Use Dash to Build to Web Apps on Halo Service Desk Data

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas module, and the Dash framework, you can build Halo Service Desk-connected web applications for Halo Service Desk data. This article shows how to connect to Halo Service Desk with the CData Connector and use pandas and Dash to build a simple web app for visualizing Halo Service Desk data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Halo Service Desk data in Python. When you issue complex SQL queries from Halo Service Desk, the driver pushes supported SQL operations, like filters and aggregations, directly to Halo Service Desk and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Halo Service Desk Data

Connecting to Halo Service Desk data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Start by setting the Profile connection property to the location of the HaloServiceDesk Profile on disk (e.g. C:\profiles\HaloServiceDesk.apip). Next, set the ProfileSettings connection property to the connection string for HaloServiceDesk (see below).

HaloServiceDesk API Profile Settings

HaloServiceDesk uses API key authentication. You can find or create API keys in HaloServiceDesk under Administration > Integrations > Halo API.

Set the following connection properties to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to the API key from your HaloServiceDesk account.
• Domain: Set this to the hostname of your HaloServiceDesk instance (e.g. yourcompany.haloservicedesk.com).

After installing the CData Halo Service Desk Connector, follow the procedure below to install the other required modules and start accessing Halo Service Desk through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install pandas
pip install dash
pip install dash-daq

Visualize Halo Service Desk Data in Python

Once the required modules and frameworks are installed, we are ready to build our web app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.api as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Halo Service Desk Connector to create a connection for working with Halo Service Desk data.

cnxn = mod.connect("Profile=C:\profiles\HaloServiceDesk.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;Domain=yourcompany.haloservicedesk.com';")

Execute SQL to Halo Service Desk

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT Id, InventoryNumber FROM Assets WHERE ClientId = '1'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-apiedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our Halo Service Desk data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.InventoryNumber, name='Id')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Halo Service Desk Assets Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
    app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the Halo Service Desk data.

python api-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps with connectivity to Halo Service Desk data. Reach out to our Support Team if you have any questions.

Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.api as mod
import plotly.graph_objs as go

cnxn = mod.connect("Profile=C:\profiles\HaloServiceDesk.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;Domain=yourcompany.haloservicedesk.com';")

df = pd.read_sql("SELECT Id, InventoryNumber FROM Assets WHERE ClientId = '1'", cnxn)
app_name = 'dash-apidataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.Id, y=df.InventoryNumber, name='Id')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Halo Service Desk Assets Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)