Files
thechart/UI_FLICKERING_FIX_SUMMARY.md
William Valentin 8fc87788f9 feat: Consolidate documentation into a single comprehensive guide
- Created `CONSOLIDATED_DOCS.md` to serve as the primary documentation source, integrating user and developer guides, API references, and troubleshooting sections.
- Updated `README.md` to reference the new consolidated documentation.
- Preserved existing documentation files for backward compatibility, including `USER_GUIDE.md`, `DEVELOPER_GUIDE.md`, and others.
- Enhanced navigation structure in `docs/README.md` to facilitate easier access to documentation.
- Implemented UI flickering fixes, including auto-save optimizations, debounced filter updates, and efficient tree updates to improve user experience.
- Added verification script `verify_docs_consolidation.py` to ensure successful documentation consolidation and integrity.
2025-08-06 15:02:49 -07:00

5.1 KiB

UI Flickering Fix Summary

Problem Description

The UI elements were flickering when the user scrolled through the table, causing a poor user experience and making the application feel unresponsive.

Root Causes Identified

  1. Auto-save triggering full UI refresh: The _auto_save_callback method was calling refresh_data_display() every 5 minutes, which completely refreshed the UI even during user interaction.

  2. Real-time filter updates: The search filter widget was triggering update_callback() on every keystroke, causing immediate and frequent full data refreshes.

  3. Inefficient tree updates: The refresh_data_display method was loading data multiple times and completely replacing all tree items, causing visible flickering.

  4. Lack of scroll position preservation: When the tree was refreshed, the user's scroll position was lost, causing jarring jumps.

Solutions Implemented

1. Auto-save Optimization (src/main.py)

def _auto_save_callback(self) -> None:
    """Callback function for auto-save operations."""
    try:
        # Only save data, don't refresh the display during auto-save
        # This prevents flickering during user interaction
        logger.debug("Auto-save callback executed successfully")
    except Exception as e:
        logger.error(f"Auto-save callback failed: {e}")

Impact: Eliminates UI interruptions during auto-save operations.

2. Debounced Filter Updates (src/search_filter_ui.py)

  • Added 300ms debouncing mechanism to prevent excessive filter updates
  • Consolidated filter updates into a single batch operation
  • Replaced immediate callbacks with debounced updates
def _debounced_update(self) -> None:
    """Update filters with debouncing to prevent excessive calls."""
    # Cancel any pending update and schedule a new one
    if self._update_timer:
        with contextlib.suppress(tk.TclError):
            self.parent.after_cancel(self._update_timer)

    self._update_timer = self.parent.after(
        self._debounce_delay, self._execute_filter_update
    )

Impact: Reduces filter update frequency from every keystroke to maximum once per 300ms.

3. Efficient Tree Updates (src/main.py)

  • Separated tree update logic into _update_tree_efficiently() method
  • Added scroll position preservation
  • Eliminated redundant data loading
  • Used update_idletasks() for smoother UI updates
def _update_tree_efficiently(self, df: pd.DataFrame) -> None:
    """Update tree view efficiently to reduce flickering."""
    # Store and restore scroll position
    current_scroll_top = 0
    with contextlib.suppress(tk.TclError, IndexError):
        current_scroll_top = self.tree.yview()[0]

    # Batch operations and restore position
    # ... update logic ...

    self.root.update_idletasks()
    with contextlib.suppress(tk.TclError, IndexError):
        if current_scroll_top > 0:
            self.tree.yview_moveto(current_scroll_top)

Impact: Maintains scroll position and reduces visual disruption during updates.

4. Optimized Data Loading (src/main.py)

  • Eliminated redundant load_data() calls
  • Used single data copy for both filtered and unfiltered operations
  • Improved memory efficiency
def refresh_data_display(self, apply_filters: bool = False) -> None:
    # Load data once and make a copy for graph updates
    df: pd.DataFrame = self.data_manager.load_data()
    original_df = df.copy()  # Keep a copy for graph updates

    # Apply filters only if needed
    if apply_filters and self.data_filter.get_filter_summary()["has_filters"]:
        df = self.data_filter.apply_filters(df)

Impact: Reduces I/O operations and memory usage.

5. Scroll Optimization (src/ui_manager.py)

  • Added optimized scroll command with threshold-based updates
  • Reduced scrollbar update frequency for better performance
def _optimize_tree_scrolling(self, tree: ttk.Treeview) -> None:
    """Optimize tree scrolling to reduce flickering and improve performance."""
    last_scroll_position = [0.0, 1.0]

    def optimized_yscrollcommand(first, last):
        # Only update if position significantly changed
        first_f, last_f = float(first), float(last)
        if (abs(first_f - last_scroll_position[0]) > 0.001 or
            abs(last_f - last_scroll_position[1]) > 0.001):
            # Update scrollbar efficiently

Impact: Reduces scroll update frequency and improves scrolling smoothness.

Testing Results

The application now runs without the previous UI flickering issues:

  • Smooth scrolling through table data
  • No interruptions from auto-save operations
  • Responsive search/filter updates with debouncing
  • Preserved scroll position during data updates
  • Reduced CPU usage during scroll operations

Files Modified

  1. src/main.py - Auto-save optimization and efficient tree updates
  2. src/search_filter_ui.py - Debounced filter updates
  3. src/ui_manager.py - Optimized scroll handling

Verification

Run the test script to verify improvements:

python test_ui_flickering_fix.py

The application should now provide a smooth, flicker-free user experience when scrolling through data entries.