How to Build an ETL App for Halo Service Desk Data in Python with CData

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 and the petl framework, you can build Halo Service Desk-connected applications and pipelines for extracting, transforming, and loading Halo Service Desk data. This article shows how to connect to Halo Service Desk with the CData Python Connector and use petl and pandas to extract, transform, and load 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 petl
pip install pandas

Build an ETL App for Halo Service Desk Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL 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 petl as etl
import pandas as pd
import cdata.api as mod

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';")

Create a SQL Statement to Query Halo Service Desk

Use SQL to create a statement for querying Halo Service Desk. In this article, we read data from the Assets entity.

sql = "SELECT Id, InventoryNumber FROM Assets WHERE ClientId = '1'"

Extract, Transform, and Load the Halo Service Desk Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the Halo Service Desk data. In this example, we extract Halo Service Desk data, sort the data by the InventoryNumber column, and load the data into a CSV file.

Loading Halo Service Desk Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'InventoryNumber')

etl.tocsv(table2,'assets_data.csv')

With the CData API Driver for Python, you can work with Halo Service Desk data just like you would with any database, including direct access to data in ETL packages like petl.

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 petl as etl
import pandas as pd
import cdata.api as mod

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

sql = "SELECT Id, InventoryNumber FROM Assets WHERE ClientId = '1'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'InventoryNumber')

etl.tocsv(table2,'assets_data.csv')