Add template for new-hyperopt command

freqtrade/configuration/arguments.py

@@ -41,6 +41,8 @@ ARGS_CREATE_USERDIR = ["user_data_dir", "reset"]
 
 ARGS_BUILD_STRATEGY = ["user_data_dir", "strategy"]
 
+ARGS_BUILD_HYPEROPT = ["user_data_dir", "hyperopt"]
+
 ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "download_trades", "exchange",
                       "timeframes", "erase"]
 
@@ -54,7 +56,7 @@ ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url",
 NO_CONF_REQURIED = ["download-data", "list-timeframes", "list-markets", "list-pairs",
                     "plot-dataframe", "plot-profit"]
 
-NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
+NO_CONF_ALLOWED = ["create-userdir", "list-exchanges","new-hyperopt", "new-strategy"]
 
 
 class Arguments:
@@ -119,7 +121,7 @@ class Arguments:
         from freqtrade.optimize import start_backtesting, start_hyperopt, start_edge
         from freqtrade.utils import (start_create_userdir, start_download_data,
                                      start_list_exchanges, start_list_markets,
-                                     start_new_strategy,
+                                     start_new_hyperopt, start_new_strategy,
                                      start_list_timeframes, start_trading)
         from freqtrade.plot.plot_utils import start_plot_dataframe, start_plot_profit
 
@@ -167,6 +169,12 @@ class Arguments:
         build_strategy_cmd.set_defaults(func=start_new_strategy)
         self._build_args(optionlist=ARGS_BUILD_STRATEGY, parser=build_strategy_cmd)
 
+        # add new-hyperopt subcommand
+        build_hyperopt_cmd = subparsers.add_parser('new-hyperopt',
+                                                   help="Create new hyperopt")
+        build_hyperopt_cmd.set_defaults(func=start_new_hyperopt)
+        self._build_args(optionlist=ARGS_BUILD_HYPEROPT, parser=build_hyperopt_cmd)
+
         # Add list-exchanges subcommand
         list_exchanges_cmd = subparsers.add_parser(
             'list-exchanges',

freqtrade/templates/base_hyperopt.py.j2

@@ -0,0 +1,154 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+from functools import reduce
+from typing import Any, Callable, Dict, List
+
+import numpy as np  # noqa
+import talib.abstract as ta
+from pandas import DataFrame
+from skopt.space import Categorical, Dimension, Integer, Real  # noqa
+
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+from freqtrade.optimize.hyperopt_interface import IHyperOpt
+
+
+class {{ hyperopt }}(IHyperOpt):
+    """
+    This is a Hyperopt template to get you started.
+
+    More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md
+
+    You should:
+    - Add any lib you need to build your hyperopt.
+
+    You must keep:
+    - The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
+
+    The roi_space, generate_roi_table, stoploss_space methods are no longer required to be
+    copied in every custom hyperopt. However, you may override them if you need the
+    'roi' and the 'stoploss' spaces that differ from the defaults offered by Freqtrade.
+    Sample implementation of these methods can be found in
+    https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py
+    """
+
+    @staticmethod
+    def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
+        """
+        Define the buy strategy parameters to be used by Hyperopt.
+        """
+        def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
+            """
+            Buy strategy Hyperopt will build and use.
+            """
+            conditions = []
+
+            # GUARDS AND TRENDS
+            if 'mfi-enabled' in params and params['mfi-enabled']:
+                conditions.append(dataframe['mfi'] < params['mfi-value'])
+            if 'fastd-enabled' in params and params['fastd-enabled']:
+                conditions.append(dataframe['fastd'] < params['fastd-value'])
+            if 'adx-enabled' in params and params['adx-enabled']:
+                conditions.append(dataframe['adx'] > params['adx-value'])
+            if 'rsi-enabled' in params and params['rsi-enabled']:
+                conditions.append(dataframe['rsi'] < params['rsi-value'])
+
+            # TRIGGERS
+            if 'trigger' in params:
+                if params['trigger'] == 'bb_lower':
+                    conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
+                if params['trigger'] == 'macd_cross_signal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['macd'], dataframe['macdsignal']
+                    ))
+                if params['trigger'] == 'sar_reversal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['close'], dataframe['sar']
+                    ))
+
+            if conditions:
+                dataframe.loc[
+                    reduce(lambda x, y: x & y, conditions),
+                    'buy'] = 1
+
+            return dataframe
+
+        return populate_buy_trend
+
+    @staticmethod
+    def indicator_space() -> List[Dimension]:
+        """
+        Define your Hyperopt space for searching buy strategy parameters.
+        """
+        return [
+            Integer(10, 25, name='mfi-value'),
+            Integer(15, 45, name='fastd-value'),
+            Integer(20, 50, name='adx-value'),
+            Integer(20, 40, name='rsi-value'),
+            Categorical([True, False], name='mfi-enabled'),
+            Categorical([True, False], name='fastd-enabled'),
+            Categorical([True, False], name='adx-enabled'),
+            Categorical([True, False], name='rsi-enabled'),
+            Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
+        ]
+
+    @staticmethod
+    def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
+        """
+        Define the sell strategy parameters to be used by Hyperopt.
+        """
+        def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
+            """
+            Sell strategy Hyperopt will build and use.
+            """
+            conditions = []
+
+            # GUARDS AND TRENDS
+            if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
+                conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
+            if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
+                conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
+            if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
+                conditions.append(dataframe['adx'] < params['sell-adx-value'])
+            if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
+                conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
+
+            # TRIGGERS
+            if 'sell-trigger' in params:
+                if params['sell-trigger'] == 'sell-bb_upper':
+                    conditions.append(dataframe['close'] > dataframe['bb_upperband'])
+                if params['sell-trigger'] == 'sell-macd_cross_signal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['macdsignal'], dataframe['macd']
+                    ))
+                if params['sell-trigger'] == 'sell-sar_reversal':
+                    conditions.append(qtpylib.crossed_above(
+                        dataframe['sar'], dataframe['close']
+                    ))
+
+            if conditions:
+                dataframe.loc[
+                    reduce(lambda x, y: x & y, conditions),
+                    'sell'] = 1
+
+            return dataframe
+
+        return populate_sell_trend
+
+    @staticmethod
+    def sell_indicator_space() -> List[Dimension]:
+        """
+        Define your Hyperopt space for searching sell strategy parameters.
+        """
+        return [
+            Integer(75, 100, name='sell-mfi-value'),
+            Integer(50, 100, name='sell-fastd-value'),
+            Integer(50, 100, name='sell-adx-value'),
+            Integer(60, 100, name='sell-rsi-value'),
+            Categorical([True, False], name='sell-mfi-enabled'),
+            Categorical([True, False], name='sell-fastd-enabled'),
+            Categorical([True, False], name='sell-adx-enabled'),
+            Categorical([True, False], name='sell-rsi-enabled'),
+            Categorical(['sell-bb_upper',
+                         'sell-macd_cross_signal',
+                         'sell-sar_reversal'], name='sell-trigger')
+        ]

freqtrade/utils.py

@@ -14,7 +14,7 @@ from freqtrade.configuration import (Configuration, TimeRange,
                                      remove_credentials)
 from freqtrade.configuration.directory_operations import (copy_sample_files,
                                                           create_userdata_dir)
-from freqtrade.constants import DEFAULT_STRATEGY
+from freqtrade.constants import DEFAULT_HYPEROPT, DEFAULT_STRATEGY
 from freqtrade.data.history import (convert_trades_to_ohlcv,
                                     refresh_backtest_ohlcv_data,
                                     refresh_backtest_trades_data)
@@ -115,6 +115,30 @@ def start_new_strategy(args: Dict[str, Any]) -> None:
         sys.exit(1)
 
 
+def start_new_hyperopt(args: Dict[str, Any]) -> None:
+
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    if "hyperopt" in args and args["hyperopt"]:
+        if args["hyperopt"] == DEFAULT_HYPEROPT:
+            raise OperationalException("DefaultHyperOpt is not allowed as name.")
+
+        new_path = config['user_data_dir'] / "hyperopts" / (args["hyperopt"] + ".py")
+
+        if new_path.exists():
+            raise OperationalException(f"`{new_path}` already exists. "
+                                       "Please choose another Strategy Name.")
+
+        strategy_text = render_template(template='base_hyperopt.py.j2',
+                                        arguments={"hyperopt": args["hyperopt"]})
+
+        logger.info(f"Writing hyperopt to `{new_path}`.")
+        new_path.write_text(strategy_text)
+    else:
+        logger.warning("`new-hyperopt` requires --hyperopt to be set.")
+        sys.exit(1)
+
+
 def start_download_data(args: Dict[str, Any]) -> None:
     """
     Download data (former download_backtest_data.py script)