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

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

Connecting to Blackbaud FE NXT Data

Connecting to Blackbaud FE NXT 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.

Blackbaud Financial Edge NXT uses the OAuth authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties.

See the Getting Started guide in the CData driver documentation for more information.

After installing the CData Blackbaud FE NXT Connector, follow the procedure below to install the other required modules and start accessing Blackbaud FE NXT 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 Blackbaud FE NXT 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.financialedgenxt as mod

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

cnxn = mod.connect("SubscriptionKey=MySubscriptionKey;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Create a SQL Statement to Query Blackbaud FE NXT

Use SQL to create a statement for querying Blackbaud FE NXT. In this article, we read data from the Accounts entity.

sql = "SELECT AccountId, AccountNumber FROM Accounts WHERE ModifiedBy = 'System'"

Extract, Transform, and Load the Blackbaud FE NXT Data

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

Loading Blackbaud FE NXT Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

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

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

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

Adding New Rows to Blackbaud FE NXT

table1 = [ ['AccountId','AccountNumber'], ['NewAccountId1','NewAccountNumber1'], ['NewAccountId2','NewAccountNumber2'], ['NewAccountId3','NewAccountNumber3'] ]

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

With the CData Python Connector for Blackbaud FE NXT, you can work with Blackbaud FE NXT 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 Blackbaud FE NXT to start building Python apps and scripts with connectivity to Blackbaud FE NXT 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.financialedgenxt as mod

cnxn = mod.connect("SubscriptionKey=MySubscriptionKey;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

sql = "SELECT AccountId, AccountNumber FROM Accounts WHERE ModifiedBy = 'System'"

table1 = etl.fromdb(cnxn,sql)

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

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

table3 = [ ['AccountId','AccountNumber'], ['NewAccountId1','NewAccountNumber1'], ['NewAccountId2','NewAccountNumber2'], ['NewAccountId3','NewAccountNumber3'] ]

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