PEP8 code compliance

freqtrade/data/btanalysis.py

@@ -435,7 +435,7 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
 
 
 def _calc_drawdown_series(profit_results: pd.DataFrame, *, date_col: str, value_col: str,
-                          starting_balance : Optional[float] = 0.0) -> pd.DataFrame:
+                          starting_balance: Optional[float] = 0.0) -> pd.DataFrame:
     max_drawdown_df = pd.DataFrame()
     max_drawdown_df['cumulative'] = profit_results[value_col].cumsum()
     max_drawdown_df['high_value'] = max_drawdown_df['cumulative'].cummax()
@@ -446,13 +446,15 @@ def _calc_drawdown_series(profit_results: pd.DataFrame, *, date_col: str, value_
         max_balance = starting_balance + max_drawdown_df['high_value']
         max_drawdown_df['drawdown_relative'] = ((max_balance - cumulative_balance) / max_balance)
     else:
-        # This is not completely accurate, 
-        max_drawdown_df['drawdown_relative'] = ((max_drawdown_df['high_value'] - max_drawdown_df['cumulative']) / max_drawdown_df['high_value'])
+        # This is not completely accurate
+        max_drawdown_df['drawdown_relative'] = (
+            (max_drawdown_df['high_value'] - max_drawdown_df['cumulative'])
+            / max_drawdown_df['high_value'])
     return max_drawdown_df
 
 
 def calculate_underwater(trades: pd.DataFrame, *, date_col: str = 'close_date',
-                         value_col: str = 'profit_ratio', starting_balance : Optional[float] = 0.0
+                         value_col: str = 'profit_ratio', starting_balance: Optional[float] = 0.0
                          ):
     """
     Calculate max drawdown and the corresponding close dates
@@ -466,7 +468,11 @@ def calculate_underwater(trades: pd.DataFrame, *, date_col: str = 'close_date',
     if len(trades) == 0:
         raise ValueError("Trade dataframe empty.")
     profit_results = trades.sort_values(date_col).reset_index(drop=True)
-    max_drawdown_df = _calc_drawdown_series(profit_results, date_col=date_col, value_col=value_col, starting_balance=starting_balance)
+    max_drawdown_df = _calc_drawdown_series(
+        profit_results,
+        date_col=date_col,
+        value_col=value_col,
+        starting_balance=starting_balance)
 
     return max_drawdown_df
 
@@ -489,9 +495,15 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date'
     if len(trades) == 0:
         raise ValueError("Trade dataframe empty.")
     profit_results = trades.sort_values(date_col).reset_index(drop=True)
-    max_drawdown_df = _calc_drawdown_series(profit_results, date_col=date_col, value_col=value_col, starting_balance=starting_balance)
+    max_drawdown_df = _calc_drawdown_series(
+        profit_results,
+        date_col=date_col,
+        value_col=value_col,
+        starting_balance=starting_balance
+    )
 
-    idxmin = max_drawdown_df['drawdown_relative'].idxmax() if relative else max_drawdown_df['drawdown'].idxmin()
+    idxmin = max_drawdown_df['drawdown_relative'].idxmax() if relative \
+        else max_drawdown_df['drawdown'].idxmin()
     if idxmin == 0:
         raise ValueError("No losing trade, therefore no drawdown.")
     high_date = profit_results.loc[max_drawdown_df.iloc[:idxmin]['high_value'].idxmax(), date_col]

freqtrade/optimize/hyperopt_loss_max_drawdown_relative.py

@@ -4,12 +4,11 @@ MaxDrawDownRelativeHyperOptLoss
 This module defines the alternative HyperOptLoss class which can be used for
 Hyperoptimization.
 """
-from datetime import datetime
 from typing import Dict
 
 from pandas import DataFrame
 
-from freqtrade.data.btanalysis import calculate_underwater, calculate_max_drawdown
+from freqtrade.data.btanalysis import calculate_underwater
 from freqtrade.optimize.hyperopt import IHyperOptLoss
 
 
@@ -34,7 +33,11 @@ class MaxDrawDownRelativeHyperOptLoss(IHyperOptLoss):
         """
         total_profit = results['profit_abs'].sum()
         try:
-            drawdown_df = calculate_underwater(results, value_col='profit_abs', starting_balance=config['available_capital'])
+            drawdown_df = calculate_underwater(
+                results,
+                value_col='profit_abs',
+                starting_balance=config['available_capital']
+            )
             max_drawdown = abs(min(drawdown_df['drawdown']))
             relative_drawdown = max(drawdown_df['drawdown_relative'])
             if max_drawdown == 0:
@@ -42,4 +45,3 @@ class MaxDrawDownRelativeHyperOptLoss(IHyperOptLoss):
             return -total_profit / max_drawdown / relative_drawdown
         except (Exception, ValueError):
             return -total_profit
-        

freqtrade/optimize/optimize_reports.py

@@ -769,7 +769,7 @@ def text_table_add_metrics(strat_results: Dict) -> str:
             if 'max_drawdown_account' in strat_results else (
                 'Drawdown', f"{strat_results['max_drawdown']:.2%}"),
             ('Absolute Drawdown', round_coin_value(strat_results['max_drawdown_abs'],
-                                          strat_results['stake_currency'])),
+                                                   strat_results['stake_currency'])),
             ('Drawdown high', round_coin_value(strat_results['max_drawdown_high'],
                                                strat_results['stake_currency'])),
             ('Drawdown low', round_coin_value(strat_results['max_drawdown_low'],

freqtrade/plot/plotting.py

@@ -164,7 +164,10 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
     Add scatter points indicating max drawdown
     """
     try:
-        _, highdate, lowdate, _, _, max_drawdown = calculate_max_drawdown(trades, starting_balance=starting_balance)
+        _, highdate, lowdate, _, _, max_drawdown = calculate_max_drawdown(
+            trades,
+            starting_balance=starting_balance
+        )
 
         drawdown = go.Scatter(
             x=[highdate, lowdate],
@@ -194,7 +197,11 @@ def add_underwater(fig, row, trades: pd.DataFrame, starting_balance: number) ->
     Add underwater plots
     """
     try:
-        underwater = calculate_underwater(trades, value_col="profit_abs", starting_balance=starting_balance)
+        underwater = calculate_underwater(
+            trades,
+            value_col="profit_abs",
+            starting_balance=starting_balance
+        )
 
         underwater_plot = go.Scatter(
             x=underwater['date'],
@@ -215,7 +222,7 @@ def add_underwater(fig, row, trades: pd.DataFrame, starting_balance: number) ->
         )
 
         fig.add_trace(underwater_plot, row, 1)
-        fig.add_trace(underwater_plot_relative, row+1, 1)
+        fig.add_trace(underwater_plot_relative, row + 1, 1)
     except ValueError:
         logger.warning("No trades found - not plotting underwater plot")
     return fig