A simple bokeh server example

bokeh_server_skeleton.py

from typing import Callable
from bokeh.server.server import Server
from bokeh.document import Document
from bokeh.models import Div, ColumnDataSource
from bokeh.plotting import figure
import pandas as pd
import sklearn.datasets as toy_data


def create_application(doc):
    # website titles
    doc.title = "Bokeh Skeleton"
    doc.add_root(Div(text="<b>Bokeh Skeleton</b>"))
    # data
    iris = toy_data.load_iris()
    df = pd.DataFrame(data=iris.data, columns=iris.feature_names)
    df['label'] = iris.target
    df['label_name'] = [iris.target_names[i] for i in iris.target]
    cds = ColumnDataSource(data=df)
    # visualization
    plot = figure(width=300, height=300)
    col_x = iris.feature_names[0]
    col_y = iris.feature_names[1]
    print(f"plotting {col_x} against {col_y}")
    renderer = plot.circle(x=col_x, y=col_y, source=cds, radius=2, radius_units="screen")
    doc.add_root(plot)


def start_server(setup_callable: Callable[[Document], None]):
    server = Server(setup_callable)
    # start timers and services and immediately return
    server.start()
    server.io_loop.add_callback(server.show, "/")
    server.io_loop.start()

if __name__ == '__main__':
    start_server(create_application)

requirements (pip install):

bokeh
pandas
scikit-learn

run in IDE or via CLI

python bokeh_server_skeleton.py