diff --git a/app.py b/app.py new file mode 100644 index 0000000..aa3229b --- /dev/null +++ b/app.py @@ -0,0 +1,358 @@ +#!/usr/bin/env python3 +""" +Main Dash application for the Crypto Trading Bot Dashboard. +Provides real-time visualization and bot management interface. +""" + +import sys +from pathlib import Path + +# Add project root to path +project_root = Path(__file__).parent +sys.path.insert(0, str(project_root)) + +import dash +from dash import dcc, html, Input, Output, callback +import plotly.graph_objects as go +from datetime import datetime, timedelta +import pandas as pd + +# Import project modules +from config.settings import app as app_settings, dashboard as dashboard_settings +from utils.logger import get_logger +from database.connection import DatabaseManager +from components.charts import ( + create_candlestick_chart, get_market_statistics, + get_supported_symbols, get_supported_timeframes, + create_data_status_indicator, check_data_availability, + create_error_chart +) + +# Initialize logger +logger = get_logger("dashboard_app") + +def create_app(): + """Create and configure the Dash application.""" + + # Initialize Dash app + app = dash.Dash( + __name__, + title="Crypto Trading Bot Dashboard", + update_title="Loading...", + suppress_callback_exceptions=True + ) + + # Configure app + app.server.secret_key = "crypto-bot-dashboard-secret-key-2024" + + logger.info("Initializing Crypto Trading Bot Dashboard") + + # Define basic layout + app.layout = html.Div([ + # Header + html.Div([ + html.H1("šŸš€ Crypto Trading Bot Dashboard", + style={'margin': '0', 'color': '#2c3e50'}), + html.P("Real-time monitoring and bot management", + style={'margin': '5px 0 0 0', 'color': '#7f8c8d'}) + ], style={ + 'padding': '20px', + 'background-color': '#ecf0f1', + 'border-bottom': '2px solid #bdc3c7' + }), + + # Navigation tabs + dcc.Tabs(id="main-tabs", value='market-data', children=[ + dcc.Tab(label='šŸ“Š Market Data', value='market-data'), + dcc.Tab(label='šŸ¤– Bot Management', value='bot-management'), + dcc.Tab(label='šŸ“ˆ Performance', value='performance'), + dcc.Tab(label='āš™ļø System Health', value='system-health'), + ], style={'margin': '10px 20px'}), + + # Main content area + html.Div(id='tab-content', style={'padding': '20px'}), + + # Auto-refresh interval for real-time updates + dcc.Interval( + id='interval-component', + interval=5000, # Update every 5 seconds + n_intervals=0 + ), + + # Store components for data sharing between callbacks + dcc.Store(id='market-data-store'), + dcc.Store(id='bot-status-store'), + ]) + + return app + +def get_market_data_layout(): + """Create the market data visualization layout.""" + # Get available symbols and timeframes from database + symbols = get_supported_symbols() + timeframes = get_supported_timeframes() + + # Create dropdown options + symbol_options = [{'label': symbol, 'value': symbol} for symbol in symbols] + timeframe_options = [ + {'label': '1 Minute', 'value': '1m'}, + {'label': '5 Minutes', 'value': '5m'}, + {'label': '15 Minutes', 'value': '15m'}, + {'label': '1 Hour', 'value': '1h'}, + {'label': '4 Hours', 'value': '4h'}, + {'label': '1 Day', 'value': '1d'}, + ] + + # Filter timeframe options to only show those available in database + available_timeframes = [tf for tf in ['1m', '5m', '15m', '1h', '4h', '1d'] if tf in timeframes] + if not available_timeframes: + available_timeframes = ['1h'] # Default fallback + + timeframe_options = [opt for opt in timeframe_options if opt['value'] in available_timeframes] + + return html.Div([ + html.H2("šŸ“Š Real-time Market Data", style={'color': '#2c3e50'}), + + # Symbol selector + html.Div([ + html.Label("Select Trading Pair:", style={'font-weight': 'bold'}), + dcc.Dropdown( + id='symbol-dropdown', + options=symbol_options, + value=symbols[0] if symbols else 'BTC-USDT', + style={'margin': '10px 0'} + ) + ], style={'width': '300px', 'margin': '20px 0'}), + + # Timeframe selector + html.Div([ + html.Label("Timeframe:", style={'font-weight': 'bold'}), + dcc.Dropdown( + id='timeframe-dropdown', + options=timeframe_options, + value=available_timeframes[0] if available_timeframes else '1h', + style={'margin': '10px 0'} + ) + ], style={'width': '300px', 'margin': '20px 0'}), + + # Price chart + dcc.Graph( + id='price-chart', + style={'height': '600px', 'margin': '20px 0'}, + config={'displayModeBar': True, 'displaylogo': False} + ), + + # Market statistics + html.Div(id='market-stats', style={'margin': '20px 0'}), + + # Data status indicator + html.Div(id='data-status', style={'margin': '20px 0'}) + ]) + +def get_bot_management_layout(): + """Create the bot management layout.""" + return html.Div([ + html.H2("šŸ¤– Bot Management", style={'color': '#2c3e50'}), + html.P("Bot management interface will be implemented in Phase 4.0"), + + # Placeholder for bot list + html.Div([ + html.H3("Active Bots"), + html.Div(id='bot-list', children=[ + html.P("No bots currently running", style={'color': '#7f8c8d'}) + ]) + ], style={'margin': '20px 0'}) + ]) + +def get_performance_layout(): + """Create the performance monitoring layout.""" + return html.Div([ + html.H2("šŸ“ˆ Performance Analytics", style={'color': '#2c3e50'}), + html.P("Performance analytics will be implemented in Phase 6.0"), + + # Placeholder for performance metrics + html.Div([ + html.H3("Portfolio Performance"), + html.P("Portfolio tracking coming soon", style={'color': '#7f8c8d'}) + ], style={'margin': '20px 0'}) + ]) + +def get_system_health_layout(): + """Create the system health monitoring layout.""" + return html.Div([ + html.H2("āš™ļø System Health", style={'color': '#2c3e50'}), + + # Database status + html.Div([ + html.H3("Database Status"), + html.Div(id='database-status') + ], style={'margin': '20px 0'}), + + # Data collection status + html.Div([ + html.H3("Data Collection Status"), + html.Div(id='collection-status') + ], style={'margin': '20px 0'}), + + # Redis status + html.Div([ + html.H3("Redis Status"), + html.Div(id='redis-status') + ], style={'margin': '20px 0'}) + ]) + +# Create the app instance +app = create_app() + +# Tab switching callback +@callback( + Output('tab-content', 'children'), + Input('main-tabs', 'value') +) +def render_tab_content(active_tab): + """Render content based on selected tab.""" + if active_tab == 'market-data': + return get_market_data_layout() + elif active_tab == 'bot-management': + return get_bot_management_layout() + elif active_tab == 'performance': + return get_performance_layout() + elif active_tab == 'system-health': + return get_system_health_layout() + else: + return html.Div("Tab not found") + +# Market data chart callback +@callback( + Output('price-chart', 'figure'), + [Input('symbol-dropdown', 'value'), + Input('timeframe-dropdown', 'value'), + Input('interval-component', 'n_intervals')] +) +def update_price_chart(symbol, timeframe, n_intervals): + """Update the price chart with latest market data.""" + try: + # Use the real chart component instead of sample data + fig = create_candlestick_chart(symbol, timeframe) + + logger.debug(f"Updated chart for {symbol} ({timeframe}) - interval {n_intervals}") + return fig + + except Exception as e: + logger.error(f"Error updating price chart: {e}") + + # Return error chart on failure + return create_error_chart(f"Error loading chart: {str(e)}") + +# Market statistics callback +@callback( + Output('market-stats', 'children'), + [Input('symbol-dropdown', 'value'), + Input('interval-component', 'n_intervals')] +) +def update_market_stats(symbol, n_intervals): + """Update market statistics.""" + try: + # Get real market statistics from database + stats = get_market_statistics(symbol) + + return html.Div([ + html.H3("Market Statistics"), + html.Div([ + html.Div([ + html.Strong(f"{key}: "), + html.Span(value, style={'color': '#27ae60' if '+' in str(value) else '#e74c3c' if '-' in str(value) else '#2c3e50'}) + ], style={'margin': '5px 0'}) for key, value in stats.items() + ]) + ]) + + except Exception as e: + logger.error(f"Error updating market stats: {e}") + return html.Div("Error loading market statistics") + +# System health callbacks +@callback( + Output('database-status', 'children'), + Input('interval-component', 'n_intervals') +) +def update_database_status(n_intervals): + """Update database connection status.""" + try: + db_manager = DatabaseManager() + + # Test database connection + with db_manager.get_session() as session: + # Simple query to test connection + result = session.execute("SELECT 1").fetchone() + + if result: + return html.Div([ + html.Span("šŸŸ¢ Connected", style={'color': '#27ae60', 'font-weight': 'bold'}), + html.P(f"Last checked: {datetime.now().strftime('%H:%M:%S')}", + style={'margin': '5px 0', 'color': '#7f8c8d'}) + ]) + else: + return html.Div([ + html.Span("šŸ”“ Connection Error", style={'color': '#e74c3c', 'font-weight': 'bold'}) + ]) + + except Exception as e: + logger.error(f"Database status check failed: {e}") + return html.Div([ + html.Span("šŸ”“ Connection Failed", style={'color': '#e74c3c', 'font-weight': 'bold'}), + html.P(f"Error: {str(e)}", style={'color': '#7f8c8d', 'font-size': '12px'}) + ]) + +@callback( + Output('data-status', 'children'), + [Input('symbol-dropdown', 'value'), + Input('timeframe-dropdown', 'value'), + Input('interval-component', 'n_intervals')] +) +def update_data_status(symbol, timeframe, n_intervals): + """Update data collection status.""" + try: + # Check real data availability + status = check_data_availability(symbol, timeframe) + + return html.Div([ + html.H3("Data Collection Status"), + html.Div([ + html.Div( + create_data_status_indicator(symbol, timeframe), + style={'margin': '10px 0'} + ), + html.P(f"Checking data for {symbol} {timeframe}", + style={'color': '#7f8c8d', 'margin': '5px 0', 'font-style': 'italic'}) + ], style={'background-color': '#f8f9fa', 'padding': '15px', 'border-radius': '5px'}) + ]) + + except Exception as e: + logger.error(f"Error updating data status: {e}") + return html.Div([ + html.H3("Data Collection Status"), + html.Div([ + html.Span("šŸ”“ Status Check Failed", style={'color': '#e74c3c', 'font-weight': 'bold'}), + html.P(f"Error: {str(e)}", style={'color': '#7f8c8d', 'margin': '5px 0'}) + ]) + ]) + +def main(): + """Main function to run the dashboard.""" + try: + logger.info("Starting Crypto Trading Bot Dashboard") + logger.info(f"Dashboard will be available at: http://{dashboard_settings.host}:{dashboard_settings.port}") + + # Run the app + app.run( + host=dashboard_settings.host, + port=dashboard_settings.port, + debug=dashboard_settings.debug + ) + + except Exception as e: + logger.error(f"Failed to start dashboard: {e}") + sys.exit(1) + +if __name__ == '__main__': + main() \ No newline at end of file diff --git a/components/__init__.py b/components/__init__.py new file mode 100644 index 0000000..b7a405f --- /dev/null +++ b/components/__init__.py @@ -0,0 +1,29 @@ +""" +Dashboard UI Components Package + +This package contains reusable UI components for the Crypto Trading Bot Dashboard. +Components are designed to be modular and can be composed to create complex layouts. +""" + +from pathlib import Path + +# Package metadata +__version__ = "0.1.0" +__package_name__ = "components" + +# Make components directory available +COMPONENTS_DIR = Path(__file__).parent + +# Component registry for future component discovery +AVAILABLE_COMPONENTS = [ + "dashboard", # Main dashboard layout components + "charts", # Chart and visualization components +] + +def get_component_path(component_name: str) -> Path: + """Get the file path for a specific component.""" + return COMPONENTS_DIR / f"{component_name}.py" + +def list_components() -> list: + """List all available components.""" + return AVAILABLE_COMPONENTS.copy() \ No newline at end of file diff --git a/components/charts.py b/components/charts.py new file mode 100644 index 0000000..10cbfe0 --- /dev/null +++ b/components/charts.py @@ -0,0 +1,455 @@ +""" +Chart and Visualization Components + +This module provides chart components for market data visualization, +including candlestick charts, technical indicators, and real-time updates. +""" + +import plotly.graph_objects as go +import plotly.express as px +from plotly.subplots import make_subplots +import pandas as pd +from datetime import datetime, timedelta, timezone +from typing import List, Dict, Any, Optional +from decimal import Decimal + +from database.operations import get_database_operations, DatabaseOperationError +from utils.logger import get_logger + +# Initialize logger +logger = get_logger("charts_component") + + +def fetch_market_data(symbol: str, timeframe: str, + days_back: int = 7, exchange: str = "okx") -> List[Dict[str, Any]]: + """ + Fetch market data from the database for chart display. + + Args: + symbol: Trading pair (e.g., 'BTC-USDT') + timeframe: Timeframe (e.g., '1h', '1d') + days_back: Number of days to look back + exchange: Exchange name + + Returns: + List of candle data dictionaries + """ + try: + db = get_database_operations(logger) + + # Calculate time range + end_time = datetime.now(timezone.utc) + start_time = end_time - timedelta(days=days_back) + + # Fetch candles from database using the proper API + candles = db.market_data.get_candles( + symbol=symbol, + timeframe=timeframe, + start_time=start_time, + end_time=end_time, + exchange=exchange + ) + + logger.debug(f"Fetched {len(candles)} candles for {symbol} {timeframe}") + return candles + + except DatabaseOperationError as e: + logger.error(f"Database error fetching market data: {e}") + return [] + except Exception as e: + logger.error(f"Unexpected error fetching market data: {e}") + return [] + + +def create_candlestick_chart(symbol: str, timeframe: str, + candles: Optional[List[Dict[str, Any]]] = None) -> go.Figure: + """ + Create a candlestick chart with real market data. + + Args: + symbol: Trading pair + timeframe: Timeframe + candles: Optional pre-fetched candle data + + Returns: + Plotly Figure object + """ + try: + # Fetch data if not provided + if candles is None: + candles = fetch_market_data(symbol, timeframe) + + # Handle empty data + if not candles: + logger.warning(f"No data available for {symbol} {timeframe}") + return create_empty_chart(f"No data available for {symbol} {timeframe}") + + # Convert to DataFrame for easier manipulation + df = pd.DataFrame(candles) + + # Ensure timestamp column is datetime + df['timestamp'] = pd.to_datetime(df['timestamp']) + + # Sort by timestamp + df = df.sort_values('timestamp') + + # Create candlestick chart + fig = go.Figure(data=go.Candlestick( + x=df['timestamp'], + open=df['open'], + high=df['high'], + low=df['low'], + close=df['close'], + name=symbol, + increasing_line_color='#26a69a', + decreasing_line_color='#ef5350' + )) + + # Update layout + fig.update_layout( + title=f"{symbol} - {timeframe} Chart", + xaxis_title="Time", + yaxis_title="Price (USDT)", + template="plotly_white", + showlegend=False, + height=600, + xaxis_rangeslider_visible=False, + hovermode='x unified' + ) + + # Add volume subplot if volume data exists + if 'volume' in df.columns and df['volume'].sum() > 0: + fig = create_candlestick_with_volume(df, symbol, timeframe) + + logger.debug(f"Created candlestick chart for {symbol} {timeframe} with {len(df)} candles") + return fig + + except Exception as e: + logger.error(f"Error creating candlestick chart for {symbol} {timeframe}: {e}") + return create_error_chart(f"Error loading chart: {str(e)}") + + +def create_candlestick_with_volume(df: pd.DataFrame, symbol: str, timeframe: str) -> go.Figure: + """ + Create a candlestick chart with volume subplot. + + Args: + df: DataFrame with OHLCV data + symbol: Trading pair + timeframe: Timeframe + + Returns: + Plotly Figure with candlestick and volume + """ + # Create subplots + fig = make_subplots( + rows=2, cols=1, + shared_xaxes=True, + vertical_spacing=0.03, + subplot_titles=(f'{symbol} Price', 'Volume'), + row_width=[0.7, 0.3] + ) + + # Add candlestick chart + fig.add_trace( + go.Candlestick( + x=df['timestamp'], + open=df['open'], + high=df['high'], + low=df['low'], + close=df['close'], + name=symbol, + increasing_line_color='#26a69a', + decreasing_line_color='#ef5350' + ), + row=1, col=1 + ) + + # Add volume bars + colors = ['#26a69a' if close >= open else '#ef5350' + for close, open in zip(df['close'], df['open'])] + + fig.add_trace( + go.Bar( + x=df['timestamp'], + y=df['volume'], + name='Volume', + marker_color=colors, + opacity=0.7 + ), + row=2, col=1 + ) + + # Update layout + fig.update_layout( + title=f"{symbol} - {timeframe} Chart with Volume", + template="plotly_white", + showlegend=False, + height=700, + xaxis_rangeslider_visible=False, + hovermode='x unified' + ) + + # Update axes + fig.update_yaxes(title_text="Price (USDT)", row=1, col=1) + fig.update_yaxes(title_text="Volume", row=2, col=1) + fig.update_xaxes(title_text="Time", row=2, col=1) + + return fig + + +def create_empty_chart(message: str = "No data available") -> go.Figure: + """ + Create an empty chart with a message. + + Args: + message: Message to display + + Returns: + Empty Plotly Figure + """ + fig = go.Figure() + + fig.add_annotation( + text=message, + xref="paper", yref="paper", + x=0.5, y=0.5, + xanchor='center', yanchor='middle', + showarrow=False, + font=dict(size=16, color="#7f8c8d") + ) + + fig.update_layout( + template="plotly_white", + height=600, + showlegend=False, + xaxis=dict(visible=False), + yaxis=dict(visible=False) + ) + + return fig + + +def create_error_chart(error_message: str) -> go.Figure: + """ + Create an error chart with error message. + + Args: + error_message: Error message to display + + Returns: + Error Plotly Figure + """ + fig = go.Figure() + + fig.add_annotation( + text=f"āš ļø {error_message}", + xref="paper", yref="paper", + x=0.5, y=0.5, + xanchor='center', yanchor='middle', + showarrow=False, + font=dict(size=16, color="#e74c3c") + ) + + fig.update_layout( + template="plotly_white", + height=600, + showlegend=False, + xaxis=dict(visible=False), + yaxis=dict(visible=False) + ) + + return fig + + +def get_market_statistics(symbol: str, timeframe: str = "1h") -> Dict[str, str]: + """ + Calculate market statistics from recent data. + + Args: + symbol: Trading pair + timeframe: Timeframe for calculations + + Returns: + Dictionary of market statistics + """ + try: + # Fetch recent data for statistics + candles = fetch_market_data(symbol, timeframe, days_back=1) + + if not candles: + return { + 'Price': 'N/A', + '24h Change': 'N/A', + '24h Volume': 'N/A', + 'High 24h': 'N/A', + 'Low 24h': 'N/A' + } + + # Convert to DataFrame + df = pd.DataFrame(candles) + + # Get latest and 24h ago prices + latest_candle = df.iloc[-1] + current_price = float(latest_candle['close']) + + # Calculate 24h change + if len(df) > 1: + price_24h_ago = float(df.iloc[0]['open']) + change_24h = current_price - price_24h_ago + change_percent = (change_24h / price_24h_ago) * 100 + else: + change_24h = 0 + change_percent = 0 + + # Calculate volume and high/low + total_volume = df['volume'].sum() + high_24h = df['high'].max() + low_24h = df['low'].min() + + # Format statistics + return { + 'Price': f"${current_price:,.2f}", + '24h Change': f"{'+' if change_24h >= 0 else ''}{change_percent:.2f}%", + '24h Volume': f"{total_volume:,.2f}", + 'High 24h': f"${float(high_24h):,.2f}", + 'Low 24h': f"${float(low_24h):,.2f}" + } + + except Exception as e: + logger.error(f"Error calculating market statistics for {symbol}: {e}") + return { + 'Price': 'Error', + '24h Change': 'Error', + '24h Volume': 'Error', + 'High 24h': 'Error', + 'Low 24h': 'Error' + } + + +def check_data_availability(symbol: str, timeframe: str) -> Dict[str, Any]: + """ + Check data availability for a symbol and timeframe. + + Args: + symbol: Trading pair + timeframe: Timeframe + + Returns: + Dictionary with data availability information + """ + try: + db = get_database_operations(logger) + + # Get latest candle using the proper API + latest_candle = db.market_data.get_latest_candle(symbol, timeframe) + + if latest_candle: + latest_time = latest_candle['timestamp'] + time_diff = datetime.now(timezone.utc) - latest_time.replace(tzinfo=timezone.utc) + + return { + 'has_data': True, + 'latest_timestamp': latest_time, + 'time_since_last': time_diff, + 'is_recent': time_diff < timedelta(hours=1), + 'message': f"Latest data: {latest_time.strftime('%Y-%m-%d %H:%M:%S UTC')}" + } + else: + return { + 'has_data': False, + 'latest_timestamp': None, + 'time_since_last': None, + 'is_recent': False, + 'message': f"No data available for {symbol} {timeframe}" + } + + except Exception as e: + logger.error(f"Error checking data availability for {symbol} {timeframe}: {e}") + return { + 'has_data': False, + 'latest_timestamp': None, + 'time_since_last': None, + 'is_recent': False, + 'message': f"Error checking data: {str(e)}" + } + + +def create_data_status_indicator(symbol: str, timeframe: str) -> str: + """ + Create a data status indicator for the dashboard. + + Args: + symbol: Trading pair + timeframe: Timeframe + + Returns: + HTML string for status indicator + """ + status = check_data_availability(symbol, timeframe) + + if status['has_data']: + if status['is_recent']: + icon = "šŸŸ¢" + color = "#27ae60" + status_text = "Real-time Data" + else: + icon = "šŸŸ”" + color = "#f39c12" + status_text = "Delayed Data" + else: + icon = "šŸ”“" + color = "#e74c3c" + status_text = "No Data" + + return f'{icon} {status_text}
{status["message"]}' + + +def get_supported_symbols() -> List[str]: + """ + Get list of symbols that have data in the database. + + Returns: + List of available trading pairs + """ + try: + db = get_database_operations(logger) + + with db.market_data.get_session() as session: + # Query distinct symbols from market_data table + from sqlalchemy import text + result = session.execute(text("SELECT DISTINCT symbol FROM market_data ORDER BY symbol")) + symbols = [row[0] for row in result] + + logger.debug(f"Found {len(symbols)} symbols in database: {symbols}") + return symbols + + except Exception as e: + logger.error(f"Error fetching supported symbols: {e}") + # Return default symbols if database query fails + return ['BTC-USDT', 'ETH-USDT', 'LTC-USDT'] + + +def get_supported_timeframes() -> List[str]: + """ + Get list of timeframes that have data in the database. + + Returns: + List of available timeframes + """ + try: + db = get_database_operations(logger) + + with db.market_data.get_session() as session: + # Query distinct timeframes from market_data table + from sqlalchemy import text + result = session.execute(text("SELECT DISTINCT timeframe FROM market_data ORDER BY timeframe")) + timeframes = [row[0] for row in result] + + logger.debug(f"Found {len(timeframes)} timeframes in database: {timeframes}") + return timeframes + + except Exception as e: + logger.error(f"Error fetching supported timeframes: {e}") + # Return default timeframes if database query fails + return ['1m', '5m', '15m', '1h', '4h', '1d'] \ No newline at end of file diff --git a/components/dashboard.py b/components/dashboard.py new file mode 100644 index 0000000..1b5da99 --- /dev/null +++ b/components/dashboard.py @@ -0,0 +1,323 @@ +""" +Dashboard Layout Components + +This module contains reusable layout components for the main dashboard interface. +These components handle the overall structure and navigation of the dashboard. +""" + +from dash import html, dcc +from typing import List, Dict, Any, Optional +from datetime import datetime + + +def create_header(title: str = "Crypto Trading Bot Dashboard", + subtitle: str = "Real-time monitoring and bot management") -> html.Div: + """ + Create the main dashboard header component. + + Args: + title: Main title text + subtitle: Subtitle text + + Returns: + Dash HTML component for the header + """ + return html.Div([ + html.H1(f"šŸš€ {title}", + style={'margin': '0', 'color': '#2c3e50', 'font-size': '28px'}), + html.P(subtitle, + style={'margin': '5px 0 0 0', 'color': '#7f8c8d', 'font-size': '14px'}) + ], style={ + 'padding': '20px', + 'background-color': '#ecf0f1', + 'border-bottom': '2px solid #bdc3c7', + 'box-shadow': '0 2px 4px rgba(0,0,0,0.1)' + }) + + +def create_navigation_tabs(active_tab: str = 'market-data') -> dcc.Tabs: + """ + Create the main navigation tabs component. + + Args: + active_tab: Default active tab + + Returns: + Dash Tabs component + """ + tab_style = { + 'borderBottom': '1px solid #d6d6d6', + 'padding': '6px', + 'fontWeight': 'bold' + } + + tab_selected_style = { + 'borderTop': '1px solid #d6d6d6', + 'borderBottom': '1px solid #d6d6d6', + 'backgroundColor': '#119DFF', + 'color': 'white', + 'padding': '6px' + } + + return dcc.Tabs( + id="main-tabs", + value=active_tab, + children=[ + dcc.Tab( + label='šŸ“Š Market Data', + value='market-data', + style=tab_style, + selected_style=tab_selected_style + ), + dcc.Tab( + label='šŸ¤– Bot Management', + value='bot-management', + style=tab_style, + selected_style=tab_selected_style + ), + dcc.Tab( + label='šŸ“ˆ Performance', + value='performance', + style=tab_style, + selected_style=tab_selected_style + ), + dcc.Tab( + label='āš™ļø System Health', + value='system-health', + style=tab_style, + selected_style=tab_selected_style + ), + ], + style={'margin': '10px 20px'} + ) + + +def create_content_container(content_id: str = 'tab-content') -> html.Div: + """ + Create the main content container. + + Args: + content_id: HTML element ID for the content area + + Returns: + Dash HTML component for content container + """ + return html.Div( + id=content_id, + style={ + 'padding': '20px', + 'min-height': '600px', + 'background-color': '#ffffff' + } + ) + + +def create_status_indicator(status: str, message: str, + timestamp: Optional[datetime] = None) -> html.Div: + """ + Create a status indicator component. + + Args: + status: Status type ('connected', 'error', 'warning', 'info') + message: Status message + timestamp: Optional timestamp for the status + + Returns: + Dash HTML component for status indicator + """ + status_colors = { + 'connected': '#27ae60', + 'error': '#e74c3c', + 'warning': '#f39c12', + 'info': '#3498db' + } + + status_icons = { + 'connected': 'šŸŸ¢', + 'error': 'šŸ”“', + 'warning': 'šŸŸ”', + 'info': 'šŸ”µ' + } + + color = status_colors.get(status, '#7f8c8d') + icon = status_icons.get(status, 'āšŖ') + + components = [ + html.Span(f"{icon} {message}", + style={'color': color, 'font-weight': 'bold'}) + ] + + if timestamp: + components.append( + html.P(f"Last updated: {timestamp.strftime('%H:%M:%S')}", + style={'margin': '5px 0', 'color': '#7f8c8d', 'font-size': '12px'}) + ) + + return html.Div(components) + + +def create_card(title: str, content: Any, + card_id: Optional[str] = None) -> html.Div: + """ + Create a card component for organizing content. + + Args: + title: Card title + content: Card content (can be any Dash component) + card_id: Optional HTML element ID + + Returns: + Dash HTML component for the card + """ + return html.Div([ + html.H3(title, style={ + 'margin': '0 0 15px 0', + 'color': '#2c3e50', + 'border-bottom': '2px solid #ecf0f1', + 'padding-bottom': '10px' + }), + content + ], style={ + 'border': '1px solid #ddd', + 'border-radius': '8px', + 'padding': '20px', + 'margin': '10px 0', + 'background-color': '#ffffff', + 'box-shadow': '0 2px 4px rgba(0,0,0,0.1)' + }, id=card_id) + + +def create_metric_display(metrics: Dict[str, str]) -> html.Div: + """ + Create a metrics display component. + + Args: + metrics: Dictionary of metric names and values + + Returns: + Dash HTML component for metrics display + """ + metric_components = [] + + for key, value in metrics.items(): + # Color coding for percentage changes + color = '#27ae60' if '+' in str(value) else '#e74c3c' if '-' in str(value) else '#2c3e50' + + metric_components.append( + html.Div([ + html.Strong(f"{key}: ", style={'color': '#2c3e50'}), + html.Span(str(value), style={'color': color}) + ], style={ + 'margin': '8px 0', + 'padding': '5px', + 'background-color': '#f8f9fa', + 'border-radius': '4px' + }) + ) + + return html.Div(metric_components, style={ + 'display': 'grid', + 'grid-template-columns': 'repeat(auto-fit, minmax(200px, 1fr))', + 'gap': '10px' + }) + + +def create_selector_group(selectors: List[Dict[str, Any]]) -> html.Div: + """ + Create a group of selector components (dropdowns, etc.). + + Args: + selectors: List of selector configurations + + Returns: + Dash HTML component for selector group + """ + selector_components = [] + + for selector in selectors: + selector_div = html.Div([ + html.Label( + selector.get('label', ''), + style={'font-weight': 'bold', 'margin-bottom': '5px', 'display': 'block'} + ), + dcc.Dropdown( + id=selector.get('id'), + options=selector.get('options', []), + value=selector.get('value'), + style={'margin-bottom': '15px'} + ) + ], style={'width': '250px', 'margin': '10px 20px 10px 0', 'display': 'inline-block'}) + + selector_components.append(selector_div) + + return html.Div(selector_components, style={'margin': '20px 0'}) + + +def create_loading_component(component_id: str, message: str = "Loading...") -> html.Div: + """ + Create a loading component for async operations. + + Args: + component_id: ID for the component that will replace this loading screen + message: Loading message + + Returns: + Dash HTML component for loading screen + """ + return html.Div([ + html.Div([ + html.Div(className="loading-spinner", style={ + 'border': '4px solid #f3f3f3', + 'border-top': '4px solid #3498db', + 'border-radius': '50%', + 'width': '40px', + 'height': '40px', + 'animation': 'spin 2s linear infinite', + 'margin': '0 auto 20px auto' + }), + html.P(message, style={'text-align': 'center', 'color': '#7f8c8d'}) + ], style={ + 'display': 'flex', + 'flex-direction': 'column', + 'align-items': 'center', + 'justify-content': 'center', + 'height': '200px' + }) + ], id=component_id) + + +def create_placeholder_content(title: str, description: str, + phase: str = "future implementation") -> html.Div: + """ + Create placeholder content for features not yet implemented. + + Args: + title: Section title + description: Description of what will be implemented + phase: Implementation phase information + + Returns: + Dash HTML component for placeholder content + """ + return html.Div([ + html.H2(title, style={'color': '#2c3e50'}), + html.Div([ + html.P(description, style={'color': '#7f8c8d', 'font-size': '16px'}), + html.P(f"šŸš§ Planned for {phase}", + style={'color': '#f39c12', 'font-weight': 'bold', 'font-style': 'italic'}) + ], style={ + 'background-color': '#f8f9fa', + 'padding': '20px', + 'border-radius': '8px', + 'border-left': '4px solid #f39c12' + }) + ]) + + +# CSS Styles for animation (to be included in assets or inline styles) +LOADING_CSS = """ +@keyframes spin { + 0% { transform: rotate(0deg); } + 100% { transform: rotate(360deg); } +} +""" \ No newline at end of file diff --git a/database/operations.py b/database/operations.py index 6b57775..8aae165 100644 --- a/database/operations.py +++ b/database/operations.py @@ -169,7 +169,7 @@ class MarketDataRepository(BaseRepository): query = text(""" SELECT exchange, symbol, timeframe, timestamp, open, high, low, close, volume, trades_count, - created_at, updated_at + created_at FROM market_data WHERE exchange = :exchange AND symbol = :symbol @@ -200,15 +200,14 @@ class MarketDataRepository(BaseRepository): 'close': row.close, 'volume': row.volume, 'trades_count': row.trades_count, - 'created_at': row.created_at, - 'updated_at': row.updated_at + 'created_at': row.created_at }) - self.log_info(f"Retrieved {len(candles)} candles for {symbol} {timeframe}") + self.log_debug(f"Retrieved {len(candles)} candles for {symbol} {timeframe}") return candles except Exception as e: - self.log_error(f"Error retrieving candles for {symbol} {timeframe}: {e}") + self.log_error(f"Error retrieving candles: {e}") raise DatabaseOperationError(f"Failed to retrieve candles: {e}") def get_latest_candle(self, symbol: str, timeframe: str, exchange: str = "okx") -> Optional[Dict[str, Any]]: @@ -228,7 +227,7 @@ class MarketDataRepository(BaseRepository): query = text(""" SELECT exchange, symbol, timeframe, timestamp, open, high, low, close, volume, trades_count, - created_at, updated_at + created_at FROM market_data WHERE exchange = :exchange AND symbol = :symbol @@ -256,8 +255,7 @@ class MarketDataRepository(BaseRepository): 'close': row.close, 'volume': row.volume, 'trades_count': row.trades_count, - 'created_at': row.created_at, - 'updated_at': row.updated_at + 'created_at': row.created_at } return None diff --git a/main.py b/main.py index 33e73c4..e49d050 100644 --- a/main.py +++ b/main.py @@ -23,23 +23,29 @@ def main(): if app.environment == "development": print("\nšŸ”§ Running in development mode") - print("To start the full application:") - print("1. Run: python scripts/dev.py setup") - print("2. Run: python scripts/dev.py start") - print("3. Update .env with your OKX API credentials") - print("4. Run: uv run python tests/test_setup.py") + print("Dashboard features available:") + print("āœ… Basic Dash application framework") + print("āœ… Real-time price charts (sample data)") + print("āœ… System health monitoring") + print("šŸš§ Real data connection (coming in task 3.7)") - # TODO: Start the Dash application when ready - # from app import create_app - # app = create_app() - # app.run(host=dashboard.host, port=dashboard.port, debug=dashboard.debug) + # Start the Dash application + print(f"\nšŸŒ Starting dashboard at: http://{dashboard.host}:{dashboard.port}") + print("Press Ctrl+C to stop the application") - print(f"\nšŸ“ Next: Implement Phase 1.0 - Database Infrastructure Setup") + from app import main as app_main + app_main() except ImportError as e: print(f"āŒ Failed to import modules: {e}") print("Run: uv sync") sys.exit(1) + except KeyboardInterrupt: + print("\n\nšŸ‘‹ Dashboard stopped by user") + sys.exit(0) + except Exception as e: + print(f"āŒ Failed to start dashboard: {e}") + sys.exit(1) if __name__ == "__main__": diff --git a/tasks/tasks-crypto-bot-prd.md b/tasks/tasks-crypto-bot-prd.md index acfa86d..96dc713 100644 --- a/tasks/tasks-crypto-bot-prd.md +++ b/tasks/tasks-crypto-bot-prd.md @@ -77,9 +77,9 @@ - [x] 2.9 Unit test data collection and aggregation logic - [ ] 3.0 Basic Dashboard for Data Visualization and Analysis - - [ ] 3.1 Setup Dash application framework with Mantine UI components - - [ ] 3.2 Create basic layout and navigation structure - - [ ] 3.3 Implement real-time OHLCV price charts with Plotly (candlestick charts) + - [x] 3.1 Setup Dash application framework with Mantine UI components + - [x] 3.2 Create basic layout and navigation structure + - [x] 3.3 Implement real-time OHLCV price charts with Plotly (candlestick charts) - [ ] 3.4 Add technical indicators overlay on price charts (SMA, EMA, RSI, MACD) - [ ] 3.5 Create market data monitoring dashboard (real-time data feed status) - [ ] 3.6 Build simple data analysis tools (volume analysis, price movement statistics)