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

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



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

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

Connecting to Oracle Financials Cloud Data

Connecting to Oracle Financials 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 ERP:

  • Url: The Url of the account to connect to. Typically, the URL of your Oracle Cloud service. For example, https://servername.fa.us2.oraclecloud.com.
  • User: The username of your account.
  • Password: The password of your account.

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

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

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

Execute SQL to Oracle Financials 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 InvoiceId, Amount FROM Invoices WHERE Supplier = 'CData Software'", 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-oracleerpedataplot'

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 Financials Cloud data and configure the app layout.

trace = go.Bar(x=df.InvoiceId, y=df.Amount, name='InvoiceId')

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 Financials Cloud Invoices 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 Financials Cloud data.

python oracleerp-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Oracle Financials Cloud to start building Python apps with connectivity to Oracle Financials 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.oracleerp 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 InvoiceId, Amount FROM Invoices WHERE Supplier = 'CData Software'", cnxn)
app_name = 'dash-oracleerpdataplot'

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.InvoiceId, y=df.Amount, name='InvoiceId')

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 Financials Cloud Invoices Data', barmode='stack')
		})
], className="container")

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