Merge branch 'develop' of https://github.com/Bovhasselt/Tradingbotv1.1 into develop

freqtrade/commands/__init__.py

@@ -12,7 +12,7 @@ from freqtrade.commands.data_commands import (start_convert_data, start_download
                                               start_list_data)
 from freqtrade.commands.deploy_commands import (start_create_userdir, start_install_ui,
                                                 start_new_hyperopt, start_new_strategy)
-from freqtrade.commands.automation_commands import start_build_hyperopt
+from freqtrade.commands.automation_commands import (start_build_hyperopt, start_custom_hyperopt, start_extract_strategy)
 from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show
 from freqtrade.commands.list_commands import (start_list_exchanges, start_list_hyperopts,
                                               start_list_markets, start_list_strategies,

freqtrade/commands/arguments.py

@@ -55,8 +55,13 @@ ARGS_BUILD_STRATEGY = ["user_data_dir", "strategy", "template"]
 
 ARGS_BUILD_HYPEROPT = ["user_data_dir", "hyperopt", "template"]
 
+# Automation
 ARGS_BUILD_CUSTOM_HYPEROPT = ["buy_indicators", "sell_indicators", "hyperopt"]
 
+ARGS_EXTRACT_STRATEGY = ["strategy", "extract_name"]
+
+ARGS_BUILD_BUILD_HYPEROPT = ["strategy", "hyperopt"]
+
 ARGS_CONVERT_DATA = ["pairs", "format_from", "format_to", "erase"]
 ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes"]
 
@@ -175,7 +180,7 @@ class Arguments:
                                         start_list_data, start_list_exchanges, start_list_hyperopts,
                                         start_list_markets, start_list_strategies,
                                         start_list_timeframes, start_new_config, start_new_hyperopt,
-                                        start_build_hyperopt,
+                                        start_build_hyperopt, start_custom_hyperopt, start_extract_strategy,
                                         start_new_strategy, start_plot_dataframe, start_plot_profit,
                                         start_show_trades, start_test_pairlist, start_trading)
 
@@ -210,12 +215,24 @@ class Arguments:
         build_hyperopt_cmd.set_defaults(func=start_new_hyperopt)
         self._build_args(optionlist=ARGS_BUILD_HYPEROPT, parser=build_hyperopt_cmd)
 
-        # add build-hyperopt subcommand
-        build_custom_hyperopt_cmd = subparsers.add_parser('build-hyperopt',
+        # add custom-hyperopt subcommand
+        build_custom_hyperopt_cmd = subparsers.add_parser('custom-hyperopt',
                                                           help="Build a custom hyperopt")
-        build_custom_hyperopt_cmd.set_defaults(func=start_build_hyperopt)
+        build_custom_hyperopt_cmd.set_defaults(func=start_custom_hyperopt)
         self._build_args(optionlist=ARGS_BUILD_CUSTOM_HYPEROPT, parser=build_custom_hyperopt_cmd)
 
+        # add extract-strategy subcommand
+        extract_strategy_cmd = subparsers.add_parser('extract-strategy',
+                                                     help="Extract data dictionaries for custom-hyperopt from strategy")
+        extract_strategy_cmd.set_defaults(func=start_extract_strategy)
+        self._build_args(optionlist=ARGS_EXTRACT_STRATEGY, parser=extract_strategy_cmd)
+
+        # add build-hyperopt subcommand
+        build_extracted_hyperopt_cmd = subparsers.add_parser('build-hyperopt',
+                                                     help="Create a hyperopt for a strategy")
+        build_extracted_hyperopt_cmd.set_defaults(func=start_build_hyperopt)
+        self._build_args(optionlist=ARGS_BUILD_BUILD_HYPEROPT, parser=build_extracted_hyperopt_cmd)
+
         # add new-strategy subcommand
         build_strategy_cmd = subparsers.add_parser('new-strategy',
                                                    help="Create new strategy")

freqtrade/commands/automation_commands.py

@@ -1,9 +1,10 @@
 import ast
 import logging
 from pathlib import Path
-from typing import Any, Dict
+from typing import Any, Dict, List
 
-from freqtrade.constants import USERPATH_HYPEROPTS
+from freqtrade.constants import (USERPATH_HYPEROPTS,
+                                 USERPATH_STRATEGIES)
 from freqtrade.exceptions import OperationalException
 from freqtrade.state import RunMode
 from freqtrade.configuration import setup_utils_configuration
@@ -11,20 +12,139 @@ from freqtrade.misc import render_template
 
 logger = logging.getLogger(__name__)
 
-'''
-    TODO 
-    -make the code below more dynamic with a large list of indicators and aims
-    -buy_space integer values variation based on aim(later deep learning)
-    -add --mode , see notes
-    -when making the strategy reading tool, make sure that the populate indicators gets copied to here
-'''
 
-POSSIBLE_GUARDS = ["rsi", "mfi", "fastd"]
-POSSIBLE_TRIGGERS = ["bb_lowerband", "bb_upperband"]
-POSSIBLE_VALUES = {"above": ">", "below": "<"}
+# ---------------------------------------------------extract-strategy------------------------------------------------------
+
+def get_indicator_info(file: List, indicators: Dict) -> None:
+    """
+    Get all necessary information to build a custom hyperopt space using
+    the file and a dictionary filled with the indicators and their corropsonding line numbers.
+    """
+    info_list = []
+    for indicator in indicators:
+        indicator_info = []
+
+        # find the corrosponding aim
+        for position, line in enumerate(file):
+            if position == indicators[indicator]:
+                # use split twice to remove the context around the indicator
+                back_of_line = line.split(f"(dataframe['{indicator}'] ", 1)[1]
+                aim = back_of_line.split()[0]
+
+                # add the indicator and aim to the info
+                indicator_info.append(indicator)
+                indicator_info.append(aim)
+
+                # check if first character after aim is a d in which case the indicator is a trigger
+                if back_of_line.split()[1][0] == "d":
+                    indicator_info.append("trigger")
+
+                    # add the second indicator of the guard to the info list
+                    back_of_line = back_of_line.split("dataframe['")[1]
+                    second_indicator = back_of_line.split("'])")[0]
+                    indicator_info.append(second_indicator)
+
+                # elif indicator[0:3] == "CDL":
+                    # indicator_info.append("guard")
+
+                # else it is a regular guard
+                else:
+                    indicator_info.append("guard")
+
+                    value = back_of_line.split()[1]
+                    value = value[:-1]
+                    value = float(value)
+
+                    indicator_info.append(value)
+        info_list.append(indicator_info)
+
+    return info_list
 
 
-def build_hyperopt_buyelements(buy_indicators: Dict[str, str]):
+def extract_lists(strategypath: Path) -> None:
+    """
+    Get the indicators, their aims and the stoploss and format them into lists
+    """
+
+    # store the file in a list for reference
+    stored_file = []
+    with open(strategypath) as file:
+        for line in file:
+            stored_file.append(line)
+
+    # find the start and end of buy trend
+    for position, line in enumerate(stored_file):
+        if "populate_buy_trend(" in line:
+            start_buy_number = position
+        elif "populate_sell_trend(" in line:
+            end_buy_number = position
+
+    # list the numbers between the start and end of buy trend
+    buy_lines = []
+    for i in range(start_buy_number, end_buy_number):
+        buy_lines.append(i)
+
+    # populate the indicators dictionaries with indicators attached to the line they are on
+    buyindicators = {}
+    sellindicators = {}
+
+    for position, line in enumerate(stored_file):
+        # check the lines in buy trend for indicator and add them
+        if position in buy_lines and "(dataframe['" in line:
+            # use split twice to remove the context around the indicator
+            back_of_line = line.split("(dataframe['", 1)[1]
+            buyindicator = back_of_line.split("'] ", 1)[0]
+            buyindicators[buyindicator] = position
+
+        # check the lines in sell trend for indicator and add them
+        elif position > end_buy_number and "(dataframe['" in line:
+            # use split twice to remove the context around the indicator
+            back_of_line = line.split("(dataframe['", 1)[1]
+            sellindicator = back_of_line.split("'] ", 1)[0]
+            sellindicators[sellindicator] = position
+
+    # build the final lists
+    buy_info_list = get_indicator_info(stored_file, buyindicators)
+    sell_info_list = get_indicator_info(stored_file, sellindicators)
+    
+    # put the final lists into a tuple
+    final_lists = (buy_info_list, sell_info_list)
+
+    return final_lists
+
+
+def start_extract_strategy(args: Dict) -> None:
+    """
+    Check if the right subcommands where passed and start extracting the strategy data
+    """
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    # check if all required options are filled in
+    if not 'strategy' in args or not args['strategy']:
+        raise OperationalException("`extract-strategy` requires --strategy to be set.")
+    else:
+        # if the name is not specified use (strategy)_extract
+        if not 'extract_name' in args or not args['extract_name']:
+            args['extract_name'] = args['strategy'] + "_extract"
+
+        new_path = config['user_data_dir'] / USERPATH_STRATEGIES / (args['extract_name'] + '.txt')
+        if new_path.exists():
+            raise OperationalException(f"`{new_path}` already exists. "
+                                       "Please choose another name.")
+        # the path of the chosen strategy
+        strategy_path = config['user_data_dir'] / USERPATH_STRATEGIES / (args['strategy'] + '.py')
+
+        # extract the buy and sell indicators as dicts
+        extracted_lists = str(extract_lists(strategy_path))
+
+        # save the dicts in a file
+        logger.info(f"Writing custom hyperopt to `{new_path}`.")
+        new_path.write_text(extracted_lists)
+
+
+# --------------------------------------------------custom-hyperopt------------------------------------------------------
+
+def custom_hyperopt_buyelements(buy_indicators: List):
     """
     Build the arguments with the placefillers for the buygenerator
     """
@@ -32,39 +152,44 @@ def build_hyperopt_buyelements(buy_indicators: Dict[str, str]):
     buy_triggers = ""
     buy_space = ""
 
-    for indicator in buy_indicators:
-        # Error handling
-        if not indicator in POSSIBLE_GUARDS and not indicator in POSSIBLE_TRIGGERS:
-            raise OperationalException(
-                f"`{indicator}` is not part of the available indicators. The current options are {POSSIBLE_GUARDS + POSSIBLE_TRIGGERS}.")
-        elif not buy_indicators[indicator] in POSSIBLE_VALUES:
-            raise OperationalException(
-                f"`{buy_indicators[indicator]}` is not part of the available indicator options. The current options are {POSSIBLE_VALUES}.")
+    for indicator_info in buy_indicators:
+        indicator = indicator_info[0]
+        aim = indicator_info[1]
+        usage = indicator_info[2]
+
         # If the indicator is a guard
-        elif indicator in POSSIBLE_GUARDS:
-            # get the symbol corrosponding to the value
-            aim = POSSIBLE_VALUES[buy_indicators[indicator]]
+        if usage == "guard":
+            value = indicator_info[3]
+            
+            if value >= -1.0 and value <= 1.0:
+                lower_bound = value - 0.3
+                upper_bound = value + 0.3
+            else:
+                lower_bound = value - 30.0
+                upper_bound = value + 30.0
 
             # add the guard to its argument
-            buy_guards += f"if '{indicator}-enabled' in params and params['{indicator}-enabled']: conditions.append(dataframe['{indicator}'] {aim} params['{indicator}-value'])"
+            buy_guards += f"if params.get('{indicator}-enabled'):\n    conditions.append(dataframe['{indicator}'] {aim} params['{indicator}-value'])\n"
 
             # add the space to its argument
-            buy_space += f"Integer(10, 90, name='{indicator}-value'), Categorical([True, False], name='{indicator}-enabled'),"
-        # If the indicator is a trigger
-        elif indicator in POSSIBLE_TRIGGERS:
-            # get the symbol corrosponding to the value
-            aim = POSSIBLE_VALUES[buy_indicators[indicator]]
+            buy_space += f"Integer({lower_bound}, {upper_bound}, name='{indicator}-value'),\nCategorical([True, False], name='{indicator}-enabled'),\n"
 
+        # If the indicator is a trigger
+        elif usage == "trigger":
+            secondindicator = indicator_info[3]
             # add the trigger to its argument
-            buy_triggers += f"if params['trigger'] == '{indicator}': conditions.append(dataframe['{indicator}'] {aim} dataframe['close'])"
+            buy_triggers += f"if params['trigger'] == '{indicator}':\n    conditions.append(dataframe['{indicator}'] {aim} dataframe['{secondindicator}'])\n"
 
     # Final line of indicator space makes all triggers
-    
+
     buy_space += "Categorical(["
 
     # adding all triggers to the list
-    for indicator in buy_indicators:
-        if indicator in POSSIBLE_TRIGGERS:
+    for indicator_info in buy_indicators:
+        indicator = indicator_info[0]
+        usage = indicator_info[2]
+
+        if usage == "trigger":
             buy_space += f"'{indicator}', "
 
     # Deleting the last ", "
@@ -74,7 +199,7 @@ def build_hyperopt_buyelements(buy_indicators: Dict[str, str]):
     return {"buy_guards": buy_guards, "buy_triggers": buy_triggers, "buy_space": buy_space}
 
 
-def build_hyperopt_sellelements(sell_indicators: Dict[str, str]):
+def custom_hyperopt_sellelements(sell_indicators: Dict[str, str]):
     """
     Build the arguments with the placefillers for the sellgenerator
     """
@@ -82,44 +207,50 @@ def build_hyperopt_sellelements(sell_indicators: Dict[str, str]):
     sell_triggers = ""
     sell_space = ""
 
-    for indicator in sell_indicators:
-        # Error handling
-        if not indicator in POSSIBLE_GUARDS and not indicator in POSSIBLE_TRIGGERS:
-            raise OperationalException(
-                f"`{indicator}` is not part of the available indicators. The current options are {POSSIBLE_GUARDS + POSSIBLE_TRIGGERS}.")
-        elif not sell_indicators[indicator] in POSSIBLE_VALUES:
-            raise OperationalException(
-                f"`{sell_indicators[indicator]}` is not part of the available indicator options. The current options are {POSSIBLE_VALUES}.")
-        # If indicator is a guard
-        elif indicator in POSSIBLE_GUARDS:
-            # get the symbol corrosponding to the value
-            aim = POSSIBLE_VALUES[sell_indicators[indicator]]
+    for indicator_info in sell_indicators:
+        indicator = indicator_info[0]
+        aim = indicator_info[1]
+        usage = indicator_info[2]
+
+        # If the indicator is a guard
+        if usage == "guard":
+            value = indicator_info[3]
+            
+            if value >= -1 and value <= 1:
+                lower_bound = value - 0.3
+                upper_bound = value + 0.3
+            else:
+                lower_bound = value - 30
+                upper_bound = value + 30
 
             # add the guard to its argument
-            sell_guards += f"if '{indicator}-enabled' in params and params['sell-{indicator}-enabled']: conditions.append(dataframe['{indicator}'] {aim} params['sell-{indicator}-value'])"
+            sell_guards += f"if params.get('sell-{indicator}-enabled'):\n    conditions.append(dataframe['{indicator}'] {aim} params['sell-{indicator}-value'])\n"
 
             # add the space to its argument
-            sell_space += f"Integer(10, 90, name='sell-{indicator}-value'), Categorical([True, False], name='sell-{indicator}-enabled'),"
+            sell_space += f"Integer({lower_bound}, {upper_bound}, name='sell-{indicator}-value'),\nCategorical([True, False], name='sell-{indicator}-enabled'),\n"
+
         # If the indicator is a trigger
-        elif indicator in POSSIBLE_TRIGGERS:
-            # get the symbol corrosponding to the value
-            aim = POSSIBLE_VALUES[sell_indicators[indicator]]
+        elif usage == "trigger":
+            secondindicator = indicator_info[3]
 
             # add the trigger to its argument
-            sell_triggers += f"if params['sell-trigger'] == 'sell-{indicator}': conditions.append(dataframe['{indicator}'] {aim} dataframe['close'])"
+            sell_triggers += f"if params['sell-trigger'] == 'sell-{indicator}':\n    conditions.append(dataframe['{indicator}'] {aim} dataframe['{secondindicator}'])\n"
 
     # Final line of indicator space makes all triggers
 
     sell_space += "Categorical(["
 
-    # Adding all triggers to the list
-    for indicator in sell_indicators:
-        if indicator in POSSIBLE_TRIGGERS:
+    # adding all triggers to the list
+    for indicator_info in sell_indicators:
+        indicator = indicator_info[0]
+        usage = indicator_info[2]
+
+        if usage == "trigger":
             sell_space += f"'sell-{indicator}', "
 
     # Deleting the last ", "
     sell_space = sell_space[:-2]
-    sell_space += "], name='trigger')"
+    sell_space += "], name='sell-trigger')"
 
     return {"sell_guards": sell_guards, "sell_triggers": sell_triggers, "sell_space": sell_space}
 
@@ -130,11 +261,11 @@ def deploy_custom_hyperopt(hyperopt_name: str, hyperopt_path: Path, buy_indicato
     """
 
     # Build the arguments for the buy and sell generators
-    buy_args = build_hyperopt_buyelements(buy_indicators)
-    sell_args = build_hyperopt_sellelements(sell_indicators)
+    buy_args = custom_hyperopt_buyelements(buy_indicators)
+    sell_args = custom_hyperopt_sellelements(sell_indicators)
 
     # Build the final template
-    strategy_text = render_template(templatefile='base_hyperopt.py.j2',
+    strategy_text = render_template(templatefile='base_custom_hyperopt.py.j2',
                                     arguments={"hyperopt": hyperopt_name,
                                                "buy_guards": buy_args["buy_guards"],
                                                "buy_triggers": buy_args["buy_triggers"],
@@ -148,19 +279,18 @@ def deploy_custom_hyperopt(hyperopt_name: str, hyperopt_path: Path, buy_indicato
     hyperopt_path.write_text(strategy_text)
 
 
-def start_build_hyperopt(args: Dict[str, Any]) -> None:
+def start_custom_hyperopt(args: Dict[str, Any]) -> None:
     """
     Check if the right subcommands where passed and start building the hyperopt
     """
     config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
 
-    # check what the name of the hyperopt should
     if not 'hyperopt' in args or not args['hyperopt']:
-        raise OperationalException("`build-hyperopt` requires --hyperopt to be set.")
+        raise OperationalException("`custom-hyperopt` requires --hyperopt to be set.")
     elif not 'buy_indicators' in args or not args['buy_indicators']:
-        raise OperationalException("`build-hyperopt` requires --buy-indicators to be set.")
+        raise OperationalException("`custom-hyperopt` requires --buy-indicators to be set.")
     elif not 'sell_indicators' in args or not args['sell_indicators']:
-        raise OperationalException("`build-hyperopt` requires --sell-indicators to be set.")
+        raise OperationalException("`custom-hyperopt` requires --sell-indicators to be set.")
     else:
         if args['hyperopt'] == 'DefaultHyperopt':
             raise OperationalException("DefaultHyperopt is not allowed as name.")
@@ -175,3 +305,40 @@ def start_build_hyperopt(args: Dict[str, Any]) -> None:
 
         deploy_custom_hyperopt(args['hyperopt'], new_path,
                                buy_indicators, sell_indicators)
+
+
+# --------------------------------------------------build-hyperopt------------------------------------------------------
+
+def start_build_hyperopt(args: Dict[str, Any]) -> None:
+    """
+    Check if the right subcommands where passed and start building the hyperopt
+    """
+    config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
+
+    # strategy and hyperopt need to be defined
+    if not 'strategy' in args or not args['strategy']:
+        raise OperationalException("`build-hyperopt` requires --strategy to be set.")
+    if not 'hyperopt' in args or not args['hyperopt']:
+        args['hyperopt'] = args['strategy'] + "opt"
+    else:
+        if args['hyperopt'] == 'DefaultHyperopt':
+            raise OperationalException("DefaultHyperopt is not allowed as name.")
+
+        # the path of the chosen strategy
+        strategy_path = config['user_data_dir'] / USERPATH_STRATEGIES / (args['strategy'] + '.py')
+
+        # the path where the hyperopt should be written
+        new_path = config['user_data_dir'] / USERPATH_HYPEROPTS / (args['hyperopt'] + '.py')
+        if new_path.exists():
+            raise OperationalException(f"`{new_path}` already exists. "
+                                       "Please choose another Hyperopt Name.")
+
+        # extract the buy and sell indicators as dicts
+        extracted_lists = extract_lists(strategy_path)
+
+        buy_indicators = extracted_lists[0]
+        sell_indicators = extracted_lists[1]
+
+        # use the dicts to write the hyperopt
+        deploy_custom_hyperopt(args['hyperopt'], new_path,
+                               buy_indicators, sell_indicators)

freqtrade/commands/cli_options.py

@@ -279,14 +279,21 @@ AVAILABLE_CLI_OPTIONS = {
     "buy_indicators": Arg(
         '-b', '--buy-indicators',
         help='Specify the buy indicators the hyperopt should build. '
-        'Example: --buy-indicators `{"rsi":"above","bb_lowerband":"below"}`',
-        metavar='DICT',
+        'Example: --buy-indicators `[["rsi","<","trigger",30.0],["bb_lowerband",">","guard","close"]]`'
+        'Check the documentation for specific requirements for the lists.',
+        metavar='LIST',
     ),
     "sell_indicators": Arg(
         '-s', '--sell-indicators',
         help='Specify the sell indicators the hyperopt should build. '
-        'Example: --sell-indicators `{"rsi":"above","bb_lowerband":"below"}`',
-        metavar='DICT',
+        'Example: --sell-indicators [["rsi",">","trigger",70.0],["bb_lowerband","<","guard","close"]]'
+        'Check the documentation for specific requirements for the lists.',
+        metavar='LIST',
+    ),
+    "extract_name": Arg(
+        '--extract-name',
+        help='Specify the name of the file to which the data should be extracted. ',
+        metavar='FILENAME',
     ),
     # List exchanges
     "print_one_column": Arg(

freqtrade/constants.py

@@ -392,4 +392,4 @@ PairWithTimeframe = Tuple[str, str]
 ListPairsWithTimeframes = List[PairWithTimeframe]
 
 # Type for trades list
-TradeList = List[List]
+TradeList = List[List]

freqtrade/templates/base_custom_hyperopt.py.j2

@@ -0,0 +1,164 @@
+# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
+
+# --- Do not remove these libs ---
+from functools import reduce
+from typing import Any, Callable, Dict, List
+
+import numpy as np  # noqa
+import pandas as pd  # noqa
+from pandas import DataFrame
+from skopt.space import Categorical, Dimension, Integer, Real  # noqa
+
+from freqtrade.optimize.hyperopt_interface import IHyperOpt
+
+# --------------------------------
+# Add your lib to import here
+import talib.abstract as ta  # noqa
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+
+
+class {{ hyperopt }}(IHyperOpt):
+    """
+    This is a Hyperopt template to get you started.
+
+    More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
+
+    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 methods roi_space, generate_roi_table and stoploss_space are not required
+    and are provided by default.
+    However, you may override them if you need 'roi' and 'stoploss' spaces that
+    differ from the defaults offered by Freqtrade.
+    Sample implementation of these methods will be copied to `user_data/hyperopts` when
+    creating the user-data directory using `freqtrade create-userdir --userdir user_data`,
+    or is available online under the following URL:
+    https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/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
+            {{ buy_guards | indent(12) }}
+
+            # TRIGGERS
+            if 'trigger' in params:
+                {{ buy_triggers | indent(16) }}
+
+            # Check that the candle had volume
+            conditions.append(dataframe['volume'] > 0)
+
+            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 [
+            {{ buy_space | indent(12) }}
+        ]
+
+    @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
+            {{ sell_guards | indent(12) }}
+
+            # TRIGGERS
+            if 'sell-trigger' in params:
+                {{ sell_triggers | indent(16) }}
+
+            # Check that the candle had volume
+            conditions.append(dataframe['volume'] > 0)
+
+            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 [
+            {{ sell_space | indent(12) }}
+        ]
+    @ staticmethod
+    def generate_roi_table(params: Dict) -> Dict[int, float]:
+        """
+        Generate the ROI table that will be used by Hyperopt
+        This implementation generates the default legacy Freqtrade ROI tables.
+        Change it if you need different number of steps in the generated
+        ROI tables or other structure of the ROI tables.
+        Please keep it aligned with parameters in the 'roi' optimization
+        hyperspace defined by the roi_space method.
+        """
+        roi_table = {}
+        roi_table[0] = params['roi_p1'] + params['roi_p2'] + params['roi_p3']
+        roi_table[params['roi_t3']] = params['roi_p1'] + params['roi_p2']
+        roi_table[params['roi_t3'] + params['roi_t2']] = params['roi_p1']
+        roi_table[params['roi_t3'] + params['roi_t2'] + params['roi_t1']] = 0
+
+        return roi_table
+
+    @ staticmethod
+    def roi_space() -> List[Dimension]:
+        """
+        Values to search for each ROI steps
+        Override it if you need some different ranges for the parameters in the
+        'roi' optimization hyperspace.
+        Please keep it aligned with the implementation of the
+        generate_roi_table method.
+        """
+        return [
+            Integer(10, 120, name='roi_t1'),
+            Integer(10, 60, name='roi_t2'),
+            Integer(10, 40, name='roi_t3'),
+            Real(0.01, 0.04, name='roi_p1'),
+            Real(0.01, 0.07, name='roi_p2'),
+            Real(0.01, 0.20, name='roi_p3'),
+        ]
+
+    @ staticmethod
+    def stoploss_space() -> List[Dimension]:
+        """
+        Stoploss Value to search
+        Override it if you need some different range for the parameter in the
+        'stoploss' optimization hyperspace.
+        """
+        return [
+            Real(-0.35, -0.02, name='stoploss'),
+        ]

freqtrade/templates/base_hyperopt.py.j2

@@ -55,7 +55,16 @@ class {{ hyperopt }}(IHyperOpt):
 
             # TRIGGERS
             if 'trigger' in params:
-                {{ buy_triggers | indent(16) }}
+                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']
+                    ))
 
             # Check that the candle had volume
             conditions.append(dataframe['volume'] > 0)
@@ -94,7 +103,16 @@ class {{ hyperopt }}(IHyperOpt):
 
             # TRIGGERS
             if 'sell-trigger' in params:
-                {{ sell_triggers | indent(16) }}
+                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']
+                    ))
 
             # Check that the candle had volume
             conditions.append(dataframe['volume'] > 0)
@@ -115,4 +133,4 @@ class {{ hyperopt }}(IHyperOpt):
         """
         return [
             {{ sell_space | indent(12) }}
-        ]
+        ]