Releasing LightningChart Python Trader 1.1

Introducing new product features and UX improvements.

Releasing new product features

In this version, LightningChart Python Trader introduces four new features: drawing tool pointer events, chart-level pointer events, value label controls, and data point management.

Drawing Tool Pointer Events

Drawing tools now support comprehensive pointer event handling, allowing for custom interactions and dynamic chart updates. All drawing tools can now respond to user interactions via Python callbacks. The available events are:

on_pointer_down(): Triggered when clicking on a drawing tool
on_pointer_up(): Triggered when releasing the mouse button
on_pointer_enter(): Triggered when the cursor enters the tool area
on_pointer_leave(): Triggered when the cursor exits the tool area
on_drawing_tool_moved(): Triggered when the tool position changes

Chart-Level Pointer Events

The charts now support pointer event tracking, which allows building custom interactions, tooltips, or analysis tools. The available events are:

on_pointer_down(): Triggered when clicking on a drawing tool
on_pointer_up(): Triggered when releasing the mouse button
on_pointer_move(): Triggered when the cursor moves

Value Label Controls

Fine-grained control over value labels allows customization of how the latest values are displayed for both price data and indicators. The new available controls are:

show_value_labels(bool): Show/hide all value labels
set_latest_value_label_type(str): Control the latest price label display

LightningChart-Python-Trader-1.1-Value-Label-Controls

Data Point Management

The new data point management methods provide users with programmatic access to the chart’s data and automatic data-point limiting for real-time applications. All the data points containing full OHLC information, date-time stamps, and optional volume / open interest fields can now be retrieved using the get_data_point_array() function.

The chart also includes a built-in mechanism for automatically dropping old data points in streaming scenarios to maintain performance. This can be enabled or disabled via enable_data_point_limit(bool) and configured with set_data_point_limit(int) to control the maximum number of data points kept in memory.

Library Improvements

LightningChart Python Trader 1.1 also prioritizes improving the developer experience and overall UX. Here are some of the enhacements:

Axis Interaction Controls: Customize mouse button behavior for each axis independently, choosing from DragZoom, Pan, RectangleZoom, ZoomToEnd, or Off to control panning and zooming.

Enhanced Menu Customization: Enhanced menu controls allow you to hide specific UI elements for cleaner, custom interfaces. For example, hiding indicator controls or X/Y axis dropdown action buttons.

Drawing Tool Position Tracking: Get the current positions of drawing tools programmatically via get_position() for analysis, synchronization, or state management.

Enhanced Event System: All event methods now support both subscription and unsubscription patterns for flexible event management.

DateTime Handling Improvements: Behind the scenes, datetime conversion has been completely rewritten to ensure proper handling of date objects throughout the library, fixing edge cases with CSV loading and data manipulation.

New Visual Customization Methods

We have introduced new styling methods to provide greater control over how the chart looks.

LC-Python-Trader-1.1-Visual-Customization

The customization methods include:

chart.set_splitter_color("#FF6600"): #Orange splitter lines
chart.set_border_color('#00FF00’):#Green border
chart.set_axis_color('#0000FF’): #Blue axes
chart.show_chart_border(True)
chart.set_zooming_sensitivity(1.5)

Get LightningChart Python Trader 1.1

Getting started with LightningChart Python Trader is easy. We’ve compiled a comprehensive documentation and 26+ examples that can be easily downloaded as ZIP files (requires a license key to run) to help you get started visualizing financial data in Python.

Request 7-day free trial

See more news

React Charting Performance

Jul 22, 2026 | Blog, JavaScript

Here's a scenario that plays out across development teams every few months. Someone builds a React dashboard, picks Recharts or Victory because they're popular, the devs love them, and the first demo looks great. Then the dataset gets bigger. Or the data starts...

Javascript Charting Library comparison 2026

Jul 22, 2026 | Blog, JavaScript

Every year someone publishes a listicle of JavaScript charting libraries. They screenshot a demo, note the GitHub stars, paste in the npm install command, and call it a day. Then you follow their recommendation, get six months into your project, and discover that your...

Visualizing 10 Million Data Points in the Browser (2026): The Technical Deep-Dive

Jul 22, 2026 | Blog, Tutorials

Ten Million Data Points in the Browser: How WebGL Makes Mass Datasets Interactive Ten million data points. That number used to mean a database problem, not a front-end problem. Now research teams want to explore it interactively in a browser. Trading desks want...

Elliott Wave Theory in Trading

Jul 14, 2026 | Blog, Trader

Financial markets often appear chaotic, but many traders believe that price movements follow recurring patterns driven by human psychology. One of the most influential approaches based on this idea is the Elliott Wave Theory. Developed nearly a century ago, it remains one of the most widely studied methods of technical analysis.