How to create a custom plot with zoom in Dear PyGui?

Use the plotting API from ImPlot integration; start with the demo code or documentation examples to add plots with zoom and pan functionality, as shown in the gallery with real-time graphing.

Dear PyGui vs Tkinter: which is better for high-performance apps?

Dear PyGui excels in performance with GPU acceleration for dynamic interfaces, while Tkinter is more established but slower for real-time updates. Choose Dear PyGui for data-intensive visualizations.

Can I deploy a Dear PyGui app as a standalone executable?

Yes, but it requires bundling dependencies and ensuring GPU support; tools like PyInstaller can be used, though deployment might be more complex due to the C++ backend and graphics requirements.

Is Dear PyGui suitable for building 2D games?

Yes, the canvas API allows custom drawing for simple 2D games, as demonstrated in the gallery with examples like Tetris and snake, but it's not a full game engine like Pygame.

What are the system requirements for Dear PyGui on Raspberry Pi?

Requires Raspberry Pi 4 with OpenGL ES support; the README lists it as a supported platform, but performance may vary compared to desktop systems with dedicated GPUs.

How to handle asynchronous functions in Dear PyGui?

Dear PyGui supports asynchronous operations through its stable operation features; refer to the documentation or demo for examples using callbacks and threading to avoid blocking the UI.

Open-Awesome

dearpygui

MITC++v2.3.1

A fast, GPU-accelerated GUI framework for Python with modern themes, plotting, and node editing.

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15.5k stars786 forks0 contributors

What is dearpygui?

Dear PyGui is a fast and powerful graphical user interface toolkit for Python that uses GPU-based rendering and an immediate mode design to create high-performance applications. It solves the need for modern, responsive GUIs in Python with minimal dependencies, offering features like advanced plotting, a node editor, and extensive theming.

Target Audience

Python developers building desktop applications, data visualization tools, scientific interfaces, or internal tools that require a modern, performant GUI.

Value Proposition

Developers choose Dear PyGui for its exceptional performance due to GPU acceleration, its rich feature set including plotting and node editing, and its cross-platform support—all while maintaining a simple Python API.

Overview

Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies

Use Cases

Best For

Creating real-time data visualization dashboards with high-frequency updates
Building internal tools and utilities with custom interactive interfaces
Developing node-based editors for visual programming or workflow design
Prototyping GUI applications quickly with a modern look and feel
Creating scientific or engineering applications requiring advanced plotting
Making lightweight 2D games or interactive simulations using the canvas API

Not Ideal For

Projects targeting web or mobile deployment, as Dear PyGui is desktop-only and requires GPU acceleration
Applications needing native platform UI components or strict OS design guidelines, due to its custom rendering approach
Teams requiring extensive pre-built widgets or a large ecosystem of plugins, compared to mature frameworks like Qt
Environments without GPU support or where minimal dependencies are critical, such as headless servers

Pros & Cons

Pros

GPU-Accelerated Performance

Leverages C/C++ backend and GPU-based rendering to handle over 1 million data points at 60 fps, ideal for real-time data visualization, as highlighted in the features.

Advanced Plotting and Node Editor

Includes built-in plotting with zoom/pan support and a node editor for visual workflows, demonstrated in the gallery with examples like stem plots and node-based interfaces.

Cross-Platform with Modern Theming

Runs on Windows, Linux, macOS, and Raspberry Pi with complete theme control, allowing for contemporary looks without platform restrictions, as shown in the themes screenshot.

Built-in Developer Tools

Offers theme inspector, runtime metrics, and debugger for easier development, mentioned in the features to aid in debugging and optimization.

Cons

Immediate Mode Learning Curve

The immediate mode paradigm, while efficient, differs from retained mode GUIs, which can be confusing for developers accustomed to frameworks like Tkinter or PyQt.

Limited Widget Library

Has a smaller set of pre-built widgets compared to established frameworks, and the README notes reliance on extensions like ImPlot and imnodes for advanced features.

GPU Dependency Issues

Performance hinges on GPU availability, which may cause problems on systems without dedicated graphics or in virtualized environments, limiting portability.

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