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Use Dash to Build to Web Apps on Email Data

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

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

Connecting to Email Data

Connecting to Email 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.

The User and Password properties, under the Authentication section, must be set to valid credentials. The Server must be specified to retrieve emails and the SMTPServer must be specified to send emails.

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

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

cnxn = mod.connect("User=username@gmail.com;Password=password;Server=imap.gmail.com;Port=993;SMTP Server=smtp.gmail.com;SMTP Port=465;SSL Mode=EXPLICIT;Protocol=IMAP;Mailbox=Inbox;")

Execute SQL to Email

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 Mailbox, RecentMessagesCount FROM Mailboxes WHERE Mailbox = 'Spam'", 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-emailedataplot'

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 Email data and configure the app layout.

trace = go.Bar(x=df.Mailbox, y=df.RecentMessagesCount, name='Mailbox')

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='Email Mailboxes 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 Email data.

python email-dash.py

Free Trial & More Information

Download a free, 30-day trial of the Email Python Connector to start building Python apps with connectivity to Email 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.email as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=username@gmail.com;Password=password;Server=imap.gmail.com;Port=993;SMTP Server=smtp.gmail.com;SMTP Port=465;SSL Mode=EXPLICIT;Protocol=IMAP;Mailbox=Inbox;")

df = pd.read_sql("SELECT Mailbox, RecentMessagesCount FROM Mailboxes WHERE Mailbox = 'Spam'", cnxn)
app_name = 'dash-emaildataplot'

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.Mailbox, y=df.RecentMessagesCount, name='Mailbox')

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='Email Mailboxes Data', barmode='stack')
		})
], className="container")

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