Extract edge reporting to optimize_reports

freqtrade/optimize/optimize_reports.py

@@ -0,0 +1,135 @@
+from datetime import timedelta
+from typing import Dict
+
+from pandas import DataFrame
+from tabulate import tabulate
+
+
+def generate_text_table(data: Dict[str, Dict], stake_currency: str, max_open_trades: int,
+                        results: DataFrame, skip_nan: bool = False) -> str:
+    """
+    Generates and returns a text table for the given backtest data and the results dataframe
+    :param data: Dict of <pair: dataframe> containing data that was used during backtesting.
+    :param stake_currency: stake-currency - used to correctly name headers
+    :param max_open_trades: Maximum allowed open trades
+    :param results: Dataframe containing the backtest results
+    :param skip_nan: Print "left open" open trades
+    :return: pretty printed table with tabulate as string
+    """
+
+    floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
+    tabular_data = []
+    headers = ['pair', 'buy count', 'avg profit %', 'cum profit %',
+               f'tot profit {stake_currency}', 'tot profit %', 'avg duration',
+               'profit', 'loss']
+    for pair in data:
+        result = results[results.pair == pair]
+        if skip_nan and result.profit_abs.isnull().all():
+            continue
+
+        tabular_data.append([
+            pair,
+            len(result.index),
+            result.profit_percent.mean() * 100.0,
+            result.profit_percent.sum() * 100.0,
+            result.profit_abs.sum(),
+            result.profit_percent.sum() * 100.0 / max_open_trades,
+            str(timedelta(
+                minutes=round(result.trade_duration.mean()))) if not result.empty else '0:00',
+            len(result[result.profit_abs > 0]),
+            len(result[result.profit_abs < 0])
+        ])
+
+    # Append Total
+    tabular_data.append([
+        'TOTAL',
+        len(results.index),
+        results.profit_percent.mean() * 100.0,
+        results.profit_percent.sum() * 100.0,
+        results.profit_abs.sum(),
+        results.profit_percent.sum() * 100.0 / max_open_trades,
+        str(timedelta(
+            minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
+        len(results[results.profit_abs > 0]),
+        len(results[results.profit_abs < 0])
+    ])
+    # Ignore type as floatfmt does allow tuples but mypy does not know that
+    return tabulate(tabular_data, headers=headers,
+                    floatfmt=floatfmt, tablefmt="pipe")  # type: ignore
+
+
+def generate_text_table_sell_reason(data: Dict[str, Dict], results: DataFrame) -> str:
+    """
+    Generate small table outlining Backtest results
+    :param data: Dict of <pair: dataframe> containing data that was used during backtesting.
+    :param results: Dataframe containing the backtest results
+    :return: pretty printed table with tabulate as string
+    """
+    tabular_data = []
+    headers = ['Sell Reason', 'Count', 'Profit', 'Loss', 'Profit %']
+    for reason, count in results['sell_reason'].value_counts().iteritems():
+        result = results.loc[results['sell_reason'] == reason]
+        profit = len(result[result['profit_abs'] >= 0])
+        loss = len(result[results['profit_abs'] < 0])
+        profit_mean = round(result['profit_percent'].mean() * 100.0, 2)
+        tabular_data.append([reason.value, count, profit, loss, profit_mean])
+    return tabulate(tabular_data, headers=headers, tablefmt="pipe")
+
+
+def generate_text_table_strategy(stake_currency: str, max_open_trades: str,
+                                 all_results: Dict) -> str:
+    """
+    Generate summary table per strategy
+    :param stake_currency: stake-currency - used to correctly name headers
+    :param max_open_trades: Maximum allowed open trades used for backtest
+    :param all_results: Dict of <Strategyname: BacktestResult> containing results for all strategies
+    :return: pretty printed table with tabulate as string
+    """
+
+    floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', '.1f', '.1f')
+    tabular_data = []
+    headers = ['Strategy', 'buy count', 'avg profit %', 'cum profit %',
+               f'tot profit {stake_currency}', 'tot profit %', 'avg duration',
+               'profit', 'loss']
+    for strategy, results in all_results.items():
+        tabular_data.append([
+            strategy,
+            len(results.index),
+            results.profit_percent.mean() * 100.0,
+            results.profit_percent.sum() * 100.0,
+            results.profit_abs.sum(),
+            results.profit_percent.sum() * 100.0 / max_open_trades,
+            str(timedelta(
+                minutes=round(results.trade_duration.mean()))) if not results.empty else '0:00',
+            len(results[results.profit_abs > 0]),
+            len(results[results.profit_abs < 0])
+        ])
+    # Ignore type as floatfmt does allow tuples but mypy does not know that
+    return tabulate(tabular_data, headers=headers,
+                    floatfmt=floatfmt, tablefmt="pipe")  # type: ignore
+
+
+def generate_edge_table(results: dict) -> str:
+
+    floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', '.d')
+    tabular_data = []
+    headers = ['pair', 'stoploss', 'win rate', 'risk reward ratio',
+                'required risk reward', 'expectancy', 'total number of trades',
+                'average duration (min)']
+
+    for result in results.items():
+        if result[1].nb_trades > 0:
+            tabular_data.append([
+                result[0],
+                result[1].stoploss,
+                result[1].winrate,
+                result[1].risk_reward_ratio,
+                result[1].required_risk_reward,
+                result[1].expectancy,
+                result[1].nb_trades,
+                round(result[1].avg_trade_duration)
+            ])
+
+    # Ignore type as floatfmt does allow tuples but mypy does not know that
+    return tabulate(tabular_data, headers=headers,
+                    floatfmt=floatfmt, tablefmt="pipe")  # type: ignore