How to Build an ETL App for ServiceDesk Plus 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 ServiceDesk Plus-connected applications and pipelines for extracting, transforming, and loading ServiceDesk Plus data. This article shows how to connect to ServiceDesk Plus with the CData Python Connector and use petl and pandas to extract, transform, and load ServiceDesk Plus data.

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

Connecting to ServiceDesk Plus Data

Connecting to ServiceDesk Plus 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.

Using OAuth Authentication

ServiceDeskPlus uses Zoho OAuth 2.0 for secure authentication. To set up OAuth access:

1. Register your application in the Zoho Developer Console at https://api-console.zoho.com
2. Configure your redirect URI to match your application setup
3. Note your Client ID and Client Secret from the application settings

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to OAuth.
• OAuthClientId: Set this to your Zoho application Client ID.
• OAuthClientSecret: Set this to your Zoho application Client Secret.
• Scope: Set this to the required ServiceDeskPlus permissions (default includes read access to requests, problems, assets, and projects).
• Domain: Set this to your ServiceDeskPlus domain
• Portal: Set this to your ServiceDeskPlus portal

Example Connection String

Profile=C:\profiles\ServiceDeskPlus.apip;ProfileSettings="Portal=itdesk;Domain=.in;Scope=SDPOnDemand.requests.READ SDPOnDemand.problems.READ SDPOnDemand.assets.READ SDPOnDemand.projects.READ";AuthScheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;

After installing the CData ServiceDesk Plus Connector, follow the procedure below to install the other required modules and start accessing ServiceDesk Plus 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 ServiceDesk Plus 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 ServiceDesk Plus Connector to create a connection for working with ServiceDesk Plus data.

cnxn = mod.connect("Profile=C:\profiles\ServiceDeskPlus.apip;ProfileSettings="Portal=itdesk;Domain=.in;Scope=SDPOnDemand.requests.READ SDPOnDemand.problems.READ SDPOnDemand.assets.READ SDPOnDemand.projects.READ";AuthScheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;")

Create a SQL Statement to Query ServiceDesk Plus

Use SQL to create a statement for querying ServiceDesk Plus. In this article, we read data from the AnnouncementComments entity.

sql = "SELECT ,  FROM AnnouncementComments WHERE AnnouncementId = '12345'"

Extract, Transform, and Load the ServiceDesk Plus Data

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

Loading ServiceDesk Plus Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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

With the CData API Driver for Python, you can work with ServiceDesk Plus 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 ServiceDesk Plus 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\ServiceDeskPlus.apip;ProfileSettings="Portal=itdesk;Domain=.in;Scope=SDPOnDemand.requests.READ SDPOnDemand.problems.READ SDPOnDemand.assets.READ SDPOnDemand.projects.READ";AuthScheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;")

sql = "SELECT ,  FROM AnnouncementComments WHERE AnnouncementId = '12345'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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