Ready to get started?

Download a free trial of the Oracle HCM Cloud Connector to get started:

 Download Now

Learn more:

Oracle HCM Cloud Icon Oracle HCM Cloud Python Connector

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

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



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

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

Connecting to Oracle HCM Cloud Data

Connecting to Oracle HCM 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 HCM Cloud:

  • Url: The Url of your account.
  • User: The user of your account.
  • Password: The password of your account.

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

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

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

Execute SQL to Oracle HCM 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 SiteId, SiteName FROM RecruitingCESites WHERE Language = 'English'", 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-oraclehcmedataplot'

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 HCM Cloud data and configure the app layout.

trace = go.Bar(x=df.SiteId, y=df.SiteName, name='SiteId')

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 HCM Cloud RecruitingCESites 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 HCM Cloud data.

python oraclehcm-dash.py

Free Trial & More Information

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

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

df = pd.read_sql("SELECT SiteId, SiteName FROM RecruitingCESites WHERE Language = 'English'", cnxn)
app_name = 'dash-oraclehcmdataplot'

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.SiteId, y=df.SiteName, name='SiteId')

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 HCM Cloud RecruitingCESites Data', barmode='stack')
		})
], className="container")

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