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

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

Connecting to Oracle Data

Connecting to Oracle 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.

To connect to Oracle, you'll first need to update your PATH variable and ensure it contains a folder location that includes the native DLLs. The native DLLs can be found in the lib folder inside the installation directory. Once you've done this, set the following to connect:

• Port: The port used to connect to the server hosting the Oracle database.
• User: The user Id provided for authentication with the Oracle database.
• Password: The password provided for authentication with the Oracle database.
• Service Name: The service name of the Oracle database.

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

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

cnxn = mod.connect("User=myuser;Password=mypassword;Server=localhost;Port=1521;")

Execute SQL to Oracle

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 CompanyName, City FROM Customers WHERE Country = 'US'", 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-oracleociedataplot'

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 data and configure the app layout.

trace = go.Bar(x=df.CompanyName, y=df.City, name='CompanyName')

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 Customers 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 data.

python oracleoci-dash.py

Free Trial & More Information

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

cnxn = mod.connect("User=myuser;Password=mypassword;Server=localhost;Port=1521;")

df = pd.read_sql("SELECT CompanyName, City FROM Customers WHERE Country = 'US'", cnxn)
app_name = 'dash-oracleocidataplot'

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.CompanyName, y=df.City, name='CompanyName')

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

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