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

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

Connecting to Zuora Data

Connecting to Zuora 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.

Zuora uses the OAuth standard to authenticate users. See the online Help documentation for a full OAuth authentication guide.

Configuring Tenant property

In order to create a valid connection with the provider you need to choose one of the Tenant values (USProduction by default) which matches your account configuration. The following is a list with the available options:

• USProduction: Requests sent to https://rest.zuora.com.
• USAPISandbox: Requests sent to https://rest.apisandbox.zuora.com"
• USPerformanceTest: Requests sent to https://rest.pt1.zuora.com"
• EUProduction: Requests sent to https://rest.eu.zuora.com"
• EUSandbox: Requests sent to https://rest.sandbox.eu.zuora.com"

Selecting a Zuora Service

Two Zuora services are available: Data Query and AQuA API. By default ZuoraService is set to AQuADataExport.

DataQuery

The Data Query feature enables you to export data from your Zuora tenant by performing asynchronous, read-only SQL queries. We recommend to use this service for quick lightweight SQL queries.

• The maximum number of input records per table after filters have been applied: 1,000,000
• The maximum number of output records: 100,000
• The maximum number of simultaneous queries submitted for execution per tenant: 5
• The maximum number of queued queries submitted for execution after reaching the limitation of simultaneous queries per tenant: 10
• The maximum processing time for each query in hours: 1
• The maximum size of memory allocated to each query in GB: 2
• The maximum number of indices when using Index Join, in other words, the maximum number of records being returned by the left table based on the unique value used in the WHERE clause when using Index Join: 20,000

AQuADataExport

AQuA API export is designed to export all the records for all the objects ( tables ). AQuA query jobs have the following limitations:

• If a query in an AQuA job is executed longer than 8 hours, this job will be killed automatically.
• The killed AQuA job can be retried three times before returned as failed.

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

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

cnxn = mod.connect("OAuthClientID=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;Tenant=USProduction;ZuoraService=DataQuery;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")

Execute SQL to Zuora

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 Id, BillingCity FROM Invoices WHERE BillingState = 'CA'", 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-zuoraedataplot'

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 Zuora data and configure the app layout.

trace = go.Bar(x=df.Id, y=df.BillingCity, name='Id')

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='Zuora 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 Zuora data.

python zuora-dash.py

Free Trial & More Information

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

cnxn = mod.connect("OAuthClientID=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;Tenant=USProduction;ZuoraService=DataQuery;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")

df = pd.read_sql("SELECT Id, BillingCity FROM Invoices WHERE BillingState = 'CA'", cnxn)
app_name = 'dash-zuoradataplot'

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.Id, y=df.BillingCity, name='Id')

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

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