Launching a dashboard

A dashboard may be launched directly from the command line, using the `bokeh serve command line utility, or from a Python session or Jupyter notebook.

From the command line

The most common use case is to launch the dashboard from the command line using the serialdashboard command. Its usage (which can also be ascertained by executing serialdashboard --help on the command line) is as follows.


serialdashboard [OPTIONS]

--port INTEGER

port at localhost for serving dashboard (default 5006)

--browser TEXT

browser to use for dashboard (defaults to OS default)

--baudrate INTEGER

baud rate of serial connection (default 115200)

--maxcols INTEGER

maximum number of columns of data coming off of the board (default 10)

--delimiter TEXT

delimiter of data coming off of the board (default comma)

--columnlabels TEXT

labels for columns using delimiter specified with –delimiter flag (default is none)

--timecolumn TEXT

column (zero-indexed) of incoming data that specifies time (default none)

--timeunits TEXT

units of incoming time data (default ms)

--rollover INTEGER

number of data points to be shown on a plot for each column (default 400)

--glyph TEXT

which glyphs to display in the plotter; either lines, dots, or both (default lines)

--inputtype TEXT

whether input is ascii or bytes (default ascii)

--fileprefix TEXT

prefix of output files

--daqdelay INTEGER

approximate delay in milliseconds for data acquisition from the board (default 20)

--streamdelay INTEGER

delay in milliseconds between updates of the plotter and monitor (default 90)

--portsearchdelay INTEGER

delay in milliseconds for checks of serial devices (default 1000)


Show this message and exit.

The --port and --browser flags determine at which port and in which browser the dashboard is to live. Once the dashboard is launched, these cannot be changed.

The --daqdelay, --streamdelay and --portsearchdelay flags also cannot be changed once the dashboard is launched. The values controlled by all other flags can be adjusted from within the dashboard; the flags serve only to populate the initial settings. This can be convenient if the dashboard is being used for a project with known properties. For example, it is convenient to launch a dashboard controlling and Arduino board with the sample sketch (described here) using

serialdashboard --columnlabels "time (ms),signal,sine wave" --maxcols 3 --timecolumn 0

From Python

From an instance of Python or IPython, you can launch the serial dashboard with

import serial_dashboard

The serial_dashboard.launch() function has the same keyword arguments as the flags for the command line interface, above (with the exception of help). For example, to launch a dashboard with the sample sketch, one would use

serial_dashboard.launch(columnlabels="time (ms),signal,sine wave", maxcols=3, timecolumn=0)

From within a Jupyter notebook

A dashboard may live within a Jupyter notebook. To enable this, use the function. (You will need to have jupyter_bokeh installed.)

import serial_dashboard

dashboard_app =

It you want the same defaults as in the above example, use

Using bokeh serve

Many users serve Bokeh-based apps using the bokeh serve command line tool. To launch a dashboard this way, you need to make a script per the specification of the bokeh serve tool. Such a script is as follows.

import bokeh.plotting
import serial_dashboard

app =


Then, to launch the app, save the script in a file (say, named and do the following on the command line.

bokeh serve --show