Use Dash to Build Web Apps on ConstantContact Data via CData Connect AI
The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Connect AI Python SDK, the pandas module, and the Dash framework, you can build ConstantContact-connected web applications for ConstantContact data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing ConstantContact data.
The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so pandas can read query results directly from the SDK connection object. There is no driver to install per source: connect with a Personal Access Token and build your app.
Connect to ConstantContact in Connect AI
CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "ConstantContact" from the Add Connection panel
-
Enter the necessary authentication properties to connect to ConstantContact.
Start by setting the Profile connection property to the location of the ConstantContact Profile on disk (e.g. C:\profiles\ConstantContact.apip). Next, set the ProfileSettings connection property to the connection string for Profile (see below).
ConstantContact API Profile Settings
ConstantContact uses OAuth-based authentication.
First, register an OAuth application with ConstantContact. You can do so from the ConstantContact API Guide (https://v3.developer.constantcontact.com/api_guide/index.html), under "MyApplications" > "New Application". Your Oauth application will be assigned a client id (API Key) and you can generate a client secret (Secret).
After setting the following connection properties, you are ready to connect:
- AuthScheme: Set this to OAuth.
- InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
- OAuthClientId: Set this to the client_id that is specified in you app settings.
- OAuthClientSecret: Set this to the client_secret that is specified in you app settings.
- CallbackURL: Set this to the Redirect URI you specified in your app settings.
- Click Save & Test
- Navigate to the Permissions tab and update the user-based permissions.

Generate a Personal Access Token (PAT)
The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.
- Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
- Give the PAT a name and click Create.

- The PAT is only visible at creation, so copy it and store it securely.
Install Required Modules
Install the SDK (with the pandas extra), Dash, and Plotly using the pip utility:
pip install "cdata-connect-ai[full]" pip install dash pip install plotly
Build a Web App on ConstantContact Data in Python
Once the required modules are installed, you are ready to build the web app. Code snippets follow, but the full source code is available at the end of the article.
First, import the modules, then connect to Connect AI with your account email and PAT and read ConstantContact data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, API1).
import dash
from dash import dcc, html
import pandas as pd
import plotly.graph_objs as go
import cdata_connect_ai
conn = cdata_connect_ai.connect(
username="[email protected]",
password="<your_pat>",
)
df = pd.read_sql(
"SELECT Id, EmailAddress "
"FROM [API1].[API].[Contacts] "
"WHERE CompanyName = 'Acme, Inc.'",
conn,
)
conn.close()
Configure the App and Layout
With the query results stored in a DataFrame, build a bar graph from the ConstantContact data and configure the app layout.
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['Id'], y=df['EmailAddress'], name='Id')
app.layout = html.Div(
children=[
html.H1("CData Connect AI + Dash", style={'textAlign': 'center'}),
dcc.Graph(
id='example-graph',
figure={
'data': [trace],
'layout': go.Layout(title='ConstantContact Contacts Data', barmode='stack'),
},
),
],
className="container",
)
Set the App to Run
With the connection, app, and layout configured, you are ready to run the app.
if __name__ == '__main__':
app.run(debug=True)
Now, use Python to run the web app and a browser to view the ConstantContact data.
python api-dash.py
More Information and Free Trial
Now you can build interactive Dash web apps on live ConstantContact data using the CData Connect AI Python SDK. For more information on connecting to ConstantContact (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live ConstantContact data in Python.
Full Source Code
import dash
from dash import dcc, html
import pandas as pd
import plotly.graph_objs as go
import cdata_connect_ai
conn = cdata_connect_ai.connect(
username="[email protected]",
password="<your_pat>",
)
df = pd.read_sql(
"SELECT Id, EmailAddress "
"FROM [API1].[API].[Contacts] "
"WHERE CompanyName = 'Acme, Inc.'",
conn,
)
conn.close()
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['Id'], y=df['EmailAddress'], name='Id')
app.layout = html.Div(
children=[
html.H1("CData Connect AI + Dash", style={'textAlign': 'center'}),
dcc.Graph(
id='example-graph',
figure={
'data': [trace],
'layout': go.Layout(title='ConstantContact Contacts Data', barmode='stack'),
},
),
],
className="container",
)
if __name__ == '__main__':
app.run(debug=True)