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Use Dash to Build to Web Apps on Blackbaud FE NXT Data

The CData Python Connector for Blackbaud FE NXT enables you to create Python applications that use pandas and Dash to build Blackbaud FE NXT-connected web apps.

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, the pandas module, and the Dash framework, you can build Blackbaud FE NXT-connected web applications for Blackbaud FE NXT data. This article shows how to connect to Blackbaud FE NXT with the CData Connector and use pandas and Dash to build a simple web app for visualizing 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 pandas
pip install dash
pip install dash-daq

Visualize Blackbaud FE NXT Data in Python

Once the required modules and frameworks are installed, we are ready to build our web 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 os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.financialedgenxt as mod
import plotly.graph_objs as go

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")")

Execute SQL to Blackbaud FE NXT

Use the read_sql function from pandas to execute any SQL statement and store the result set in a DataFrame.

df = pd.read_sql("SELECT AccountId, AccountNumber FROM Accounts WHERE ModifiedBy = 'System'", cnxn)

Configure the Web App

With the query results stored in a DataFrame, we can begin configuring the web app, assigning a name, stylesheet, and title.

app_name = 'dash-financialedgenxtedataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'

Configure the Layout

The next step is to create a bar graph based on our Blackbaud FE NXT data and configure the app layout.

trace = go.Bar(x=df.AccountId, y=df.AccountNumber, name='AccountId')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Blackbaud FE NXT Accounts Data', barmode='stack')
		})
], className="container")

Set the App to Run

With the connection, app, and layout configured, we are ready to run the app. The last lines of Python code follow.

if __name__ == '__main__':
    app.run_server(debug=True)

Now, use Python to run the web app and a browser to view the Blackbaud FE NXT data.

python financialedgenxt-dash.py

Free Trial & More Information

Download a free, 30-day trial of the Blackbaud FE NXT Python Connector to start building Python apps with connectivity to Blackbaud FE NXT data. Reach out to our Support Team if you have any questions.



Full Source Code

import os
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import cdata.financialedgenxt as mod
import plotly.graph_objs as go

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

df = pd.read_sql("SELECT AccountId, AccountNumber FROM Accounts WHERE ModifiedBy = 'System'", cnxn)
app_name = 'dash-financialedgenxtdataplot'

external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']

app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = 'CData + Dash'
trace = go.Bar(x=df.AccountId, y=df.AccountNumber, name='AccountId')

app.layout = html.Div(children=[html.H1("CData Extension + Dash", style={'textAlign': 'center'}),
	dcc.Graph(
		id='example-graph',
		figure={
			'data': [trace],
			'layout':
			go.Layout(title='Blackbaud FE NXT Accounts Data', barmode='stack')
		})
], className="container")

if __name__ == '__main__':
    app.run_server(debug=True)