Metadata-Version: 2.1
Name: testwise
Version: 0.0.59
Summary: A backtester (backtest helper) for testing my trading strategies.
Home-page: https://github.com/aticio/testwise
Author: Özgür Atıcı
Author-email: aticiozgur@gmail.com
License: UNKNOWN
Description: # Testwise
        
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        A backtester (backtest helper) for testing my trading strategies.
        
        ## Example Usage
        Note: Explanatory comments will be updated soon.
        ```python
        # Testwise is a backtester library that requires some coding knowledge
        # There is no cli or interface. 
        # You should directly execute necessary functions like enter_long() or exit_short()
        # This is a backtesting example of Exponantial Moving Average cross strategy.
        # There is 1.5 ATR stop loss level and 1 ATR take profit level for every position. 
        # Commission rate is 0.1000%. 
        # Margin usage is allowed up to 5 times the main capital.
        from datetime import datetime, timedelta
        from testwise import Testwise
        import requests
        from legitindicators import ema, atr
        
        # In this example, daily BTCUSDT kline data is used from binance
        # Let's say you want to backtest your strategy for 180 days.
        # It would be useful to add some extra days to the specified time interval
        # for the indicators to work properly.
        # (For example a 10 days of EMA won't be calculated for the first 9 days of time range)
        # In this examle I add 40 extra days. This value can be determined by assigning the TRIM variable
        TRIM = 40
        BINANCE_URL = "https://api.binance.com/api/v3/klines"
        SYMBOL = "BTCUSDT"
        INTERVAL = "1d"
        
        # These are the initial paramteres for backtester.
        # You can find a more detailed explanation where the Testwise definition is given below.
        COMMISSION = 0.001
        DYNAMIC_POSITIONING = True
        MARGIN_FACTOR = 5
        LIMIT_FACTOR = 1
        RISK_FACTOR = 1.5
        
        
        def main():
            # Here we define start time and end time of backtest.
            # Notice usage of TRIM variable to start backtest a few days earlier for proper indicator use.
            start_time = datetime(2020, 6, 1, 0, 0, 0)
            start_time = start_time - timedelta(days=TRIM)
        
            end_time = datetime(2021, 9, 1, 0, 0, 0)
        
            # In this example, timestamps are used. (Because binance api requests accept timestamp)
            start_time_ts = int(datetime.timestamp(start_time) * 1000)
            end_time_ts = int(datetime.timestamp(end_time) * 1000)
        
            backtest(start_time_ts, end_time_ts)
        
        
        def backtest(start_time, end_time):
            # Getting OHLC data
            params = {"symbol": SYMBOL, "interval": INTERVAL, "startTime": start_time, "endTime": end_time}
            data = get_data(params)
            opn, high, low, close = get_ohlc(data)
        
            # Backtest section
            lookback = len(data) - TRIM
        
            data = data[-lookback:]
            close_tmp = close[-lookback:]
            opn = opn[-lookback:]
            high = high[-lookback:]
            low = low[-lookback:]
        
            # ATR
            atr_input = []
            for i, _ in enumerate(data):
                ohlc = [opn[i], high[i], low[i], close_tmp[i]]
                atr_input.append(ohlc)
            atrng = atr(atr_input, 14)
        
            for ema_length1 in range(10, 11):
                for ema_length2 in range(ema_length1 + 1, 12):
                    # When the dynamic_positioning is set to True, 
                    # the backtester will work as if the margin usage is available for use.
                    # margin_factor indicates the margin ratio. (In this example, it is 5 times the main capital)
                    # limit_factor is an ATR based take profit level. (In this example, it is 1 ATR from the position price)
                    # risk_factor is an ATR based stop loss level. (In this example, it is 1.5 ATR from the position price)
                    twise = Testwise(
                        commission=COMMISSION,
                        dynamic_positioning=DYNAMIC_POSITIONING,
                        margin_factor=MARGIN_FACTOR,
                        limit_factor=LIMIT_FACTOR,
                        risk_factor=RISK_FACTOR
                    )
        
                    ema_first = ema(close, ema_length1)
                    ema_second = ema(close, ema_length2)
                    ema_first = ema_first[-lookback:]
                    ema_second = ema_second[-lookback:]
        
                    for i, _ in enumerate(data):
                        if i > 1 and i < len(data) - 1:
                            date_open = datetime.fromtimestamp(int(data[i+1][0] / 1000)).strftime("%Y-%m-%d %H")
                            date_close = datetime.fromtimestamp(int(data[i][0] / 1000)).strftime("%Y-%m-%d %H")
        
                            # Position exits
                            if twise.pos == 1 and (ema_first[i] < ema_second[i]):
                                twise.exit_long(date_close, opn[i + 1], twise.current_open_pos["qty"])
        
                            if twise.pos == -1 and (ema_first[i] > ema_second[i]):
                                twise.exit_short(date_close, opn[i + 1], twise.current_open_pos["qty"])
        
                            if abs(high[i] - opn[i]) < abs(low[i] - opn[i]):
                                # open - high - low - close
        
                                # if long
                                #   TP check
                                if twise.pos == 1 and high[i] > twise.current_open_pos["tp"] and twise.current_open_pos["tptaken"] is False:
                                    twise.break_even()
                                    twise.exit_long(date_close, twise.current_open_pos["tp"], twise.current_open_pos["qty"] / 2, True)
        
                                #   SL check
                                if twise.pos == 1 and low[i] < twise.current_open_pos["sl"]:
                                    twise.exit_long(date_close, twise.current_open_pos["sl"], twise.current_open_pos["qty"])
        
                                # if short
                                #   SL check
                                if twise.pos == -1 and high[i] > twise.current_open_pos["sl"]:
                                    twise.exit_short(date_close, twise.current_open_pos["sl"], twise.current_open_pos["qty"])
        
                                #   TP check
                                if twise.pos == -1 and low[i] < twise.current_open_pos["tp"] and twise.current_open_pos["tptaken"] is False:
                                    twise.break_even()
                                    twise.exit_short(date_close, twise.current_open_pos["tp"], twise.current_open_pos["qty"] / 2, True)
                            else:
                                # open - low - high - close
        
                                # if long
                                #   SL check
                                if twise.pos == 1 and low[i] < twise.current_open_pos["sl"]:
                                    twise.exit_long(date_close, twise.current_open_pos["sl"], twise.current_open_pos["qty"])
        
                                #   TP check
                                if twise.pos == 1 and high[i] > twise.current_open_pos["tp"] and twise.current_open_pos["tptaken"] is False:
                                    twise.break_even()
                                    twise.exit_long(date_close, twise.current_open_pos["tp"], twise.current_open_pos["qty"] / 2, True)
        
                                # if short
                                #   TP check
                                if twise.pos == -1 and low[i] < twise.current_open_pos["tp"] and twise.current_open_pos["tptaken"] is False:
                                    twise.break_even()
                                    twise.exit_short(date_close, twise.current_open_pos["tp"], twise.current_open_pos["qty"] / 2, True)
        
                                #   SL check
                                if twise.pos == -1 and high[i] > twise.current_open_pos["sl"]:
                                    twise.exit_short(date_close, twise.current_open_pos["sl"], twise.current_open_pos["qty"])
        
                            # Open position
                            if twise.pos != 1:
                                if ema_first[i] > ema_second[i]:
                                    share = twise.calculate_share(atrng[i], custom_position_risk=0.02)
                                    twise.entry_long(date_open, opn[i + 1], share, atrng[i])
        
                            if twise.pos != -1:
                                if ema_first[i] < ema_second[i]:
                                    share = twise.calculate_share(atrng[i], custom_position_risk=0.02)
                                    twise.entry_short(date_open, opn[i + 1], share, atrng[i])
                    print(twise.get_result())
        
        
        def get_data(params):
            r = requests.get(url=BINANCE_URL, params=params)
            data = r.json()
            return data
        
        
        def get_ohlc(data):
            opn = [float(o[1]) for o in data]
            close = [float(d[4]) for d in data]
            high = [float(h[2]) for h in data]
            low = [float(lo[3]) for lo in data]
        
            return opn, high, low, close
        
        
        if __name__ == "__main__":
            main()
        ```
        
        ## Installation
        
        Run the following to install:
        
        ```python
        pip install testwise
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Provides-Extra: dev
