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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 ServiceDesk Plus-connected Python applications and scripts for visualizing ServiceDesk Plus data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to ServiceDesk Plus data, execute queries, and visualize the results.
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 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.
ServiceDeskPlus uses Zoho OAuth 2.0 for secure authentication. To set up OAuth access:
After setting the following connection properties, you are ready to 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;
Follow the procedure below to install the required modules and start accessing ServiceDesk Plus through Python objects.
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
You can now connect with a connection string. Use the create_engine function to create an Engine for working with ServiceDesk Plus data.
engine = create_engine("api:///?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")
Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.
df = pandas.read_sql("SELECT , FROM AnnouncementComments WHERE AnnouncementId = '12345'", engine)
With the query results stored in a DataFrame, use the plot function to build a chart to display the ServiceDesk Plus data. The show method displays the chart in a new window.
df.plot(kind="bar", x="", y="") plt.show()👁 ServiceDesk Plus data in a Python plot (Salesforce is shown).
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.
import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin
engine = create_engine("api:///?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")
df = pandas.read_sql("SELECT , FROM AnnouncementComments WHERE AnnouncementId = '12345'", engine)
df.plot(kind="bar", x="", y="")
plt.show()
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