategyfile.
last change: 2024-04-29 01:35:31