How to Build an ETL App for Oracle Service Cloud 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 Python Connector for Oracle Service Cloud and the petl framework, you can build Oracle Service Cloud-connected applications and pipelines for extracting, transforming, and loading Oracle Service Cloud data. This article shows how to connect to Oracle Service Cloud with the CData Python Connector and use petl and pandas to extract, transform, and load Oracle Service Cloud data.

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

Connecting to Oracle Service Cloud Data

Connecting to Oracle Service Cloud 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 Basic Authentication

You must set the following to authenticate to Oracle Service Cloud:

• Url: The Url of the account to connect to.
• User: The username of the authenticating account.
• Password: The password of the authenticating account.

After installing the CData Oracle Service Cloud Connector, follow the procedure below to install the other required modules and start accessing Oracle Service Cloud 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 Oracle Service Cloud 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.oracleservicecloud as mod

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

cnxn = mod.connect("Url=https://abc.rightnowdemo.com;User=user;Password=password;")

Create a SQL Statement to Query Oracle Service Cloud

Use SQL to create a statement for querying Oracle Service Cloud. In this article, we read data from the Accounts entity.

sql = "SELECT Id, LookupName FROM Accounts WHERE DisplayOrder = '12'"

Extract, Transform, and Load the Oracle Service Cloud Data

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

Loading Oracle Service Cloud Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

In the following example, we add new rows to the Accounts table.

Adding New Rows to Oracle Service Cloud

table1 = [ ['Id','LookupName'], ['NewId1','NewLookupName1'], ['NewId2','NewLookupName2'], ['NewId3','NewLookupName3'] ]

etl.appenddb(table1, cnxn, 'Accounts')

With the CData Python Connector for Oracle Service Cloud, you can work with Oracle Service Cloud 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 Python Connector for Oracle Service Cloud to start building Python apps and scripts with connectivity to Oracle Service Cloud 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.oracleservicecloud as mod

cnxn = mod.connect("Url=https://abc.rightnowdemo.com;User=user;Password=password;")

sql = "SELECT Id, LookupName FROM Accounts WHERE DisplayOrder = '12'"

table1 = etl.fromdb(cnxn,sql)

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

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

table3 = [ ['Id','LookupName'], ['NewId1','NewLookupName1'], ['NewId2','NewLookupName2'], ['NewId3','NewLookupName3'] ]

etl.appenddb(table3, cnxn, 'Accounts')