c121b469f0
- Updated `ChartBuilder` to support dynamic indicator integration, allowing users to specify overlay and subplot indicators for enhanced chart analysis. - Implemented a new `get_indicator_data` method in `MarketDataIntegrator` for fetching indicator data based on user configurations. - Added `create_export_controls` in `chart_controls.py` to facilitate data export options (CSV/JSON) for user analysis. - Enhanced error handling and logging throughout the chart and data analysis processes to improve reliability and user feedback. - Updated documentation to reflect new features and usage guidelines for indicator management and data export functionalities.
213 lines
9.6 KiB
Python
213 lines
9.6 KiB
Python
"""
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Chart-related callbacks for the dashboard.
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"""
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from dash import Output, Input, State, Patch, ctx, html, no_update, dcc
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from datetime import datetime, timedelta
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from utils.logger import get_logger
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from components.charts import (
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create_strategy_chart,
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create_chart_with_indicators,
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create_error_chart,
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)
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from dashboard.components.data_analysis import get_market_statistics
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from components.charts.config import get_all_example_strategies
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from database.connection import DatabaseManager
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from components.charts.builder import ChartBuilder
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from components.charts.utils import prepare_chart_data
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import pandas as pd
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import io
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logger = get_logger("default_logger")
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def calculate_time_range(time_range_quick, custom_start_date, custom_end_date, analysis_mode, n_intervals):
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"""Calculate days_back and status message based on time range controls."""
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try:
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predefined_ranges = ['1h', '4h', '6h', '12h', '1d', '3d', '7d', '30d']
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if time_range_quick in predefined_ranges:
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time_map = {
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'1h': (1/24, '🕐 Last 1 Hour'), '4h': (4/24, '🕐 Last 4 Hours'), '6h': (6/24, '🕐 Last 6 Hours'),
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'12h': (12/24, '🕐 Last 12 Hours'), '1d': (1, '📅 Last 1 Day'), '3d': (3, '📅 Last 3 Days'),
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'7d': (7, '📅 Last 7 Days'), '30d': (30, '📅 Last 30 Days')
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}
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days_back_fractional, label = time_map[time_range_quick]
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mode_text = "🔒 Locked" if analysis_mode == 'locked' else "🔴 Live"
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status = f"{label} | {mode_text}"
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days_back = days_back_fractional if days_back_fractional < 1 else int(days_back_fractional)
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return days_back, status
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if time_range_quick == 'custom' and custom_start_date and custom_end_date:
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start_date = datetime.fromisoformat(custom_start_date.split('T')[0])
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end_date = datetime.fromisoformat(custom_end_date.split('T')[0])
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days_diff = (end_date - start_date).days
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status = f"📅 Custom Range: {start_date.strftime('%Y-%m-%d')} to {end_date.strftime('%Y-%m-%d')} ({days_diff} days)"
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return max(1, days_diff), status
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if time_range_quick == 'realtime':
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mode_text = "🔒 Analysis Mode" if analysis_mode == 'locked' else "🔴 Real-time Updates"
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status = f"📈 Real-time Mode | {mode_text} (Default: Last 7 Days)"
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return 7, status
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mode_text = "🔒 Analysis Mode" if analysis_mode == 'locked' else "🔴 Live"
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default_label = "📅 Default (Last 7 Days)"
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if time_range_quick == 'custom' and not (custom_start_date and custom_end_date):
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default_label = "⏳ Select Custom Dates"
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status = f"{default_label} | {mode_text}"
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return 7, status
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except Exception as e:
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logger.warning(f"Error calculating time range: {e}. Defaulting to 7 days.")
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return 7, f"⚠️ Error in time range. Defaulting to 7 days."
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def register_chart_callbacks(app):
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"""Register chart-related callbacks."""
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@app.callback(
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[Output('price-chart', 'figure'),
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Output('time-range-status', 'children'),
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Output('chart-data-store', 'data')],
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[Input('symbol-dropdown', 'value'),
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Input('timeframe-dropdown', 'value'),
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Input('overlay-indicators-checklist', 'value'),
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Input('subplot-indicators-checklist', 'value'),
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Input('strategy-dropdown', 'value'),
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Input('time-range-quick-select', 'value'),
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Input('custom-date-range', 'start_date'),
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Input('custom-date-range', 'end_date'),
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Input('analysis-mode-toggle', 'value'),
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Input('interval-component', 'n_intervals')],
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[State('price-chart', 'relayoutData'),
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State('price-chart', 'figure')]
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)
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def update_price_chart(symbol, timeframe, overlay_indicators, subplot_indicators, selected_strategy,
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time_range_quick, custom_start_date, custom_end_date, analysis_mode, n_intervals,
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relayout_data, current_figure):
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try:
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triggered_id = ctx.triggered_id
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if triggered_id == 'interval-component' and analysis_mode == 'locked':
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return no_update, no_update, no_update
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days_back, status_message = calculate_time_range(
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time_range_quick, custom_start_date, custom_end_date, analysis_mode, n_intervals
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)
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chart_df = pd.DataFrame()
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if selected_strategy and selected_strategy != 'basic':
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fig, chart_df = create_strategy_chart(symbol, timeframe, selected_strategy, days_back=days_back)
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else:
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fig, chart_df = create_chart_with_indicators(
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symbol=symbol, timeframe=timeframe,
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overlay_indicators=overlay_indicators or [], subplot_indicators=subplot_indicators or [],
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days_back=days_back
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)
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stored_data = None
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if chart_df is not None and not chart_df.empty:
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stored_data = chart_df.to_json(orient='split', date_format='iso')
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if relayout_data and 'xaxis.range' in relayout_data:
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fig.update_layout(xaxis=dict(range=relayout_data['xaxis.range']), yaxis=dict(range=relayout_data.get('yaxis.range')))
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return fig, status_message, stored_data
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except Exception as e:
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logger.error(f"Error updating price chart: {e}", exc_info=True)
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error_fig = create_error_chart(f"Error loading chart: {str(e)}")
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return error_fig, f"❌ Error: {str(e)}", None
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@app.callback(
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Output('analysis-mode-toggle', 'value'),
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Input('price-chart', 'relayoutData'),
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State('analysis-mode-toggle', 'value'),
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prevent_initial_call=True
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)
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def auto_lock_chart_on_interaction(relayout_data, current_mode):
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if relayout_data and 'xaxis.range' in relayout_data and current_mode != 'locked':
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return 'locked'
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return no_update
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@app.callback(
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Output('market-stats', 'children'),
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[Input('chart-data-store', 'data')],
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[State('symbol-dropdown', 'value'),
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State('timeframe-dropdown', 'value')]
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)
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def update_market_stats(stored_data, symbol, timeframe):
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if not stored_data:
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return html.Div("Statistics will be available once chart data is loaded.")
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try:
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df = pd.read_json(io.StringIO(stored_data), orient='split')
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if df.empty:
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return html.Div("Not enough data to calculate statistics.")
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return get_market_statistics(df, symbol, timeframe)
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except Exception as e:
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logger.error(f"Error updating market stats from stored data: {e}", exc_info=True)
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return html.Div(f"Error loading statistics: {e}", style={'color': 'red'})
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@app.callback(
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Output("download-chart-data", "data"),
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[Input("export-csv-btn", "n_clicks"),
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Input("export-json-btn", "n_clicks")],
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[State("chart-data-store", "data"),
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State("symbol-dropdown", "value"),
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State("timeframe-dropdown", "value")],
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prevent_initial_call=True,
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)
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def export_chart_data(csv_clicks, json_clicks, stored_data, symbol, timeframe):
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triggered_id = ctx.triggered_id
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if not triggered_id or not stored_data:
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return no_update
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try:
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df = pd.read_json(io.StringIO(stored_data), orient='split')
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if df.empty:
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return no_update
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename_base = f"chart_data_{symbol}_{timeframe}_{timestamp}"
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if triggered_id == "export-csv-btn":
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return dcc.send_data_frame(df.to_csv, f"{filename_base}.csv", index=False)
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elif triggered_id == "export-json-btn":
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return dict(content=df.to_json(orient='records', date_format='iso'), filename=f"{filename_base}.json")
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except Exception as e:
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logger.error(f"Error exporting chart data from store: {e}", exc_info=True)
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return no_update
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@app.callback(
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[Output('overlay-indicators-checklist', 'value'),
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Output('subplot-indicators-checklist', 'value')],
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[Input('strategy-dropdown', 'value')]
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)
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def update_indicators_from_strategy(selected_strategy):
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if not selected_strategy or selected_strategy == 'basic':
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return [], []
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try:
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all_strategies = get_all_example_strategies()
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if selected_strategy in all_strategies:
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strategy_example = all_strategies[selected_strategy]
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config = strategy_example.config
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overlay_indicators = config.overlay_indicators or []
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subplot_indicators = []
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for subplot_config in config.subplot_configs or []:
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subplot_indicators.extend(subplot_config.indicators or [])
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return overlay_indicators, subplot_indicators
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else:
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return [], []
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except Exception as e:
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logger.error(f"Error loading strategy indicators: {e}", exc_info=True)
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return [], []
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@app.callback(
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[Output('custom-date-range', 'start_date'),
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Output('custom-date-range', 'end_date'),
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Output('time-range-quick-select', 'value')],
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[Input('clear-date-range-btn', 'n_clicks')],
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prevent_initial_call=True
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)
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def clear_custom_date_range(n_clicks):
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if n_clicks and n_clicks > 0:
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return None, None, '7d'
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return no_update, no_update, no_update
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logger.info("Chart callback: Chart callbacks registered successfully") |