Remove plotting logic and instead depend on local plotting module

backtest_iron_condor_example.py

@@ -1,5 +1,6 @@
 from backtesting import backtest_iron_condor, DeltaTargetStrategy, OptionType
 from datetime import datetime
+from plotting import BacktestChart, plot
 
 def create_strategies(entry_time: str, number_of_contracts: int = 1):
     call_spread_strategy = DeltaTargetStrategy(
@@ -34,5 +35,9 @@ if __name__ == '__main__':
         end_date
     )
     print(backtest_result)
-    # TODO: Move plot() to plotting module.
+
-    # plot(backtest_result, title = 'Iron Condor Backtest Results')
+    plot(BacktestChart(
+        dates = backtest_result['Date'], 
+        profit = backtest_result['Cumulative Profit'], 
+        title = f'Iron Condor @ {call_spread_strategy.trade_entry_time}'
+    ))

backtesting/backtest_iron_condor.py

@@ -1,5 +1,4 @@
 import logging
-import numpy as np
 import os
 import pandas as pd
 import plotly.express as px
@@ -44,42 +43,6 @@ max_profits = []
 wins = []
 exit_times = []
 
-def plot(backtest_results: pd.DataFrame, title: str):
-    backtest_results.drop('Profit', axis = 1, inplace = True)
-    backtest_results.rename(columns = {'Cumulative Profit' : 'Profit'}, inplace = True)
-
-    # Exclude dates on which the market was closed from being plotted in order to prevent gaps on chart.
-    start_date = backtest_results['Date'].min()
-    end_date = backtest_results['Date'].max()
-    backtest_date_range = pd.date_range(start = start_date, end = end_date).to_list()
-    backtest_date_range = set([timestamp.strftime('%Y-%m-%d') for timestamp in backtest_date_range])
-    backtested_dates = set(backtest_results['Date'].to_list())
-    excluded_dates = backtest_date_range - backtested_dates
-
-    backtest_results['Color'] = np.where(backtest_results['Profit'] >= 0, 'limegreen', 'red')
-    color_sequence = ['limegreen', 'red'] if backtest_results.iloc[0]['Profit'] >= 0 else ['red', 'limegreen']
-
-    chart = px.bar(backtest_results, x='Date', y='Profit', title=title, color='Color', color_discrete_sequence=color_sequence, hover_data={'Color': False})
-    chart.update_layout({
-        'font_color': '#7a7c7d',
-        'plot_bgcolor': '#0f0f0f',
-        'paper_bgcolor': '#0f0f0f',
-        'title_font_color': '#7a7c7d',
-        'xaxis': {
-            'gridcolor': '#0f0f0f',
-            'zerolinecolor': '#0f0f0f'
-        },
-        'yaxis': {
-            'gridcolor': '#0f0f0f',
-            'zerolinecolor': '#0f0f0f'
-        }
-    })
-    chart.update_traces(marker_line_width=0, selector=dict(type='bar'))
-    chart.update_layout(bargap=0, bargroupgap = 0)
-    chart.update_layout(showlegend=False)
-    chart.update_xaxes(rangebreaks=[dict(values=list(excluded_dates))])
-    chart.show()
-
 def get_spread_history_credit(historical_option_data: pd.DataFrame, option_strat: CreditTargetStrategy) -> pd.DataFrame:
     current_date = historical_option_data.iloc[0]['quote_datetime'][:10]
     opening_quotes = historical_option_data[(historical_option_data['quote_datetime'] == (current_date + ' ' + option_strat.trade_entry_time))]