Released: Oct 10, 2025

Mises à jour de v2.0

Fonctionnalités

Modifications to Legends

• Legends are now added automatically and can be fully customized at the chart, series, and entry levels, which gives you total control over how information is displayed.
• Chart-level configuration
  • Set up default legend behavior right from chart initialization. You can adjust visibility, position, title, orientation, background style, margins, and even automatic entry management.
• Series-Level Styling
  • Define how each series appears in the legend as you create it. Customize text, button shape and size, fill styles, fonts, and control visibility per series.
• Entry-level customization
  • Use set_entry_options() to style individual components like series or LUTs. Apply custom text, symbols, colors, and LUT display settings to fine-tune the look of each entry.
• Multiple legend support
  • Add multiple legends to the same chart with chart.add_legend(). You can also manually choose which components appear in each one for precise layout control.
• Standalone entries
  • Include additional informational entries not linked to any chart component using the add() method — perfect for notes, labels, or other context indicators.

ChartXY Series Data API Improvements

• The ChartXY Series Data API has been enhanced to offer more flexibility, precision, and efficiency in how data is added, managed, and updated.
• Updated Data Addition Methods
  • The following methods have been improved for better usability and performance:
    • add(), add_dict_data(), append_JSON(), append_sample(), and append_samples().
• Schema-based Data Management
  • Define your data structure with the schema parameter during series creation, and use set_data_mapping() to specify how data properties map to chart coordinates. This enables organized data handling and makes it easier to implement progressive data patterns.
• Enhanced Sample Modification
  • Use alter_samples() to modify data points directly by index, or alter_samples_by_match() to target and update specific points. These methods allow precise edits without needing to replace the entire dataset.
• Progressive data patterns
  • Progressive data patterns can now be applied directly in the schema, supporting real-time and continuous data streaming scenarios.
• Property-specific data storage
  • Optimize memory and performance by configuring storage types per data property.

Other Improvements

• Simplified Scroll Strategies
  • A single set_scroll_strategy() method now handles all scroll behaviors. Choose from ‘scrolling’, ‘fitting’, ‘expansion’, or ‘fittingStepped’, and easily fine-tune with parameters like progressive=True, realtime=True, start=False, or end=True.
• Customizable point series borders
  • You can now customize point borders in ChartXY (Point, Point-Line, Spline, Step) and Polar (Point, Point-Line) series using the new set_point_stroke_style() method for better visual control.
• TextBox Auto-Dispose
  • TextBoxes can now automatically remove themselves when they exceed a specified portion of the viewport. Configure this with set_auto_dispose(mode, threshold) for cleaner, dynamic visuals.
• Removed series types
  • Some previous AreaSeries functionalities have been removed under ChartXY — specifically, the Bipolar, Negative, and Positive series types.
• Expanded data type support
  • The update adds compatibility for a wider range of non-native Python data types, improving flexibility and integration with external data sources.