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Use Dash to Build to Web Apps on MailChimp Data

The CData Python Connector for MailChimp enables you to create Python applications that use pandas and Dash to build MailChimp-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 MailChimp, the pandas module, and the Dash framework, you can build MailChimp-connected web applications for MailChimp data. This article shows how to connect to MailChimp with the CData Connector and use pandas and Dash to build a simple web app for visualizing MailChimp data.

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

Connecting to MailChimp Data

Connecting to MailChimp 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.

You can set the APIKey to the key you generate in your account settings, or, instead of providing your APIKey, you can use the OAuth standard to authenticate the application. OAuth can be used to enable other users to access their own data. To authenticate using OAuth, you will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL by registering an app with MailChimp.

See the "Getting Started" chapter in the help documentation for a guide to using OAuth.

After installing the CData MailChimp Connector, follow the procedure below to install the other required modules and start accessing MailChimp 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 MailChimp 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.mailchimp as mod
import plotly.graph_objs as go

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

cnxn = mod.connect("APIKey=myAPIKey;")

Execute SQL to MailChimp

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 Name, Stats_AvgSubRate FROM Lists WHERE Contact_Country = 'US'", 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-mailchimpedataplot'

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 MailChimp data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.Stats_AvgSubRate, name='Name')

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='MailChimp Lists 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 MailChimp data.

python mailchimp-dash.py

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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.mailchimp as mod
import plotly.graph_objs as go

cnxn = mod.connect("APIKey=myAPIKey;")

df = pd.read_sql("SELECT Name, Stats_AvgSubRate FROM Lists WHERE Contact_Country = 'US'", cnxn)
app_name = 'dash-mailchimpdataplot'

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.Name, y=df.Stats_AvgSubRate, name='Name')

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='MailChimp Lists Data', barmode='stack')
		})
], className="container")

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