Use Dash to Build to Web Apps on Oracle Sales 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 Oracle Sales, the pandas module, and the Dash framework, you can build Oracle Sales-connected web applications for Oracle Sales data. This article shows how to connect to Oracle Sales with the CData Connector and use pandas and Dash to build a simple web app for visualizing Oracle Sales data.

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

Connecting to Oracle Sales Data

Connecting to Oracle Sales 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 Sales uses Basic authentication over SSL; after setting the following connection properties, you are ready to connect:

• Username: Set this to the user name that you use to log into your Oracle Cloud service.
• Password: Set this to your password.
• HostURL: Set this to the Web address (URL) of your Oracle Cloud service.

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

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

cnxn = mod.connect("HostURL=https://my.host.oraclecloud.com; Username=abc123; Password=abcdef;")

Execute SQL to Oracle Sales

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 OptyId, Name FROM Opportunities WHERE CreatedBy = 'Jack'", 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-oraclesalescloudedataplot'

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 Sales data and configure the app layout.

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

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 Sales Opportunities 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 Sales data.

python oraclesalescloud-dash.py

Free Trial & More Information

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

cnxn = mod.connect("HostURL=https://my.host.oraclecloud.com; Username=abc123; Password=abcdef;")

df = pd.read_sql("SELECT OptyId, Name FROM Opportunities WHERE CreatedBy = 'Jack'", cnxn)
app_name = 'dash-oraclesalesclouddataplot'

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

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 Sales Opportunities Data', barmode='stack')
		})
], className="container")

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