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()andapp.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), andDeepagentProvider(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.SecretInputstores 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.specedits or--hidden-importflags 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
- 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
Release Artifacts
Release bundles include CycloneDX SBOM files as sbom.xml and sbom.json.
These SBOM files are published with release artifacts rather than committed to repository root.
License
Apache 2.0 — see LICENSE.
1 maintainer
Release files for pywry 2.0.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pywry-2.0.6.tar.gz | 4.4 MB | Details |
Built distributions (wheels)
Total release size: 446.4 MB
Release files / pywry-2.0.6.tar.gz
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| Tags | Source |
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