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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 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.
You must set the following to authenticate to Oracle HCM Cloud:
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.
Use the pip utility to install the required modules and frameworks:
pip install pandas pip install dash pip install dash-daq
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;")
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)
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'
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")
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👁 Oracle HCM Cloud data in a Dash web app (Salesforce is shown).
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.
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)
Download a Community License of the Oracle HCM Cloud Connector to get started:
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👁 Oracle HCM Cloud IconPython Connector Libraries for Oracle HCM Cloud Data Connectivity. Integrate Oracle HCM Cloud with popular Python tools like Pandas, SQLAlchemy, Dash & petl.