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

Use Dash to Build to Web Apps on Oracle Service Cloud Data



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

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

Connecting to Oracle Service Cloud Data

Connecting to Oracle Service Cloud 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.

Using Basic Authentication

You must set the following to authenticate to Oracle Service Cloud:

  • Url: The Url of the account to connect to.
  • User: The username of the authenticating account.
  • Password: The password of the authenticating account.

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

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

cnxn = mod.connect("Url=https://abc.rightnowdemo.com;User=user;Password=password;")

Execute SQL to Oracle Service Cloud

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 Id, LookupName FROM Accounts WHERE DisplayOrder = '12'", 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-oracleservicecloudedataplot'

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 Service Cloud data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.LookupName, name='Id')

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 Service Cloud Accounts 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 Service Cloud data.

python oracleservicecloud-dash.py

Free Trial & More Information

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

cnxn = mod.connect("Url=https://abc.rightnowdemo.com;User=user;Password=password;")

df = pd.read_sql("SELECT Id, LookupName FROM Accounts WHERE DisplayOrder = '12'", cnxn)
app_name = 'dash-oracleserviceclouddataplot'

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.Id, y=df.LookupName, name='Id')

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 Service Cloud Accounts Data', barmode='stack')
		})
], className="container")

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