(feat) format visualizations

frontend/visualization/backtesting.py

@@ -1,5 +1,6 @@
 from plotly.subplots import make_subplots
-from frontend.visualization.candles import get_bt_candlestick_trace, get_candlestick_trace
+
+from frontend.visualization.candles import get_bt_candlestick_trace
 from frontend.visualization.executors import add_executors_trace
 from frontend.visualization.pnl import get_pnl_trace
 from frontend.visualization.theme import get_default_layout

frontend/visualization/backtesting_metrics.py

@@ -38,6 +38,7 @@ def render_accuracy_metrics(summary_results):
     st.metric(label="Accuracy Long", value=f"{accuracy_long:.2%}")
     st.metric(label="Accuracy Short", value=f"{accuracy_short:.2%}")
 
+
 def render_accuracy_metrics2(summary_results):
     accuracy = summary_results.get('accuracy', 0)
     total_long = summary_results.get('total_long', 0)

frontend/visualization/candles.py

@@ -1,5 +1,5 @@
-import plotly.graph_objects as go
 import pandas as pd
+import plotly.graph_objects as go
 
 from frontend.visualization import theme
 
@@ -11,7 +11,7 @@ def get_candlestick_trace(df):
                           low=df['low'],
                           close=df['close'],
                           name="Candlesticks",
-                          increasing_line_color='#2ECC71', decreasing_line_color='#E74C3C',)
+                          increasing_line_color='#2ECC71', decreasing_line_color='#E74C3C', )
 
 
 def get_bt_candlestick_trace(df):

frontend/visualization/dca_builder.py

@@ -1,6 +1,6 @@
-from decimal import Decimal
 import plotly.graph_objects as go
 from plotly.subplots import make_subplots
+
 import frontend.visualization.theme as theme
 
 

frontend/visualization/executors_distribution.py

@@ -1,9 +1,11 @@
 import numpy as np
 import plotly.graph_objects as go
+
 import frontend.visualization.theme as theme
 
 
-def create_executors_distribution_traces(buy_spreads, sell_spreads, buy_amounts_pct, sell_amounts_pct, total_amount_quote):
+def create_executors_distribution_traces(buy_spreads, sell_spreads, buy_amounts_pct, sell_amounts_pct,
+                                         total_amount_quote):
     colors = theme.get_color_scheme()
 
     buy_spread_distributions = [spread * 100 for spread in buy_spreads]

frontend/visualization/indicators.py

@@ -24,7 +24,9 @@ def get_bbands_traces(df, bb_length, bb_std):
 
 def get_volume_trace(df):
     df.index = pd.to_datetime(df.timestamp, unit='s')
-    return go.Bar(x=df.index, y=df['volume'], name="Volume", marker_color=theme.get_color_scheme()["volume"], opacity=0.7)
+    return go.Bar(x=df.index, y=df['volume'], name="Volume", marker_color=theme.get_color_scheme()["volume"],
+                  opacity=0.7)
+
 
 def get_macd_traces(df, macd_fast, macd_slow, macd_signal):
     tech_colors = theme.get_color_scheme()
@@ -38,7 +40,8 @@ def get_macd_traces(df, macd_fast, macd_slow, macd_signal):
         go.Scatter(x=df.index, y=df[macd_s], line=dict(color=tech_colors['macd_signal']),
                    name='MACD Signal'),
         go.Bar(x=df.index, y=df[macd_hist], name='MACD Histogram',
-               marker_color=df[f"MACDh_{macd_fast}_{macd_slow}_{macd_signal}"].apply(lambda x: '#FF6347' if x < 0 else '#32CD32'))
+               marker_color=df[f"MACDh_{macd_fast}_{macd_slow}_{macd_signal}"].apply(
+                   lambda x: '#FF6347' if x < 0 else '#32CD32'))
     ]
     return traces
 
@@ -79,4 +82,3 @@ def get_supertrend_traces(df, length, multiplier):
     ]
 
     return traces
-

frontend/visualization/signals.py

@@ -1,6 +1,7 @@
-from frontend.visualization import theme
-import plotly.graph_objects as go
 import pandas_ta as ta  # noqa: F401
+import plotly.graph_objects as go
+
+from frontend.visualization import theme
 
 
 def get_signal_traces(buy_signals, sell_signals):
@@ -15,6 +16,7 @@ def get_signal_traces(buy_signals, sell_signals):
     ]
     return traces
 
+
 def get_bollinger_v1_signal_traces(df, bb_length, bb_std, bb_long_threshold, bb_short_threshold):
     # Add Bollinger Bands
     candles = df.copy()
@@ -29,7 +31,6 @@ def get_bollinger_v1_signal_traces(df, bb_length, bb_std, bb_long_threshold, bb_
 
 def get_macdbb_v1_signal_traces(df, bb_length, bb_std, bb_long_threshold, bb_short_threshold, macd_fast, macd_slow,
                                 macd_signal):
-    tech_colors = theme.get_color_scheme()
     # Add Bollinger Bands
     df.ta.bbands(length=bb_length, std=bb_std, append=True)
     # Add MACD