How to Visualize Halo Service Desk Data in Python with pandas

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 & Matplotlib modules, and the SQLAlchemy toolkit, you can build Halo Service Desk-connected Python applications and scripts for visualizing Halo Service Desk data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Halo Service Desk data, execute queries, and visualize the results.

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).

Follow the procedure below to install the required modules and start accessing Halo Service Desk through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize Halo Service Desk Data in Python

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

engine = create_engine("api:///?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 resultset in a DataFrame.

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

Visualize Halo Service Desk Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the Halo Service Desk data. The show method displays the chart in a new window.

df.plot(kind="bar", x="Id", y="InventoryNumber")
plt.show()

Free Trial & More Information

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

Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("api:///?Profile=C:\profiles\HaloServiceDesk.apip&AuthScheme=APIKey&ProfileSettings='APIKey=your_api_key&Domain=yourcompany.haloservicedesk.com'")
df = pandas.read_sql("SELECT Id, InventoryNumber FROM Assets WHERE ClientId = '1'", engine)

df.plot(kind="bar", x="Id", y="InventoryNumber")
plt.show()