PyWry FAQs

Question 1

Can PyWry integrate with AI and large language models (LLMs)?

Accepted Answer

Yes, PyWry offers extensive AI and LLM integration, including a streaming chat widget with pluggable providers (e.g., OpenAI, Anthropic), Model Context Protocol (MCP) server support, and a dedicated Claude Code Plugin for advanced AI agent interactions.

Question 2

What output targets does PyWry support?

Accepted Answer

PyWry supports three main output targets: native desktop applications (via OS webviews and PyTauri), interactive Jupyter widgets (compatible with JupyterLab, VS Code, and Colab), and scalable web applications powered by a FastAPI server.

Question 3

How does PyWry compare to Electron or Qt for desktop application development?

Accepted Answer

Unlike Electron (which bundles a full Chromium browser) or Qt (which uses its own rendering engine), PyWry leverages OS-native webviews (like WebView2 on Windows, WKWebView on macOS, and WebKitGTK on Linux). This results in significantly lighter, more secure, and self-contained standalone executables that utilize unrestricted HTML/CSS/JS for UI.

Question 4

How does PyWry facilitate interactive data visualization and analytics?

Accepted Answer

PyWry provides seamless integration with popular data science tools. It can display Pandas DataFrames using AgGrid, render interactive Plotly charts, and even integrate advanced TradingView charts with comprehensive drawing tools and datafeed APIs, making it ideal for data-driven applications.

Question 5

What is PyWry and what is its primary purpose?

Accepted Answer

PyWry is a Python toolkit designed to create cross-platform applications and interactive UI experiences from a single API. Its primary purpose is to enable developers to build once and deploy to native desktop, web browsers, and Jupyter notebooks without significant code changes.

PyWry

PyWry

Key Features

Use Cases

Key Features

Use Cases