(feat) add macd bb

main.py

@@ -17,6 +17,7 @@ def main_page():
             Page("pages/pmm_simple/app.py", "PMM Simple", "👨‍🏫"),
             Page("pages/dman_maker_v2/app.py", "D-Man Maker V2", "🤖"),
             Page("pages/bollinger_v1/app.py", "Bollinger V1", "📈"),
+            Page("pages/macd_bb_v1/app.py", "MACD_BB V1", "📉"),
             Page("pages/xemm_controller/app.py", "XEMM Controller", "⚡️"),
             Page("pages/position_builder/app.py", "Position Builder", "🔭"),
             # Page("pages/master_conf/app.py", "Credentials", "🗝️"),

pages/macd_bb_v1/README.md

@@ -0,0 +1,19 @@
+# D-Man Maker V2
+
+## Features
+- **Interactive Configuration**: Configure market making parameters such as spreads, amounts, and order levels through an intuitive web interface.
+- **Visual Feedback**: Visualize order spread and amount distributions using dynamic Plotly charts.
+- **Backend Integration**: Save and deploy configurations directly to a backend system for active management and execution.
+
+### Using the Tool
+1. **Configure Parameters**: Use the Streamlit interface to input parameters such as connector type, trading pair, and leverage.
+2. **Set Distributions**: Define distributions for buy and sell orders, including spread and amount, either manually or through predefined distribution types like Geometric or Fibonacci.
+3. **Visualize Orders**: View the configured order distributions on a Plotly graph, which illustrates the relationship between spread and amount.
+4. **Export Configuration**: Once the configuration is set, export it as a YAML file or directly upload it to the Backend API.
+5. **Upload**: Use the "Upload Config to BackendAPI" button to send your configuration to the backend system. Then can be used to deploy a new bot.
+
+## Troubleshooting
+- **UI Not Loading**: Ensure all Python dependencies are installed and that the Streamlit server is running correctly.
+- **API Errors**: Check the console for any error messages that may indicate issues with the backend connection.
+
+For more detailed documentation on the backend API and additional configurations, please refer to the project's documentation or contact the development team.

pages/macd_bb_v1/app.py

@@ -0,0 +1,147 @@
+import streamlit as st
+import pandas as pd
+import pandas_ta as ta
+import plotly.graph_objects as go
+import yaml
+from hummingbot.connector.connector_base import OrderType
+from plotly.subplots import make_subplots
+
+from CONFIG import BACKEND_API_HOST, BACKEND_API_PORT
+from utils.backend_api_client import BackendAPIClient
+from utils.st_utils import initialize_st_page
+
+# Initialize the Streamlit page
+initialize_st_page(title="MACD_BB V1", icon="📊", initial_sidebar_state="expanded")
+
+@st.cache_data
+def get_candles(connector_name, trading_pair, interval, max_records):
+    backend_client = BackendAPIClient(BACKEND_API_HOST, BACKEND_API_PORT)
+    return backend_client.get_candles(connector_name, trading_pair, interval, max_records)
+
+@st.cache_data
+def add_indicators(df, bb_length, bb_std, bb_long_threshold, bb_short_threshold, macd_fast, macd_slow, macd_signal):
+    # Bollinger Bands
+    df.ta.bbands(length=bb_length, std=bb_std, append=True)
+    # MACD
+    df.ta.macd(fast=macd_fast, slow=macd_slow, signal=macd_signal, append=True)
+
+    # Decision Logic
+    bbp = df[f"BBP_{bb_length}_{bb_std}"]
+    macdh = df[f"MACDh_{macd_fast}_{macd_slow}_{macd_signal}"]
+    macd = df[f"MACD_{macd_fast}_{macd_slow}_{macd_signal}"]
+
+    long_condition = (bbp < bb_long_threshold) & (macdh > 0) & (macd < 0)
+    short_condition = (bbp > bb_short_threshold) & (macdh < 0) & (macd > 0)
+
+    df["signal"] = 0
+    df.loc[long_condition, "signal"] = 1
+    df.loc[short_condition, "signal"] = -1
+
+    return df
+
+st.write("## Configuration")
+c1, c2, c3, c4 = st.columns(4)
+with c1:
+    connector_name = st.text_input("Connector Name", value="binance_perpetual")
+    trading_pair = st.text_input("Trading Pair", value="WLD-USDT")
+with c2:
+    interval = st.selectbox("Candle Interval", ["1m", "3m", "5m", "15m", "30m"], index=1)
+    max_records = st.number_input("Max Records", min_value=100, max_value=10000, value=1000)
+with c3:
+    macd_fast = st.number_input("MACD Fast", min_value=1, value=21)
+    macd_slow = st.number_input("MACD Slow", min_value=1, value=42)
+    macd_signal = st.number_input("MACD Signal", min_value=1, value=9)
+with c4:
+    bb_length = st.number_input("BB Length", min_value=2, value=100)
+    bb_std = st.number_input("BB Std Dev", min_value=0.1, value=2.0, step=0.1)
+    bb_long_threshold = st.number_input("BB Long Threshold", value=0.0)
+    bb_short_threshold = st.number_input("BB Short Threshold", value=1.0)
+
+# Fetch and process data
+candle_data = get_candles(connector_name, trading_pair, interval, max_records)
+df = pd.DataFrame(candle_data)
+df.index = pd.to_datetime(df['timestamp'], unit='ms')
+df = add_indicators(df, bb_length, bb_std, bb_long_threshold, bb_short_threshold, macd_fast, macd_slow, macd_signal)
+
+# Prepare data for signals
+signals = df[df['signal'] != 0]
+buy_signals = signals[signals['signal'] == 1]
+sell_signals = signals[signals['signal'] == -1]
+
+
+# Define your color palette
+tech_colors = {
+    'upper_band': '#4682B4',
+    'middle_band': '#FFD700',
+    'lower_band': '#32CD32',
+    'buy_signal': '#1E90FF',
+    'sell_signal': '#FF0000',
+}
+
+# Create a subplot with 3 rows
+fig = make_subplots(rows=3, cols=1, shared_xaxes=True,
+                    vertical_spacing=0.05,  # Adjust spacing to make the plot look better
+                    subplot_titles=('Candlestick with Bollinger Bands', 'MACD Line and Histogram', 'Trading Signals'),
+                    row_heights=[0.5, 0.3, 0.2])  # Adjust heights to give more space to candlestick and MACD
+
+# Candlestick and Bollinger Bands
+fig.add_trace(go.Candlestick(x=df.index,
+                             open=df['open'],
+                             high=df['high'],
+                             low=df['low'],
+                             close=df['close'],
+                             name="Candlesticks", increasing_line_color='#2ECC71', decreasing_line_color='#E74C3C'),
+              row=1, col=1)
+
+fig.add_trace(go.Scatter(x=df.index, y=df[f"BBL_{bb_length}_{bb_std}"], line=dict(color='blue'), name='Lower Band'), row=1, col=1)
+fig.add_trace(go.Scatter(x=df.index, y=df[f"BBM_{bb_length}_{bb_std}"], line=dict(color='red'), name='Middle Band'), row=1, col=1)
+fig.add_trace(go.Scatter(x=df.index, y=df[f"BBU_{bb_length}_{bb_std}"], line=dict(color='green'), name='Upper Band'), row=1, col=1)
+
+# MACD Line and Histogram
+fig.add_trace(go.Scatter(x=df.index, y=df[f"MACD_{macd_fast}_{macd_slow}_{macd_signal}"], line=dict(color='orange'), name='MACD Line'), row=2, col=1)
+fig.add_trace(go.Scatter(x=df.index, y=df[f"MACDs_{macd_fast}_{macd_slow}_{macd_signal}"], line=dict(color='purple'), name='MACD Signal'), row=2, col=1)
+fig.add_trace(go.Bar(x=df.index, y=df[f"MACDh_{macd_fast}_{macd_slow}_{macd_signal}"], name='MACD Histogram', marker_color=df[f"MACDh_{macd_fast}_{macd_slow}_{macd_signal}"].apply(lambda x: '#FF6347' if x < 0 else '#32CD32')), row=2, col=1)
+# Signals plot
+fig.add_trace(go.Scatter(x=buy_signals.index, y=buy_signals['close'], mode='markers',
+                         marker=dict(color=tech_colors['buy_signal'], size=20, symbol='triangle-up'),
+                         name='Buy Signal'), row=1, col=1)
+fig.add_trace(go.Scatter(x=sell_signals.index, y=sell_signals['close'], mode='markers',
+                         marker=dict(color=tech_colors['sell_signal'], size=20, symbol='triangle-down'),
+                         name='Sell Signal'), row=1, col=1)
+
+# Trading Signals
+fig.add_trace(go.Scatter(x=signals.index, y=signals['signal'], mode='markers', marker=dict(color=signals['signal'].map({1: '#1E90FF', -1: '#FF0000'}), size=10), name='Trading Signals'), row=3, col=1)
+
+# Update layout settings for a clean look
+fig.update_layout(height=1000, title="MACD and Bollinger Bands Strategy", xaxis_title="Time", yaxis_title="Price", template="plotly_dark", showlegend=True)
+fig.update_xaxes(rangeslider_visible=False, row=1, col=1)
+fig.update_xaxes(rangeslider_visible=False, row=2, col=1)
+fig.update_xaxes(rangeslider_visible=False, row=3, col=1)
+
+# Display the chart
+st.plotly_chart(fig, use_container_width=True)
+
+
+c1, c2, c3 = st.columns([2, 2, 1])
+
+with c1:
+    config_base = st.text_input("Config Base", value=f"macd_bb_v1-{connector_name}-{trading_pair.split('-')[0]}")
+with c2:
+    config_tag = st.text_input("Config Tag", value="1.1")
+
+# Save the configuration
+id = f"{config_base}-{config_tag}"
+
+config = {
+    "id": id,
+    "connector_name": connector_name,
+    "trading_pair": trading_pair,
+    "interval": interval,
+    "bb_length": bb_length,
+    "bb_std": bb_std,
+    "bb_long_threshold": bb_long_threshold,
+    "bb_short_threshold": bb_short_threshold,
+    "macd_fast": macd_fast,
+    "macd_slow": macd_slow,
+    "macd_signal": macd_signal,
+}