pywry 2.0.0rc7

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

Core extras:

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[sqlite]'	Encrypted SQLite state backend (SQLCipher)
pip install 'pywry[all]'	Everything above

Chat provider extras:

Extra	When to use
pip install 'pywry[openai]'	OpenAIProvider (OpenAI SDK)
pip install 'pywry[anthropic]'	AnthropicProvider (Anthropic SDK)
pip install 'pywry[magentic]'	MagenticProvider (any magentic-supported LLM)
pip install 'pywry[acp]'	StdioProvider (Agent Client Protocol subprocess)
pip install 'pywry[deepagent]'	DeepagentProvider (LangChain Deep Agents — includes MCP adapters and ACP)

The chat UI itself is included in the base package. Provider extras only install the matching third-party SDK.

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

• Toolbar components — Button, Select, MultiSelect, TextInput, SecretInput, SliderInput, RangeInput, Toggle, Checkbox, RadioGroup, TabGroup, Marquee, Modal, and more. All Pydantic models; position them around the content edges or inside the chart area.
• Two-way events — app.emit() and app.on() bridge Python and JavaScript in both directions. Pre-wired Plotly and AgGrid events included.
• Chat — streaming chat widget with threads, slash commands, artifacts, and pluggable providers: OpenAIProvider, AnthropicProvider, MagenticProvider, CallbackProvider, StdioProvider (ACP subprocess), and DeepagentProvider (LangChain Deep Agents).
• TradingView charts — extended Lightweight Charts integration with a full drawing surface (trendlines, fib tools, text annotations, price notes, brushes), pluggable datafeed API, UDF adapter for external quote servers, streaming bar updates, compare overlays, compare-derivative indicators (Spread / Ratio / Sum / Product / Correlation), savable layouts, and a themeable settings panel.
• Theming — light / dark / system modes, themeable via --pywry-* CSS variables, hot reload during development.
• Security — token auth, CSP headers, SecuritySettings.strict() / .permissive() / .localhost() presets. SecretInput stores values server-side, never in HTML.
• State backends — in-memory (default), Redis (multi-worker), or SQLite with SQLCipher encryption at rest.
• Standalone executables — PyInstaller hook ships with pywry[freeze]. No .spec edits or --hidden-import flags required.
• MCP server — drive widgets, charts, and dashboards from any Model Context Protocol client (Claude Desktop, Claude Code, Cursor, etc.).

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.