Tutorial: A tornado server in Python
Perspective ships with a pre-built Tornado handler that makes integration with
tornado.websockets
extremely easy. This allows you to run an instance of
Perspective
on a server using Python, open a websocket to a Table
, and
access the Table
in JavaScript and through <perspective-viewer>
. All
instructions sent to the Table
are processed in Python, which executes the
commands, and returns its output through the websocket back to Javascript.
Python setup
Make sure Perspective and Tornado are installed!
pip install perspective-python tornado
To use the handler, we need to first have a Server
, a Client
and an instance
of a Table
:
import perspective
SERVER = perspective.Server()
CLIENT = SERVER.new_local_client()
Once the server has been created, create a Table
instance with a name. The
name that you host the table under is important — it acts as a unique accessor
on the JavaScript side, which will look for a Table hosted at the websocket with
the name you specify.
TABLE = client.table(data, name="data_source_one")
After the server and table setup is complete, create a websocket endpoint and
provide it a reference to PerspectiveTornadoHandler
. You must provide the
configuration object in the route tuple, and it must contain
"perspective_server"
, which is a reference to the Server
you just created.
from perspective.handlers.tornado import PerspectiveTornadoHandler
app = tornado.web.Application([
# ... other handlers ...
# Create a websocket endpoint that the client JavaScript can access
(r"/websocket", PerspectiveTornadoHandler, {"perspective_server": SERVER, "check_origin": True})
])
Optionally, the configuration object can also include check_origin
, a boolean
that determines whether the websocket accepts requests from origins other than
where the server is hosted. See
Tornado docs
for more details.
JavaScript setup
Once the server is up and running, you can access the Table you just hosted
using perspective.websocket
and open_table()
. First, create a client that
expects a Perspective server to accept connections at the specified URL:
import "@finos/perspective-viewer";
import "@finos/perspective-viewer-datagrid";
import perspective from "@finos/perspective";
const websocket = await perspective.websocket("ws://localhost:8888/websocket");
Next open the Table
we created on the server by name:
const table = await websocket.open_table("data_source_one");
table
is a proxy for the Table
we created on the server. All operations that
are possible through the JavaScript API are possible on the Python API as well,
thus calling view()
, schema()
, update()
etc. on const table
will pass
those operations to the Python Table
, execute the commands, and return the
result back to JavaScript. Similarly, providing this table
to a
<perspective-viewer>
instance will allow virtual rendering:
const viewer = document.createElement("perspective-viewer");
viewer.style.height = "500px";
document.body.appendChild(viewer);
await viewer.load(table);
perspective.websocket
expects a Websocket URL where it will send instructions.
When open_table
is called, the name to a hosted Table is passed through, and a
request is sent through the socket to fetch the Table. No actual Table
instance is passed inbetween the runtimes; all instructions are proxied through
websockets.
This provides for great flexibility — while Perspective.js
is full of
features, browser WebAssembly runtimes currently have some performance
restrictions on memory and CPU feature utilization, and the architecture in
general suffers when the dataset itself is too large to download to the client
in full.
The Python runtime does not suffer from memory limitations, utilizes Apache
Arrow internal threadpools for threading and parallel processing, and generates
architecture optimized code, which currently makes it more suitable as a
server-side runtime than node.js
.