diff --git a/docs/advanced-backtesting.md b/docs/advanced-backtesting.md index 2a484da69..5c2500f18 100644 --- a/docs/advanced-backtesting.md +++ b/docs/advanced-backtesting.md @@ -22,50 +22,79 @@ DataFrame of the candles that resulted in buy signals. Depending on how many buy makes, this file may get quite large, so periodically check your `user_data/backtest_results` folder to delete old exports. -To analyze the buy tags, we need to use the `buy_reasons.py` script from -[froggleston's repo](https://github.com/froggleston/freqtrade-buyreasons). Follow the instructions -in their README to copy the script into your `freqtrade/scripts/` folder. - Before running your next backtest, make sure you either delete your old backtest results or run backtesting with the `--cache none` option to make sure no cached results are used. If all goes well, you should now see a `backtest-result-{timestamp}_signals.pkl` file in the `user_data/backtest_results` folder. -Now run the `buy_reasons.py` script, supplying a few options: +To analyze the entry/exit tags, we now need to use the `freqtrade backtesting-analysis` command +with `--analysis-groups` option provided with space-separated arguments (default `0 1 2`): ``` bash -python3 scripts/buy_reasons.py -c -s -t -g0,1,2,3,4 +freqtrade backtesting-analysis -c --analysis-groups 0 1 2 3 4 ``` -The `-g` option is used to specify the various tabular outputs, ranging from the simplest (0) -to the most detailed per pair, per buy and per sell tag (4). More options are available by -running with the `-h` option. +This command will read from the last backtesting results. The `--analysis-groups` option is +used to specify the various tabular outputs showing the profit fo each group or trade, +ranging from the simplest (0) to the most detailed per pair, per buy and per sell tag (4): + +* 1: profit summaries grouped by enter_tag +* 2: profit summaries grouped by enter_tag and exit_tag +* 3: profit summaries grouped by pair and enter_tag +* 4: profit summaries grouped by pair, enter_ and exit_tag (this can get quite large) + +More options are available by running with the `-h` option. + +### Using export-filename + +Normally, `backtesting-analysis` uses the latest backtest results, but if you wanted to go +back to a previous backtest output, you need to supply the `--export-filename` option. +You can supply the same parameter to `backtest-analysis` with the name of the final backtest +output file. This allows you to keep historical versions of backtest results and re-analyse +them at a later date: + +``` bash +freqtrade backtesting -c --timeframe --strategy --timerange= --export=signals --export-filename=/tmp/mystrat_backtest.json +``` + +You should see some output similar to below in the logs with the name of the timestamped +filename that was exported: + +``` +2022-06-14 16:28:32,698 - freqtrade.misc - INFO - dumping json to "/tmp/mystrat_backtest-2022-06-14_16-28-32.json" +``` + +You can then use that filename in `backtesting-analysis`: + +``` +freqtrade backtesting-analysis -c --export-filename=/tmp/mystrat_backtest-2022-06-14_16-28-32.json +``` ### Tuning the buy tags and sell tags to display To show only certain buy and sell tags in the displayed output, use the following two options: ``` ---enter_reason_list : Comma separated list of enter signals to analyse. Default: "all" ---exit_reason_list : Comma separated list of exit signals to analyse. Default: "stop_loss,trailing_stop_loss" +--enter-reason-list : Space-separated list of enter signals to analyse. Default: "all" +--exit-reason-list : Space-separated list of exit signals to analyse. Default: "all" ``` For example: ```bash -python3 scripts/buy_reasons.py -c -s -t -g0,1,2,3,4 --enter_reason_list "enter_tag_a,enter_tag_b" --exit_reason_list "roi,custom_exit_tag_a,stop_loss" +freqtrade backtesting-analysis -c --analysis-groups 0 2 --enter-reason-list enter_tag_a enter_tag_b --exit-reason-list roi custom_exit_tag_a stop_loss ``` ### Outputting signal candle indicators -The real power of the buy_reasons.py script comes from the ability to print out the indicator +The real power of `freqtrade backtesting-analysis` comes from the ability to print out the indicator values present on signal candles to allow fine-grained investigation and tuning of buy signal indicators. To print out a column for a given set of indicators, use the `--indicator-list` option: ```bash -python3 scripts/buy_reasons.py -c -s -t -g0,1,2,3,4 --enter_reason_list "enter_tag_a,enter_tag_b" --exit_reason_list "roi,custom_exit_tag_a,stop_loss" --indicator_list "rsi,rsi_1h,bb_lowerband,ema_9,macd,macdsignal" +freqtrade backtesting-analysis -c --analysis-groups 0 2 --enter-reason-list enter_tag_a enter_tag_b --exit-reason-list roi custom_exit_tag_a stop_loss --indicator-list rsi rsi_1h bb_lowerband ema_9 macd macdsignal ``` The indicators have to be present in your strategy's main DataFrame (either for your main diff --git a/docs/utils.md b/docs/utils.md index 9b799e5fc..0dd88b242 100644 --- a/docs/utils.md +++ b/docs/utils.md @@ -651,6 +651,61 @@ Common arguments: ``` +## Detailed backtest analysis + +Advanced backtest result analysis. + +More details in the [Backtesting analysis](advanced-backtesting.md#analyze-the-buyentry-and-sellexit-tags) Section. + +``` +usage: freqtrade backtesting-analysis [-h] [-v] [--logfile FILE] [-V] + [-c PATH] [-d PATH] [--userdir PATH] + [--export-filename PATH] + [--analysis-groups {0,1,2,3,4} [{0,1,2,3,4} ...]] + [--enter-reason-list ENTER_REASON_LIST [ENTER_REASON_LIST ...]] + [--exit-reason-list EXIT_REASON_LIST [EXIT_REASON_LIST ...]] + [--indicator-list INDICATOR_LIST [INDICATOR_LIST ...]] + +optional arguments: + -h, --help show this help message and exit + --export-filename PATH, --backtest-filename PATH + Use this filename for backtest results.Requires + `--export` to be set as well. Example: `--export-filen + ame=user_data/backtest_results/backtest_today.json` + --analysis-groups {0,1,2,3,4} [{0,1,2,3,4} ...] + grouping output - 0: simple wins/losses by enter tag, + 1: by enter_tag, 2: by enter_tag and exit_tag, 3: by + pair and enter_tag, 4: by pair, enter_ and exit_tag + (this can get quite large) + --enter-reason-list ENTER_REASON_LIST [ENTER_REASON_LIST ...] + Comma separated list of entry signals to analyse. + Default: all. e.g. 'entry_tag_a,entry_tag_b' + --exit-reason-list EXIT_REASON_LIST [EXIT_REASON_LIST ...] + Comma separated list of exit signals to analyse. + Default: all. e.g. + 'exit_tag_a,roi,stop_loss,trailing_stop_loss' + --indicator-list INDICATOR_LIST [INDICATOR_LIST ...] + Comma separated list of indicators to analyse. e.g. + 'close,rsi,bb_lowerband,profit_abs' + +Common arguments: + -v, --verbose Verbose mode (-vv for more, -vvv to get all messages). + --logfile FILE Log to the file specified. Special values are: + 'syslog', 'journald'. See the documentation for more + details. + -V, --version show program's version number and exit + -c PATH, --config PATH + Specify configuration file (default: + `userdir/config.json` or `config.json` whichever + exists). Multiple --config options may be used. Can be + set to `-` to read config from stdin. + -d PATH, --datadir PATH + Path to directory with historical backtesting data. + --userdir PATH, --user-data-dir PATH + Path to userdata directory. + +``` + ## List Hyperopt results You can list the hyperoptimization epochs the Hyperopt module evaluated previously with the `hyperopt-list` sub-command. diff --git a/freqtrade/commands/__init__.py b/freqtrade/commands/__init__.py index 0e637c487..d93ed1e09 100644 --- a/freqtrade/commands/__init__.py +++ b/freqtrade/commands/__init__.py @@ -6,6 +6,7 @@ Contains all start-commands, subcommands and CLI Interface creation. Note: Be careful with file-scoped imports in these subfiles. as they are parsed on startup, nothing containing optional modules should be loaded. """ +from freqtrade.commands.analyze_commands import start_analysis_entries_exits from freqtrade.commands.arguments import Arguments from freqtrade.commands.build_config_commands import start_new_config from freqtrade.commands.data_commands import (start_convert_data, start_convert_trades, diff --git a/freqtrade/commands/analyze_commands.py b/freqtrade/commands/analyze_commands.py new file mode 100755 index 000000000..b6b790788 --- /dev/null +++ b/freqtrade/commands/analyze_commands.py @@ -0,0 +1,69 @@ +import logging +from pathlib import Path +from typing import Any, Dict + +from freqtrade.configuration import setup_utils_configuration +from freqtrade.enums import RunMode +from freqtrade.exceptions import OperationalException + + +logger = logging.getLogger(__name__) + + +def setup_analyze_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str, Any]: + """ + Prepare the configuration for the entry/exit reason analysis module + :param args: Cli args from Arguments() + :param method: Bot running mode + :return: Configuration + """ + config = setup_utils_configuration(args, method) + + no_unlimited_runmodes = { + RunMode.BACKTEST: 'backtesting', + } + if method in no_unlimited_runmodes.keys(): + from freqtrade.data.btanalysis import get_latest_backtest_filename + + if 'exportfilename' in config: + if config['exportfilename'].is_dir(): + btfile = Path(get_latest_backtest_filename(config['exportfilename'])) + signals_file = f"{config['exportfilename']}/{btfile.stem}_signals.pkl" + else: + if config['exportfilename'].exists(): + btfile = Path(config['exportfilename']) + signals_file = f"{btfile.parent}/{btfile.stem}_signals.pkl" + else: + raise OperationalException(f"{config['exportfilename']} does not exist.") + else: + raise OperationalException('exportfilename not in config.') + + if (not Path(signals_file).exists()): + raise OperationalException( + (f"Cannot find latest backtest signals file: {signals_file}." + "Run backtesting with `--export signals`.") + ) + + return config + + +def start_analysis_entries_exits(args: Dict[str, Any]) -> None: + """ + Start analysis script + :param args: Cli args from Arguments() + :return: None + """ + from freqtrade.data.entryexitanalysis import process_entry_exit_reasons + + # Initialize configuration + config = setup_analyze_configuration(args, RunMode.BACKTEST) + + logger.info('Starting freqtrade in analysis mode') + + process_entry_exit_reasons(config['exportfilename'], + config['exchange']['pair_whitelist'], + config['analysis_groups'], + config['enter_reason_list'], + config['exit_reason_list'], + config['indicator_list'] + ) diff --git a/freqtrade/commands/arguments.py b/freqtrade/commands/arguments.py index 815e28175..1e3e2845a 100644 --- a/freqtrade/commands/arguments.py +++ b/freqtrade/commands/arguments.py @@ -101,6 +101,9 @@ ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperop "print_json", "hyperoptexportfilename", "hyperopt_show_no_header", "disableparamexport", "backtest_breakdown"] +ARGS_ANALYZE_ENTRIES_EXITS = ["exportfilename", "analysis_groups", "enter_reason_list", + "exit_reason_list", "indicator_list"] + NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes", "list-markets", "list-pairs", "list-strategies", "list-data", "hyperopt-list", "hyperopt-show", "backtest-filter", @@ -182,8 +185,9 @@ class Arguments: self.parser = argparse.ArgumentParser(description='Free, open source crypto trading bot') self._build_args(optionlist=['version'], parser=self.parser) - from freqtrade.commands import (start_backtesting, start_backtesting_show, - start_convert_data, start_convert_db, start_convert_trades, + from freqtrade.commands import (start_analysis_entries_exits, start_backtesting, + start_backtesting_show, start_convert_data, + start_convert_db, start_convert_trades, start_create_userdir, start_download_data, start_edge, start_hyperopt, start_hyperopt_list, start_hyperopt_show, start_install_ui, start_list_data, start_list_exchanges, @@ -283,6 +287,13 @@ class Arguments: backtesting_show_cmd.set_defaults(func=start_backtesting_show) self._build_args(optionlist=ARGS_BACKTEST_SHOW, parser=backtesting_show_cmd) + # Add backtesting analysis subcommand + analysis_cmd = subparsers.add_parser('backtesting-analysis', + help='Backtest Analysis module.', + parents=[_common_parser]) + analysis_cmd.set_defaults(func=start_analysis_entries_exits) + self._build_args(optionlist=ARGS_ANALYZE_ENTRIES_EXITS, parser=analysis_cmd) + # Add edge subcommand edge_cmd = subparsers.add_parser('edge', help='Edge module.', parents=[_common_parser, _strategy_parser]) diff --git a/freqtrade/commands/cli_options.py b/freqtrade/commands/cli_options.py index aac9f5713..3370ce64b 100644 --- a/freqtrade/commands/cli_options.py +++ b/freqtrade/commands/cli_options.py @@ -614,4 +614,37 @@ AVAILABLE_CLI_OPTIONS = { "that do not contain any parameters."), action="store_true", ), + "analysis_groups": Arg( + "--analysis-groups", + help=("grouping output - " + "0: simple wins/losses by enter tag, " + "1: by enter_tag, " + "2: by enter_tag and exit_tag, " + "3: by pair and enter_tag, " + "4: by pair, enter_ and exit_tag (this can get quite large)"), + nargs='+', + default=['0', '1', '2'], + choices=['0', '1', '2', '3', '4'], + ), + "enter_reason_list": Arg( + "--enter-reason-list", + help=("Comma separated list of entry signals to analyse. Default: all. " + "e.g. 'entry_tag_a,entry_tag_b'"), + nargs='+', + default=['all'], + ), + "exit_reason_list": Arg( + "--exit-reason-list", + help=("Comma separated list of exit signals to analyse. Default: all. " + "e.g. 'exit_tag_a,roi,stop_loss,trailing_stop_loss'"), + nargs='+', + default=['all'], + ), + "indicator_list": Arg( + "--indicator-list", + help=("Comma separated list of indicators to analyse. " + "e.g. 'close,rsi,bb_lowerband,profit_abs'"), + nargs='+', + default=[], + ), } diff --git a/freqtrade/configuration/configuration.py b/freqtrade/configuration/configuration.py index 3f563b6cd..2f9932070 100644 --- a/freqtrade/configuration/configuration.py +++ b/freqtrade/configuration/configuration.py @@ -95,6 +95,8 @@ class Configuration: self._process_data_options(config) + self._process_analyze_options(config) + # Check if the exchange set by the user is supported check_exchange(config, config.get('experimental', {}).get('block_bad_exchanges', True)) @@ -433,6 +435,19 @@ class Configuration: self._args_to_config(config, argname='candle_types', logstring='Detected --candle-types: {}') + def _process_analyze_options(self, config: Dict[str, Any]) -> None: + self._args_to_config(config, argname='analysis_groups', + logstring='Analysis reason groups: {}') + + self._args_to_config(config, argname='enter_reason_list', + logstring='Analysis enter tag list: {}') + + self._args_to_config(config, argname='exit_reason_list', + logstring='Analysis exit tag list: {}') + + self._args_to_config(config, argname='indicator_list', + logstring='Analysis indicator list: {}') + def _process_runmode(self, config: Dict[str, Any]) -> None: self._args_to_config(config, argname='dry_run', diff --git a/freqtrade/data/entryexitanalysis.py b/freqtrade/data/entryexitanalysis.py new file mode 100755 index 000000000..b22c3f87e --- /dev/null +++ b/freqtrade/data/entryexitanalysis.py @@ -0,0 +1,227 @@ +import logging +from pathlib import Path +from typing import List, Optional + +import joblib +import pandas as pd +from tabulate import tabulate + +from freqtrade.data.btanalysis import (get_latest_backtest_filename, load_backtest_data, + load_backtest_stats) +from freqtrade.exceptions import OperationalException + + +logger = logging.getLogger(__name__) + + +def _load_signal_candles(backtest_dir: Path): + if backtest_dir.is_dir(): + scpf = Path(backtest_dir, + Path(get_latest_backtest_filename(backtest_dir)).stem + "_signals.pkl" + ) + else: + scpf = Path(backtest_dir.parent / f"{backtest_dir.stem}_signals.pkl") + + try: + scp = open(scpf, "rb") + signal_candles = joblib.load(scp) + logger.info(f"Loaded signal candles: {str(scpf)}") + except Exception as e: + logger.error("Cannot load signal candles from pickled results: ", e) + + return signal_candles + + +def _process_candles_and_indicators(pairlist, strategy_name, trades, signal_candles): + analysed_trades_dict = {} + analysed_trades_dict[strategy_name] = {} + + try: + logger.info(f"Processing {strategy_name} : {len(pairlist)} pairs") + + for pair in pairlist: + if pair in signal_candles[strategy_name]: + analysed_trades_dict[strategy_name][pair] = _analyze_candles_and_indicators( + pair, + trades, + signal_candles[strategy_name][pair]) + except Exception as e: + print(f"Cannot process entry/exit reasons for {strategy_name}: ", e) + + return analysed_trades_dict + + +def _analyze_candles_and_indicators(pair, trades, signal_candles): + buyf = signal_candles + + if len(buyf) > 0: + buyf = buyf.set_index('date', drop=False) + trades_red = trades.loc[trades['pair'] == pair].copy() + + trades_inds = pd.DataFrame() + + if trades_red.shape[0] > 0 and buyf.shape[0] > 0: + for t, v in trades_red.open_date.items(): + allinds = buyf.loc[(buyf['date'] < v)] + if allinds.shape[0] > 0: + tmp_inds = allinds.iloc[[-1]] + + trades_red.loc[t, 'signal_date'] = tmp_inds['date'].values[0] + trades_red.loc[t, 'enter_reason'] = trades_red.loc[t, 'enter_tag'] + tmp_inds.index.rename('signal_date', inplace=True) + trades_inds = pd.concat([trades_inds, tmp_inds]) + + if 'signal_date' in trades_red: + trades_red['signal_date'] = pd.to_datetime(trades_red['signal_date'], utc=True) + trades_red.set_index('signal_date', inplace=True) + + try: + trades_red = pd.merge(trades_red, trades_inds, on='signal_date', how='outer') + except Exception as e: + raise e + return trades_red + else: + return pd.DataFrame() + + +def _do_group_table_output(bigdf, glist): + for g in glist: + # 0: summary wins/losses grouped by enter tag + if g == "0": + group_mask = ['enter_reason'] + wins = bigdf.loc[bigdf['profit_abs'] >= 0] \ + .groupby(group_mask) \ + .agg({'profit_abs': ['sum']}) + + wins.columns = ['profit_abs_wins'] + loss = bigdf.loc[bigdf['profit_abs'] < 0] \ + .groupby(group_mask) \ + .agg({'profit_abs': ['sum']}) + loss.columns = ['profit_abs_loss'] + + new = bigdf.groupby(group_mask).agg({'profit_abs': [ + 'count', + lambda x: sum(x > 0), + lambda x: sum(x <= 0)]}) + new = pd.concat([new, wins, loss], axis=1).fillna(0) + + new['profit_tot'] = new['profit_abs_wins'] - abs(new['profit_abs_loss']) + new['wl_ratio_pct'] = (new.iloc[:, 1] / new.iloc[:, 0] * 100).fillna(0) + new['avg_win'] = (new['profit_abs_wins'] / new.iloc[:, 1]).fillna(0) + new['avg_loss'] = (new['profit_abs_loss'] / new.iloc[:, 2]).fillna(0) + + new.columns = ['total_num_buys', 'wins', 'losses', 'profit_abs_wins', 'profit_abs_loss', + 'profit_tot', 'wl_ratio_pct', 'avg_win', 'avg_loss'] + + sortcols = ['total_num_buys'] + + _print_table(new, sortcols, show_index=True) + + else: + agg_mask = {'profit_abs': ['count', 'sum', 'median', 'mean'], + 'profit_ratio': ['sum', 'median', 'mean']} + agg_cols = ['num_buys', 'profit_abs_sum', 'profit_abs_median', + 'profit_abs_mean', 'median_profit_pct', 'mean_profit_pct', + 'total_profit_pct'] + sortcols = ['profit_abs_sum', 'enter_reason'] + + # 1: profit summaries grouped by enter_tag + if g == "1": + group_mask = ['enter_reason'] + + # 2: profit summaries grouped by enter_tag and exit_tag + if g == "2": + group_mask = ['enter_reason', 'exit_reason'] + + # 3: profit summaries grouped by pair and enter_tag + if g == "3": + group_mask = ['pair', 'enter_reason'] + + # 4: profit summaries grouped by pair, enter_ and exit_tag (this can get quite large) + if g == "4": + group_mask = ['pair', 'enter_reason', 'exit_reason'] + if group_mask: + new = bigdf.groupby(group_mask).agg(agg_mask).reset_index() + new.columns = group_mask + agg_cols + new['median_profit_pct'] = new['median_profit_pct'] * 100 + new['mean_profit_pct'] = new['mean_profit_pct'] * 100 + new['total_profit_pct'] = new['total_profit_pct'] * 100 + + _print_table(new, sortcols) + else: + logger.warning("Invalid group mask specified.") + + +def _print_results(analysed_trades, stratname, analysis_groups, + enter_reason_list, exit_reason_list, + indicator_list, columns=None): + if columns is None: + columns = ['pair', 'open_date', 'close_date', 'profit_abs', 'enter_reason', 'exit_reason'] + + bigdf = pd.DataFrame() + for pair, trades in analysed_trades[stratname].items(): + bigdf = pd.concat([bigdf, trades], ignore_index=True) + + if bigdf.shape[0] > 0 and ('enter_reason' in bigdf.columns): + if analysis_groups: + _do_group_table_output(bigdf, analysis_groups) + + if enter_reason_list and "all" not in enter_reason_list: + bigdf = bigdf.loc[(bigdf['enter_reason'].isin(enter_reason_list))] + + if exit_reason_list and "all" not in exit_reason_list: + bigdf = bigdf.loc[(bigdf['exit_reason'].isin(exit_reason_list))] + + if "all" in indicator_list: + print(bigdf) + elif indicator_list is not None: + available_inds = [] + for ind in indicator_list: + if ind in bigdf: + available_inds.append(ind) + ilist = ["pair", "enter_reason", "exit_reason"] + available_inds + _print_table(bigdf[ilist], sortcols=['exit_reason'], show_index=False) + else: + print("\\_ No trades to show") + + +def _print_table(df, sortcols=None, show_index=False): + if (sortcols is not None): + data = df.sort_values(sortcols) + else: + data = df + + print( + tabulate( + data, + headers='keys', + tablefmt='psql', + showindex=show_index + ) + ) + + +def process_entry_exit_reasons(backtest_dir: Path, + pairlist: List[str], + analysis_groups: Optional[List[str]] = ["0", "1", "2"], + enter_reason_list: Optional[List[str]] = ["all"], + exit_reason_list: Optional[List[str]] = ["all"], + indicator_list: Optional[List[str]] = []): + try: + backtest_stats = load_backtest_stats(backtest_dir) + for strategy_name, results in backtest_stats['strategy'].items(): + trades = load_backtest_data(backtest_dir, strategy_name) + + if not trades.empty: + signal_candles = _load_signal_candles(backtest_dir) + analysed_trades_dict = _process_candles_and_indicators(pairlist, strategy_name, + trades, signal_candles) + _print_results(analysed_trades_dict, + strategy_name, + analysis_groups, + enter_reason_list, + exit_reason_list, + indicator_list) + + except ValueError as e: + raise OperationalException(e) from e diff --git a/tests/data/test_entryexitanalysis.py b/tests/data/test_entryexitanalysis.py new file mode 100755 index 000000000..09fbe9957 --- /dev/null +++ b/tests/data/test_entryexitanalysis.py @@ -0,0 +1,191 @@ +import logging +from unittest.mock import MagicMock, PropertyMock + +import pandas as pd +import pytest + +from freqtrade.commands.analyze_commands import start_analysis_entries_exits +from freqtrade.commands.optimize_commands import start_backtesting +from freqtrade.enums import ExitType +from freqtrade.optimize.backtesting import Backtesting +from tests.conftest import get_args, patch_exchange, patched_configuration_load_config_file + + +@pytest.fixture(autouse=True) +def entryexitanalysis_cleanup() -> None: + yield None + + Backtesting.cleanup() + + +def test_backtest_analysis_nomock(default_conf, mocker, caplog, testdatadir, tmpdir, capsys): + caplog.set_level(logging.INFO) + + default_conf.update({ + "use_exit_signal": True, + "exit_profit_only": False, + "exit_profit_offset": 0.0, + "ignore_roi_if_entry_signal": False, + }) + patch_exchange(mocker) + result1 = pd.DataFrame({'pair': ['ETH/BTC', 'LTC/BTC', 'ETH/BTC', 'LTC/BTC'], + 'profit_ratio': [0.025, 0.05, -0.1, -0.05], + 'profit_abs': [0.5, 2.0, -4.0, -2.0], + 'open_date': pd.to_datetime(['2018-01-29 18:40:00', + '2018-01-30 03:30:00', + '2018-01-30 08:10:00', + '2018-01-31 13:30:00', ], utc=True + ), + 'close_date': pd.to_datetime(['2018-01-29 20:45:00', + '2018-01-30 05:35:00', + '2018-01-30 09:10:00', + '2018-01-31 15:00:00', ], utc=True), + 'trade_duration': [235, 40, 60, 90], + 'is_open': [False, False, False, False], + 'stake_amount': [0.01, 0.01, 0.01, 0.01], + 'open_rate': [0.104445, 0.10302485, 0.10302485, 0.10302485], + 'close_rate': [0.104969, 0.103541, 0.102041, 0.102541], + "is_short": [False, False, False, False], + 'enter_tag': ["enter_tag_long_a", + "enter_tag_long_b", + "enter_tag_long_a", + "enter_tag_long_b"], + 'exit_reason': [ExitType.ROI, + ExitType.EXIT_SIGNAL, + ExitType.STOP_LOSS, + ExitType.TRAILING_STOP_LOSS] + }) + + backtestmock = MagicMock(side_effect=[ + { + 'results': result1, + 'config': default_conf, + 'locks': [], + 'rejected_signals': 20, + 'timedout_entry_orders': 0, + 'timedout_exit_orders': 0, + 'canceled_trade_entries': 0, + 'canceled_entry_orders': 0, + 'replaced_entry_orders': 0, + 'final_balance': 1000, + } + ]) + mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist', + PropertyMock(return_value=['ETH/BTC', 'LTC/BTC', 'DASH/BTC'])) + mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock) + + patched_configuration_load_config_file(mocker, default_conf) + + args = [ + 'backtesting', + '--config', 'config.json', + '--datadir', str(testdatadir), + '--user-data-dir', str(tmpdir), + '--timeframe', '5m', + '--timerange', '1515560100-1517287800', + '--export', 'signals', + '--cache', 'none', + ] + args = get_args(args) + start_backtesting(args) + + captured = capsys.readouterr() + assert 'BACKTESTING REPORT' in captured.out + assert 'EXIT REASON STATS' in captured.out + assert 'LEFT OPEN TRADES REPORT' in captured.out + + base_args = [ + 'backtesting-analysis', + '--config', 'config.json', + '--datadir', str(testdatadir), + '--user-data-dir', str(tmpdir), + ] + + # test group 0 and indicator list + args = get_args(base_args + + ['--analysis-groups', "0", + '--indicator-list', "close", "rsi", "profit_abs"] + ) + start_analysis_entries_exits(args) + captured = capsys.readouterr() + assert 'LTC/BTC' in captured.out + assert 'ETH/BTC' in captured.out + assert 'enter_tag_long_a' in captured.out + assert 'enter_tag_long_b' in captured.out + assert 'exit_signal' in captured.out + assert 'roi' in captured.out + assert 'stop_loss' in captured.out + assert 'trailing_stop_loss' in captured.out + assert '0.5' in captured.out + assert '-4' in captured.out + assert '-2' in captured.out + assert '-3.5' in captured.out + assert '50' in captured.out + assert '0' in captured.out + assert '0.01616' in captured.out + assert '34.049' in captured.out + assert '0.104104' in captured.out + assert '47.0996' in captured.out + + # test group 1 + args = get_args(base_args + ['--analysis-groups', "1"]) + start_analysis_entries_exits(args) + captured = capsys.readouterr() + assert 'enter_tag_long_a' in captured.out + assert 'enter_tag_long_b' in captured.out + assert 'total_profit_pct' in captured.out + assert '-3.5' in captured.out + assert '-1.75' in captured.out + assert '-7.5' in captured.out + assert '-3.75' in captured.out + assert '0' in captured.out + + # test group 2 + args = get_args(base_args + ['--analysis-groups', "2"]) + start_analysis_entries_exits(args) + captured = capsys.readouterr() + assert 'enter_tag_long_a' in captured.out + assert 'enter_tag_long_b' in captured.out + assert 'exit_signal' in captured.out + assert 'roi' in captured.out + assert 'stop_loss' in captured.out + assert 'trailing_stop_loss' in captured.out + assert 'total_profit_pct' in captured.out + assert '-10' in captured.out + assert '-5' in captured.out + assert '2.5' in captured.out + + # test group 3 + args = get_args(base_args + ['--analysis-groups', "3"]) + start_analysis_entries_exits(args) + captured = capsys.readouterr() + assert 'LTC/BTC' in captured.out + assert 'ETH/BTC' in captured.out + assert 'enter_tag_long_a' in captured.out + assert 'enter_tag_long_b' in captured.out + assert 'total_profit_pct' in captured.out + assert '-7.5' in captured.out + assert '-3.75' in captured.out + assert '-1.75' in captured.out + assert '0' in captured.out + assert '2' in captured.out + + # test group 4 + args = get_args(base_args + ['--analysis-groups', "4"]) + start_analysis_entries_exits(args) + captured = capsys.readouterr() + assert 'LTC/BTC' in captured.out + assert 'ETH/BTC' in captured.out + assert 'enter_tag_long_a' in captured.out + assert 'enter_tag_long_b' in captured.out + assert 'exit_signal' in captured.out + assert 'roi' in captured.out + assert 'stop_loss' in captured.out + assert 'trailing_stop_loss' in captured.out + assert 'total_profit_pct' in captured.out + assert '-10' in captured.out + assert '-5' in captured.out + assert '-4' in captured.out + assert '0.5' in captured.out + assert '1' in captured.out + assert '2.5' in captured.out diff --git a/tests/rpc/test_rpc_apiserver.py b/tests/rpc/test_rpc_apiserver.py index 03ba895a1..8b3ac18ac 100644 --- a/tests/rpc/test_rpc_apiserver.py +++ b/tests/rpc/test_rpc_apiserver.py @@ -1384,12 +1384,14 @@ def test_api_strategies(botclient): rc = client_get(client, f"{BASE_URI}/strategies") assert_response(rc) + assert rc.json() == {'strategies': [ 'HyperoptableStrategy', 'InformativeDecoratorTest', 'StrategyTestV2', 'StrategyTestV3', - 'StrategyTestV3Futures', + 'StrategyTestV3Analysis', + 'StrategyTestV3Futures' ]} diff --git a/tests/strategy/strats/strategy_test_v3_analysis.py b/tests/strategy/strats/strategy_test_v3_analysis.py new file mode 100644 index 000000000..290fef156 --- /dev/null +++ b/tests/strategy/strats/strategy_test_v3_analysis.py @@ -0,0 +1,175 @@ +# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement + +import talib.abstract as ta +from pandas import DataFrame + +import freqtrade.vendor.qtpylib.indicators as qtpylib +from freqtrade.strategy import (BooleanParameter, DecimalParameter, IntParameter, IStrategy, + RealParameter) + + +class StrategyTestV3Analysis(IStrategy): + """ + Strategy used by tests freqtrade bot. + Please do not modify this strategy, it's intended for internal use only. + Please look at the SampleStrategy in the user_data/strategy directory + or strategy repository https://github.com/freqtrade/freqtrade-strategies + for samples and inspiration. + """ + INTERFACE_VERSION = 3 + + # Minimal ROI designed for the strategy + minimal_roi = { + "40": 0.0, + "30": 0.01, + "20": 0.02, + "0": 0.04 + } + + # Optimal stoploss designed for the strategy + stoploss = -0.10 + + # Optimal timeframe for the strategy + timeframe = '5m' + + # Optional order type mapping + order_types = { + 'entry': 'limit', + 'exit': 'limit', + 'stoploss': 'limit', + 'stoploss_on_exchange': False + } + + # Number of candles the strategy requires before producing valid signals + startup_candle_count: int = 20 + + # Optional time in force for orders + order_time_in_force = { + 'entry': 'gtc', + 'exit': 'gtc', + } + + buy_params = { + 'buy_rsi': 35, + # Intentionally not specified, so "default" is tested + # 'buy_plusdi': 0.4 + } + + sell_params = { + 'sell_rsi': 74, + 'sell_minusdi': 0.4 + } + + buy_rsi = IntParameter([0, 50], default=30, space='buy') + buy_plusdi = RealParameter(low=0, high=1, default=0.5, space='buy') + sell_rsi = IntParameter(low=50, high=100, default=70, space='sell') + sell_minusdi = DecimalParameter(low=0, high=1, default=0.5001, decimals=3, space='sell', + load=False) + protection_enabled = BooleanParameter(default=True) + protection_cooldown_lookback = IntParameter([0, 50], default=30) + + # TODO: Can this work with protection tests? (replace HyperoptableStrategy implicitly ... ) + # @property + # def protections(self): + # prot = [] + # if self.protection_enabled.value: + # prot.append({ + # "method": "CooldownPeriod", + # "stop_duration_candles": self.protection_cooldown_lookback.value + # }) + # return prot + + bot_started = False + + def bot_start(self): + self.bot_started = True + + def informative_pairs(self): + + return [] + + def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + + # Momentum Indicator + # ------------------------------------ + + # ADX + dataframe['adx'] = ta.ADX(dataframe) + + # MACD + macd = ta.MACD(dataframe) + dataframe['macd'] = macd['macd'] + dataframe['macdsignal'] = macd['macdsignal'] + dataframe['macdhist'] = macd['macdhist'] + + # Minus Directional Indicator / Movement + dataframe['minus_di'] = ta.MINUS_DI(dataframe) + + # Plus Directional Indicator / Movement + dataframe['plus_di'] = ta.PLUS_DI(dataframe) + + # RSI + dataframe['rsi'] = ta.RSI(dataframe) + + # Stoch fast + stoch_fast = ta.STOCHF(dataframe) + dataframe['fastd'] = stoch_fast['fastd'] + dataframe['fastk'] = stoch_fast['fastk'] + + # Bollinger bands + bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) + dataframe['bb_lowerband'] = bollinger['lower'] + dataframe['bb_middleband'] = bollinger['mid'] + dataframe['bb_upperband'] = bollinger['upper'] + + # EMA - Exponential Moving Average + dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10) + + return dataframe + + def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + + dataframe.loc[ + ( + (dataframe['rsi'] < self.buy_rsi.value) & + (dataframe['fastd'] < 35) & + (dataframe['adx'] > 30) & + (dataframe['plus_di'] > self.buy_plusdi.value) + ) | + ( + (dataframe['adx'] > 65) & + (dataframe['plus_di'] > self.buy_plusdi.value) + ), + ['enter_long', 'enter_tag']] = 1, 'enter_tag_long' + + dataframe.loc[ + ( + qtpylib.crossed_below(dataframe['rsi'], self.sell_rsi.value) + ), + ['enter_short', 'enter_tag']] = 1, 'enter_tag_short' + + return dataframe + + def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: + dataframe.loc[ + ( + ( + (qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) | + (qtpylib.crossed_above(dataframe['fastd'], 70)) + ) & + (dataframe['adx'] > 10) & + (dataframe['minus_di'] > 0) + ) | + ( + (dataframe['adx'] > 70) & + (dataframe['minus_di'] > self.sell_minusdi.value) + ), + ['exit_long', 'exit_tag']] = 1, 'exit_tag_long' + + dataframe.loc[ + ( + qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value) + ), + ['exit_long', 'exit_tag']] = 1, 'exit_tag_short' + + return dataframe diff --git a/tests/strategy/test_strategy_loading.py b/tests/strategy/test_strategy_loading.py index 919a4bd00..666ae2b05 100644 --- a/tests/strategy/test_strategy_loading.py +++ b/tests/strategy/test_strategy_loading.py @@ -34,7 +34,7 @@ def test_search_all_strategies_no_failed(): directory = Path(__file__).parent / "strats" strategies = StrategyResolver.search_all_objects(directory, enum_failed=False) assert isinstance(strategies, list) - assert len(strategies) == 5 + assert len(strategies) == 6 assert isinstance(strategies[0], dict) @@ -42,10 +42,10 @@ def test_search_all_strategies_with_failed(): directory = Path(__file__).parent / "strats" strategies = StrategyResolver.search_all_objects(directory, enum_failed=True) assert isinstance(strategies, list) - assert len(strategies) == 6 + assert len(strategies) == 7 # with enum_failed=True search_all_objects() shall find 2 good strategies # and 1 which fails to load - assert len([x for x in strategies if x['class'] is not None]) == 5 + assert len([x for x in strategies if x['class'] is not None]) == 6 assert len([x for x in strategies if x['class'] is None]) == 1