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Python

Blackbaud FE NXT Python Connector

SQL-based access to Blackbaud FE NXT from Python

Easily connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with Blackbaud FE NXT!

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CData Drivers now work with AI Coding tools

Python Connector Libraries for Blackbaud FE NXT Data Connectivity. Integrate Blackbaud FE NXT with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect Blackbaud FE NXT data with Python and any Python-based applications.

Features

Powerful metadata querying enables SQL-like access to non-database sources
Push down query optimization pushes SQL operations down to the server whenever possible, increasing performance
Client-side query execution engine, supports SQL-92 operations that are not available server-side
Connect to live Blackbaud FE NXT data, for real-time data access with the Blackbaud FE NXT Python Connectors
Full support for data aggregation and complex JOINs in SQL queries
Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the Blackbaud FE NXT Connector.

Specifications

Python Database API (DB-API) Modules for Blackbaud FE NXT .
Write SQL, get Blackbaud FE NXT data. Access Blackbaud FE NXT through standard Python Database Connectivity.
Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
Simple command-line based data exploration of Blackbaud FE NXT Accounts, Budgets, Projects, and more!
Full Unicode support for data, parameter, & metadata.

CData Python connectors in action!

Watch the video overview for a first hand-look at the powerful data integration capabilities included in the CData Python Connectors.

Watch the Python Connector Video Overview

Python connectivity with Blackbaud FE NXT

Full-featured and consistent SQL access to any supported data source through Python


Connecting to Blackbaud FE NXT with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Blackbaud FE NXT from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

  • Configure the connection properties to Blackbaud FE NXT
  • Query Blackbaud FE NXT to retrieve or update data
  • Connect your Blackbaud FE NXT data with Python data tools.


Connecting to Blackbaud FE NXT in Python

To connect to your data from Python, import the extension and create a connection:

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

import cdata.financialedgenxt as mod
conn = mod.connect("[email protected]; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM Accounts")
	
rs = cur.fetchall()
	
for row in rs:
print(row)
		
engine = create_engine("financialedgenxt///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM Accounts", engine)

df.plot()
plt.show()

Visualize Blackbaud FE NXT Data with pandas

The data-centric interfaces of the Blackbaud FE NXT Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

AI-assisted development with CData CLI

Build Blackbaud FE NXT integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Blackbaud FE NXT schema. No more guessing table names or column types—AI sees the same metadata in your Python Connectors.

Your AI Knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to Blackbaud FE NXT.

More Accurate, More Token-Efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools
Download CData CLI