pywry 2.0.0rc4

A lightweight and blazingly fast, cross-platform, WebView rendering engine and desktop UI toolkit for Python.

PyWry is a cross-platform rendering engine and desktop UI toolkit for Python. One API, three output targets:

• Native window — OS webview via PyTauri. Not Qt, not Electron. Use unrestricted HTML/CSS/JS.
• Jupyter widget — anywidget + FastAPI + WebSocket, works in JupyterLab, VS Code, and Colab.
• Browser tab — FastAPI server with Redis state backend for horizontal scaling.

Build Once, Render Anywhere: Prototype interactive data apps in a Jupyter Notebook, easily deploy them as web apps, and seamlessly compile them into secure, lightweight standalone desktop executables via pywry[freeze].

Installation

Python 3.10–3.14, virtual environment recommended.

pip install pywry

Extra	When to use
pip install 'pywry[notebook]'	Jupyter / anywidget integration
pip install 'pywry[auth]'	OAuth2 and keyring-backed auth support
pip install 'pywry[freeze]'	PyInstaller hook for standalone executables
pip install 'pywry[mcp]'	Model Context Protocol server support
pip install 'pywry[openai]'	OpenAIProvider integration
pip install 'pywry[anthropic]'	AnthropicProvider integration
pip install 'pywry[magentic]'	MagenticProvider integration
pip install 'pywry[all]'	Everything above

The chat UI itself is included in the base package. The provider extras only install optional third-party SDKs.

Linux only — install system webview dependencies first:

sudo apt-get install libwebkit2gtk-4.1-dev libgtk-3-dev libglib2.0-dev \
    libxkbcommon-x11-0 libxcb-icccm4 libxcb-image0 libxcb-keysyms1 \
    libxcb-randr0 libxcb-render-util0 libxcb-xinerama0 libxcb-xfixes0 \
    libxcb-shape0 libgl1 libegl1

Quick Start

from pywry import PyWry

app = PyWry()
app.show("Hello World!")
app.block()

Toolbar + callbacks

from pywry import PyWry, Toolbar, Button

app = PyWry()

def on_click(data, event_type, label):
    app.emit("pywry:set-content", {"selector": "h1", "text": "Clicked!"}, label)

app.show(
    "<h1>Hello</h1>",
    toolbars=[Toolbar(position="top", items=[Button(label="Click me", event="app:click")])],
    callbacks={"app:click": on_click},
)
app.block()

Pandas DataFrame → AgGrid

from pywry import PyWry
import pandas as pd

app = PyWry()
df = pd.DataFrame({"name": ["Alice", "Bob", "Carol"], "age": [30, 25, 35]})

def on_select(data, event_type, label):
    names = ", ".join(row["name"] for row in data["rows"])
    app.emit("pywry:alert", {"message": f"Selected: {names}"}, label)

app.show_dataframe(df, callbacks={"grid:row-selected": on_select})
app.block()

Plotly chart

from pywry import PyWry
import plotly.express as px

app = PyWry(theme="light")
fig = px.scatter(px.data.iris(), x="sepal_width", y="sepal_length", color="species")
app.show_plotly(fig)
app.block()

Features

• 18 toolbar components — Button, Select, MultiSelect, TextInput, SecretInput, SliderInput, RangeInput, Toggle, Checkbox, RadioGroup, TabGroup, Marquee, Modal, and more. All Pydantic models, 7 layout positions.
• Two-way events — app.emit() and app.on() bridge Python and JavaScript in both directions. Pre-wired Plotly and AgGrid events included.
• Theming — light/dark modes, 60+ CSS variables, hot reload during development.
• Security — token auth, CSP headers, SecuritySettings.strict() / .permissive() / .localhost() presets. SecretInput stores values server-side, never in HTML.
• Standalone executables — PyInstaller hook ships with pywry[freeze]. No .spec edits or --hidden-import flags required.
• MCP server — 25 tools, 8 skills, 20+ resources for AI agent integration.

MCP Server

pip install 'pywry[mcp]'
pywry mcp --transport stdio

See the MCP docs for Claude Desktop setup and tool reference.

Standalone Executables

pip install 'pywry[freeze]'
pyinstaller --windowed --name MyApp my_app.py

The output in dist/MyApp/ is fully self-contained. Target machines need no Python installation — only the OS webview (WebView2 on Windows 10 1803+, WKWebView on macOS, libwebkit2gtk on Linux).

Documentation

deeleeramone.github.io/PyWry

• Getting Started — installation, quick start, rendering paths
• Concepts — events, configuration, state, hot reload, RBAC
• Components — live previews for all toolbar components
• API Reference — auto-generated docs for every class and function
• MCP Server — AI agent integration

License

Apache 2.0 — see LICENSE.