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Extract, Transform, and Load ServiceNow Data in Python

The CData Python Connector for ServiceNow enables you to create ETL applications and pipelines for ServiceNow data in Python with petl.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for ServiceNow and the petl framework, you can build ServiceNow-connected applications and pipelines for extracting, transforming, and loading ServiceNow data. This article shows how to connect to ServiceNow with the CData Python Connector and use petl and pandas to extract, transform, and load ServiceNow data.

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

Connecting to ServiceNow Data

Connecting to ServiceNow 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.

ServiceNow uses the OAuth 2.0 authentication standard. To authenticate using OAuth, you will need to register an OAuth app with ServiceNow to obtain the OAuthClientId and OAuthClientSecret connection properties. In addition to the OAuth values, you will need to specify the Instance, Username, and Password connection properties.

See the "Getting Started" chapter in the help documentation for a guide on connecting to ServiceNow.

After installing the CData ServiceNow Connector, follow the procedure below to install the other required modules and start accessing ServiceNow 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 ServiceNow 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.servicenow as mod

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

cnxn = mod.connect("OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;Username=MyUsername;Password=MyPassword;Instance=MyInstance;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query ServiceNow

Use SQL to create a statement for querying ServiceNow. In this article, we read data from the incident entity.

sql = "SELECT sys_id, priority FROM incident WHERE category = 'request'"

Extract, Transform, and Load the ServiceNow Data

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

Loading ServiceNow Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

With the CData Python Connector for ServiceNow, you can work with ServiceNow 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 ServiceNow Python Connector to start building Python apps and scripts with connectivity to ServiceNow 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.servicenow as mod

cnxn = mod.connect("OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;Username=MyUsername;Password=MyPassword;Instance=MyInstance;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT sys_id, priority FROM incident WHERE category = 'request'"

table1 = etl.fromdb(cnxn,sql)

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

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