Bokeh server APIs

It can be useful to embed the Bokeh Server in a larger Tornado application, or a Jupyter notebook, and use the already existing Tornado IOloop. Here is the basis for integration of Bokeh in such a scenario:

from bokeh.server.server import Server

server = Server(
    bokeh_applications,  # list of Bokeh applications
    io_loop=loop,        # Tornado IOLoop
    **server_kwargs      # port, num_procs, etc.
)

# start timers and services and immediately return
server.start()

If your server should honor the same environment variables and configuration files used by bokeh serve (for example, BOKEH_AUTH_MODULE, BOKEH_SSL_CERTFILE, BOKEH_SIGN_SESSIONS), use the from_settings() factory method instead:

from bokeh.server.server import Server

server = Server.from_settings(
    bokeh_applications,  # list of Bokeh applications
    io_loop=loop,        # Tornado IOLoop
    **server_kwargs
)

server.start()

You can also create and control an IOLoop directly. This can be useful when creating standalone “normal” Python scripts that serve Bokeh apps or embedding a Bokeh application in a framework like Flask or Django without having to run a separate Bokeh server process. You can find some examples of this technique in the examples directory:

• examples/server/api/flask_embed.py

• examples/server/api/notebook_embed.ipynb

• examples/server/api/standalone_embed.py

• examples/server/api/tornado_embed.py

Also note that every command line argument for bokeh serve has a corresponding keyword argument for Server. For instance, using the --allow-websocket-origin command line argument is equivalent to passing allow_websocket_origin as a parameter.

Connecting with bokeh.client

You can directly interact with the Bokeh server via a client API, which you can use to make modifications to Bokeh documents in existing sessions on a Bokeh server.

Typically, web browsers connect to the Bokeh server, but you can make a connection from Python by using the bokeh.client module.

This can be useful, for example, to make user-specific customizations to a Bokeh app that is embedded by another web framework, such as Flask or Django. In the following example, a Flask endpoint embeds a “sliders” app already running on the server but changes the plot title before passing the output to the user.

from flask import Flask, render_template

from bokeh.client import pull_session
from bokeh.embed import server_session

app = Flask(__name__)

@app.route('/', methods=['GET'])
def bkapp_page():

    with pull_session(url="http://localhost:5006/sliders") as session:

        # update or customize that session
        session.document.roots[0].children[1].title.text = "Special sliders for a specific user!"

        # generate a script to load the customized session
        script = server_session(session_id=session.id, url='http://localhost:5006/sliders')

        # use the script in the rendered page
        return render_template("embed.html", script=script, template="Flask")

if __name__ == '__main__':
    app.run(port=8080)