Use Dash to Build to Web Apps on Oracle Eloqua Reporting Data

Jerod Johnson
Jerod Johnson
Senior Technology Evangelist
Create Python applications that use pandas and Dash to build Oracle Eloqua Reporting-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 Oracle Eloqua Reporting, the pandas module, and the Dash framework, you can build Oracle Eloqua Reporting-connected web applications for Oracle Eloqua Reporting data. This article shows how to connect to Oracle Eloqua Reporting with the CData Connector and use pandas and Dash to build a simple web app for visualizing Oracle Eloqua Reporting data.

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

Connecting to Oracle Eloqua Reporting Data

Connecting to Oracle Eloqua Reporting 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.

Oracle Eloqua Reporting supports the following authentication methods:

  • Basic authentication (User and Password)
  • OAuth 2.0 code grant flow
  • OAuth 2.0 password grant flow

Basic Authentication (User and Password)

To perform authentication with a user and password, specify these properties:

  • AuthScheme: Basic.
  • Company: The company name associated with your Oracle Eloqua Reporting account.
  • User: Your login account name.
  • Password: Your login password.

OAuth Authentication (Code Grant Flow)

To authenticate with the OAuth code grant flow, you must set AuthScheme to OAuth and create a custom OAuth application. For information about how to create a custom OAuth application, see the Help documentation.

Then set the following properties:

  • InitiateOAuth: GETANDREFRESH. Used to automatically get and refresh the OAuthAccessToken.
  • OAuthClientId: The client Id assigned when you registered your application.
  • OAuthClientSecret: The client secret that was assigned when you registered your application.
  • CallbackURL: The redirect URI that was defined when you registered your application.

When you connect, the driver opens Oracle Eloqua Reporting's OAuth endpoint in your default browser. Log in and grant permissions to the application. When the access token expires, the driver refreshes it automatically.

OAuth Authentication (Password Grant Flow)

With the OAuth password grant flow, you can use your OAuth application's credentials alongside your user credentials to authenticate without the need to grant permission manually via a browser prompt. You must create an OAuth app (see the Help documentation) to use this authentication method.

Set the following properties:

  • AuthScheme: OAuthPassword
  • Company: The company's unique identifier.
  • User: Your login account name.
  • Password: Your login password.
  • OAuthClientId: The client Id assigned when you registered your custom OAuth application.
  • OAuthClientSecret: The client secret assigned when you registered your custom OAuth application.

After installing the CData Oracle Eloqua Reporting Connector, follow the procedure below to install the other required modules and start accessing Oracle Eloqua Reporting 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 Reporting 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.oracleeloquareporting 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 Reporting Connector to create a connection for working with Oracle Eloqua Reporting data.

cnxn = mod.connect("AuthScheme=Basic;User=user;Password=password;Company=MyCompany;")

Execute SQL to Oracle Eloqua Reporting

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 ,  FROM  WHERE  = ''", 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-oracleeloquareportingedataplot'

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 Reporting data and configure the app layout.

trace = go.Bar(x=df., y=df., 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 Reporting  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 Reporting data.

python oracleeloquareporting-dash.py

Free Trial & More Information

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

cnxn = mod.connect("AuthScheme=Basic;User=user;Password=password;Company=MyCompany;")

df = pd.read_sql("SELECT ,  FROM  WHERE  = ''", cnxn)
app_name = 'dash-oracleeloquareportingdataplot'

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., y=df., 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 Reporting  Data', barmode='stack')
		})
], className="container")

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

Ready to get started?

Download a free trial of the Oracle Eloqua Reporting Connector to get started:

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Learn more:

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Python Connector Libraries for Oracle Eloqua Reporting Data Connectivity. Integrate Oracle Eloqua Reporting with popular Python tools like Pandas, SQLAlchemy, Dash & petl.