Use Dash to Build to Web Apps on Oracle Eloqua Data

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Eloqua, the pandas module, and the Dash framework, you can build Oracle Eloqua-connected web applications for Oracle Eloqua data. This article shows how to connect to Oracle Eloqua with the CData Connector and use pandas and Dash to build a simple web app for visualizing Oracle Eloqua data.

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

Connecting to Oracle Eloqua Data

Connecting to Oracle Eloqua 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.

There are two authentication methods available for connecting to Oracle Eloqua: Login and OAuth. The Login method requires you to have the Company, User, and Password of the user.

If you do not have access to the username and password or do not wish to require them, you can use OAuth authentication. OAuth is better suited for allowing other users to access their own data. Using login credentials is better suited for accessing your own data.

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

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

cnxn = mod.connect("User=user;Password=password;Company=CData;")

Execute SQL to Oracle Eloqua

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, ActualCost FROM Campaign WHERE ShipCity = 'New York'", 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-oracleeloquaedataplot'

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 Oracle Eloqua data and configure the app layout.

trace = go.Bar(x=df.Name, y=df.ActualCost, 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='Oracle Eloqua Campaign 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 Oracle Eloqua data.

python oracleeloqua-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Eloqua to start building Python apps with connectivity to Oracle Eloqua 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.oracleeloqua as mod
import plotly.graph_objs as go

cnxn = mod.connect("User=user;Password=password;Company=CData;")

df = pd.read_sql("SELECT Name, ActualCost FROM Campaign WHERE ShipCity = 'New York'", cnxn)
app_name = 'dash-oracleeloquadataplot'

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.ActualCost, 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='Oracle Eloqua Campaign Data', barmode='stack')
		})
], className="container")

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