# Chart Improvements - Immediate Tasks ## Overview This document outlines immediate improvements for chart functionality, time range selection, and performance optimization to address current issues with page refreshing and chart state preservation. ## Current Issues Identified - Frequent page refreshing due to debug mode hot-reload (every 2-3 minutes) - Chart zoom/pan state resets when callbacks trigger - No time range control for historical data analysis - Statistics reset when changing parameters - No way to "lock" time range for analysis without real-time updates ## Immediate Tasks (Priority Order) - [x] **Task 1: Fix Page Refresh Issues** (Priority: HIGH - 5 minutes) - [x] 1.1 Choose debug mode option (Option A: debug=False OR Option B: debug=True, use_reloader=False) - [x] 1.2 Update app_new.py with selected debug settings - [x] 1.3 Test app stability (no frequent restarts) - [x] **Task 2: Add Time Range Selector** (Priority: HIGH - 45 minutes) ✅ COMPLETED + ENHANCED - [x] 2.1 Create time range control components - [x] 2.1.1 Add quick select dropdown (1h, 4h, 6h, 12h, 1d, 3d, 7d, 30d, real-time) - [x] 2.1.2 Add custom date picker component - [x] 2.1.3 Add analysis mode toggle (real-time vs locked) - [x] 2.2 Update dashboard layout with time range controls - [x] 2.3 Modify chart callbacks to handle time range inputs - [x] 2.4 Test time range functionality - [x] 2.5 **ENHANCEMENT**: Fixed sub-day time period precision (1h, 4h working correctly) - [x] 2.6 **ENHANCEMENT**: Added 6h and 12h options per user request - [x] 2.7 **ENHANCEMENT**: Fixed custom date range and dropdown interaction logic with Clear button and explicit "Custom Range" dropdown option. - [ ] **Task 3: Prevent Chart State Reset** (Priority: MEDIUM - 45 minutes) - [x] 3.1 Add relayoutData state preservation to chart callbacks (Completed as part of Task 2) - [x] 3.2 Implement smart partial updates using Patch() (Initial implementation for basic charts completed) - [x] 3.3 Preserve zoom/pan during data updates (Completed as part of Task 2 & 3.1) - [x] 3.4 Test chart state preservation (Visual testing by user indicates OK) - [x] 3.5 Refine Patching: More robust trace identification (New sub-task) (Completed) - [x] **Task 4: Enhanced Statistics Integration** (Priority: MEDIUM - 30 minutes) - [x] 4.1 Make statistics respect selected time range - [x] 4.2 Add time range context to statistics display - [x] 4.3 Implement real-time vs historical analysis modes - [x] 4.4 Test statistics integration with time controls - [ ] **Task 5: Advanced Chart Controls** (Priority: LOW - Future) - [ ] 5.1 Chart annotation tools - [ ] 5.2 Export functionality (PNG, SVG, data) - [-] 3.6 Refine Patching: Optimize data fetching for patches (fetch only new data) (New sub-task) - [-] 3.7 Refine Patching: Enable for simple overlay indicators (New sub-task) ## Implementation Plan ### Phase 1: Immediate Fixes (Day 1) 1. **Fix refresh issues** (5 minutes) 2. **Add basic time range dropdown** (30 minutes) 3. **Test and validate** (15 minutes) ### Phase 2: Enhanced Time Controls (Day 1-2) 1. **Add date picker component** (30 minutes) 2. **Implement analysis mode toggle** (30 minutes) 3. **Integrate with statistics** (30 minutes) ### Phase 3: Chart State Preservation (Day 2) 1. **Implement zoom/pan preservation** (45 minutes) 2. **Add smart partial updates** (30 minutes) 3. **Testing and optimization** (30 minutes) ## Technical Specifications ### Time Range Selector UI ```python # Quick Select Dropdown dcc.Dropdown( id='time-range-quick-select', options=[ {'label': '🕐 Last 1 Hour', 'value': '1h'}, {'label': '🕐 Last 4 Hours', 'value': '4h'}, {'label': '📅 Last 1 Day', 'value': '1d'}, {'label': '📅 Last 3 Days', 'value': '3d'}, {'label': '📅 Last 7 Days', 'value': '7d'}, {'label': '📅 Last 30 Days', 'value': '30d'}, {'label': '🔴 Real-time', 'value': 'realtime'} ], value='7d' ) # Custom Date Range Picker dcc.DatePickerRange( id='custom-date-range', display_format='YYYY-MM-DD', style={'margin': '10px 0'} ) # Analysis Mode Toggle dcc.RadioItems( id='analysis-mode-toggle', options=[ {'label': '🔴 Real-time Updates', 'value': 'realtime'}, {'label': '🔒 Analysis Mode (Locked)', 'value': 'locked'} ], value='realtime', inline=True ) ``` ### Enhanced Callback Structure ```python @app.callback( [Output('price-chart', 'figure'), Output('market-stats', 'children')], [Input('symbol-dropdown', 'value'), Input('timeframe-dropdown', 'value'), Input('time-range-quick-select', 'value'), Input('custom-date-range', 'start_date'), Input('custom-date-range', 'end_date'), Input('analysis-mode-toggle', 'value'), Input('interval-component', 'n_intervals')], [State('price-chart', 'relayoutData')], prevent_initial_call=False ) def update_chart_and_stats_with_time_control(...): # Smart update logic with state preservation # Conditional real-time updates based on analysis mode # Time range validation and data fetching ``` ## Success Criteria - ✅ No more frequent page refreshes (app runs stable) - ✅ Chart zoom/pan preserved during updates - ✅ Time range selection works for both quick select and custom dates - ✅ Analysis mode prevents unwanted real-time resets - ✅ Statistics update correctly for selected time ranges - ✅ Smooth user experience without interruptions ## Files to Modify - `app_new.py` - Debug mode settings - `dashboard/layouts/market_data.py` - Add time range UI - `dashboard/callbacks/charts.py` - Enhanced callbacks with state preservation - `dashboard/components/chart_controls.py` - New time range control components - `components/charts/__init__.py` - Enhanced data fetching with time ranges ## Testing Checklist - [ ] App runs without frequent refreshes - [ ] Quick time range selection works - [ ] Custom date picker functions correctly - [ ] Analysis mode prevents real-time updates - [ ] Chart zoom/pan preserved during data updates - [ ] Statistics reflect selected time range - [ ] Symbol changes work with custom time ranges - [ ] Timeframe changes work with custom time ranges - [ ] Real-time mode resumes correctly after analysis mode ## Notes - Prioritize stability and user experience over advanced features - Keep implementation simple and focused on immediate user needs - Consider performance impact of frequent data queries - Ensure backward compatibility with existing functionality