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Get the Report →Use Dash to Build to Web Apps on Oracle Sales Data
Create Python applications that use pandas and Dash to build Oracle Sales-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 Sales, the pandas module, and the Dash framework, you can build Oracle Sales-connected web applications for Oracle Sales data. This article shows how to connect to Oracle Sales with the CData Connector and use pandas and Dash to build a simple web app for visualizing Oracle Sales data.
With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Oracle Sales data in Python. When you issue complex SQL queries from Oracle Sales, the driver pushes supported SQL operations, like filters and aggregations, directly to Oracle Sales and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Oracle Sales Data
Connecting to Oracle Sales 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.
Oracle Sales uses Basic authentication over SSL; after setting the following connection properties, you are ready to connect:
- Username: Set this to the user name that you use to log into your Oracle Cloud service.
- Password: Set this to your password.
- HostURL: Set this to the Web address (URL) of your Oracle Cloud service.
After installing the CData Oracle Sales Connector, follow the procedure below to install the other required modules and start accessing Oracle Sales 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 Sales 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.oraclesalescloud as mod import plotly.graph_objs as go
You can now connect with a connection string. Use the connect function for the CData Oracle Sales Connector to create a connection for working with Oracle Sales data.
cnxn = mod.connect("HostURL=https://my.host.oraclecloud.com; Username=abc123; Password=abcdef;")
Execute SQL to Oracle Sales
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 OptyId, Name FROM Opportunities WHERE CreatedBy = 'Jack'", 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-oraclesalescloudedataplot' 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 Sales data and configure the app layout.
trace = go.Bar(x=df.OptyId, y=df.Name, name='OptyId') 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 Sales Opportunities 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 Sales data.
python oraclesalescloud-dash.py
Free Trial & More Information
Download a free, 30-day trial of the CData Python Connector for Oracle Sales to start building Python apps with connectivity to Oracle Sales 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.oraclesalescloud as mod import plotly.graph_objs as go cnxn = mod.connect("HostURL=https://my.host.oraclecloud.com; Username=abc123; Password=abcdef;") df = pd.read_sql("SELECT OptyId, Name FROM Opportunities WHERE CreatedBy = 'Jack'", cnxn) app_name = 'dash-oraclesalesclouddataplot' 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.OptyId, y=df.Name, name='OptyId') 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 Sales Opportunities Data', barmode='stack') }) ], className="container") if __name__ == '__main__': app.run_server(debug=True)