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

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

Connecting to Anaplan Data

Connecting to Anaplan 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.

Authenticating to Anaplan

The driver supports authenticating with Basic, Certificate, or OAuth. In every case, set Region to the region where your Anaplan account data is hosted (e.g., US1, which is the default).

Using Basic Authentication

Set AuthScheme to Basic, then supply your Anaplan User and Password. If your workspace uses single sign-on (SSO), you must be assigned as an Exception User to use Basic authentication.

Using Certificate Authentication

Set AuthScheme to Certificate, then supply the Certificate, CertificateType, and PrivateKey properties (and the matching CertificatePassword / PrivateKeyPassword if either is encrypted). The certificate must be a CA-issued X.509 certificate registered with your Anaplan tenant administrator.

Using OAuth Authentication

Register a custom OAuth application in Anaplan, then set the following properties:

• OAuthClientId: The client Id assigned when you registered your custom OAuth application.
• OAuthClientSecret: The client secret assigned when you registered your custom OAuth application.
• CallbackURL: The redirect URI defined when you registered your application.
• InitiateOAuth: Set to GETANDREFRESH to have the driver manage the OAuth token exchange and refresh automatically.

See the Getting Started chapter of the help documentation for a guide to creating a custom OAuth app and using OAuth.

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

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

cnxn = mod.connect("OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=your_callback_url;Region=US1;InitiateOAuth=GETANDREFRESH;")

Execute SQL to Anaplan

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 Region, Product FROM Sales WHERE Value = '100'", 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-anaplanedataplot'

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 Anaplan data and configure the app layout.

trace = go.Bar(x=df.Region, y=df.Product, name='Region')

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='Anaplan Sales 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 Anaplan data.

python anaplan-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackURL=your_callback_url;Region=US1;InitiateOAuth=GETANDREFRESH;")

df = pd.read_sql("SELECT Region, Product FROM Sales WHERE Value = '100'", cnxn)
app_name = 'dash-anaplandataplot'

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.Region, y=df.Product, name='Region')

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

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