Use Dash to Build Web Apps on Zuora Data via CData Connect AI

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Connect AI Python SDK, the pandas module, and the Dash framework, you can build Zuora-connected web applications for Zuora data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing Zuora data.

The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so pandas can read query results directly from the SDK connection object. There is no driver to install per source: connect with a Personal Access Token and build your app.

Connect to Zuora in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Zuora" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Zuora.

   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.

   Limitations
   • 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:

   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.
   
4. Click Save & Test
5. Navigate to the Permissions tab and update the user-based permissions.

Generate a Personal Access Token (PAT)

The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.

1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The PAT is only visible at creation, so copy it and store it securely.

Install Required Modules

Install the SDK (with the pandas extra), Dash, and Plotly using the pip utility:

pip install "cdata-connect-ai[full]"
pip install dash
pip install plotly

Build a Web App on Zuora Data in Python

Once the required modules are installed, you are ready to build the web app. Code snippets follow, but the full source code is available at the end of the article.

First, import the modules, then connect to Connect AI with your account email and PAT and read Zuora data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, Zuora1).

import dash
from dash import dcc, html
import pandas as pd
import plotly.graph_objs as go
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

df = pd.read_sql(
    "SELECT Id, BillingCity "
    "FROM [Zuora1].[Zuora].[Invoices] "
    "WHERE BillingState = 'CA'",
    conn,
)

conn.close()

Configure the App and Layout

With the query results stored in a DataFrame, build a bar graph from the Zuora data and configure the app layout.

app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'

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

app.layout = html.Div(
    children=[
        html.H1("CData Connect AI + 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, you are ready to run the app.

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

Now, use Python to run the web app and a browser to view the Zuora data.

python zuora-dash.py

More Information and Free Trial

Now you can build interactive Dash web apps on live Zuora data using the CData Connect AI Python SDK. For more information on connecting to Zuora (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live Zuora data in Python.

Full Source Code

import dash
from dash import dcc, html
import pandas as pd
import plotly.graph_objs as go
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

df = pd.read_sql(
    "SELECT Id, BillingCity "
    "FROM [Zuora1].[Zuora].[Invoices] "
    "WHERE BillingState = 'CA'",
    conn,
)

conn.close()

app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'

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

app.layout = html.Div(
    children=[
        html.H1("CData Connect AI + 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(debug=True)