H2O Wave Python driver for integration with arbitrary python web frameworks.
Project description
H2O Lightwave
H2O Lightwave is a lightweight, pure-Python version of H2O Wave that can be embedded in popular async web frameworks like FastAPI, Starlette, etc.
In other words, H2O Lightwave works without the Wave server.
The integration consists of 2 steps:
- Add Wave's web assets directory to your framework's static file handler.
- Add a WebSocket handler, and use
wave_serve()to connect Wave to your web UI.
That's it. You can now render UI elements using pure Python. Lightwave aims to be as minimal as possible and only provides:
- A simple way to render your UI.
- A simple way of getting the UI inputs (like button clicks, dropdown values etc.)
- Minimal state management.
Nothing more, nothing less.
Example FastAPI integration:
from fastapi import FastAPI, WebSocket, WebSocketDisconnect
from fastapi.staticfiles import StaticFiles
from h2o_lightwave import Q, ui, wave_serve
from h2o_lightwave_web import web_directory
# Lightwave callback function.
async def serve(q: Q):
# Paint our UI on the first page visit.
if not q.client.initialized:
# Create a local state.
q.client.count = 0
# Add a "card" with a text and a button
q.page['hello'] = ui.form_card(box='1 1 2 2', items=[
ui.text_xl('Hello world'),
ui.button(name='counter', label=f'Current count: {q.client.count}'),
])
q.client.initialized = True
# Handle counter button click.
if q.args.counter:
# Increment the counter.
q.client.count += 1
# Update the counter button.
q.page['hello'].items[1].button.label = f'Current count: {q.client.count}'
# Send the UI changes to the browser.
await q.page.save()
# Run: uvicorn hello_fastapi:app.
# FastAPI boilerplate.
app = FastAPI()
# FastAPI: WebSocket must be registered before index.html handler.
@app.websocket("/_s/")
async def ws(ws: WebSocket):
try:
await ws.accept()
await wave_serve(serve, ws.send_text, ws.receive_text)
await ws.close()
except WebSocketDisconnect:
print('Client disconnected')
app.mount("/", StaticFiles(directory=web_directory, html=True), name="/")
Installation
pip install "h2o-lightwave[web]"
Lightwave requires websockets to function properly. Not all libraries come with them out of the box so you might need to install them additionally. For example, Starlette & FastAPI requires
pip install websockets
to be able to expose websocket handlers. This might differ from framework to framework.
Widgets
All available widgets can be found here. We are working on separate docs for Lightwave.
Using Lightwave within an existing HTML page
Lightwave can also be used only for certain parts of your HTML pages, e.g. for charts. In addition to the integration steps above:
- Use the
get_web_filesfunction which HTML links to scripts and styles for you to inject into your existing HTML. - Render a
divwith an idwave-root(<div id='wave-root'></div>) into which you want Lightwave to render. - Render a parent container for
wave-rootthat hasposition: relativeand has some dimensions attached.
{# index_template.html #}
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Document</title>
<!-- Scripts and stylesheets required for Wave to work properly. -->
{{ wave_files }}
</head>
<style>
/* Must have position: relative and some size specified (e.g. height, flexbox, absolute positioning etc.). */
.wave-container {
position: relative;
height: 800px;
}
</style>
<!-- Websocket URL can be changed if needed. Defaults to "/_s/". -->
<body data-wave-socket-url="/custom_socket/">
<noscript>You need to enable JavaScript to run this app.</noscript>
<div class="wave-container">
<!-- Wave renders here. -->
<div id="wave-root"></div>
</div>
</body>
</html>
Configuration
By default, Lightwave tries to connect to websocket route at /_s/. This can be configured by adding a data-wave-socket-url attribute on the HTML body element (<body data-wave-socket-url='/my_socket_url/'>).
Links
- Website: https://wave.h2o.ai/
- Releases: https://pypi.org/project/h2o-wave/
- Code: https://github.com/h2oai/wave
- Issue tracker: https://github.com/h2oai/wave/issues
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