Use Dash to Build Web Apps on NetSuite SuiteAnalytics 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 NetSuite SuiteAnalytics-connected web applications for NetSuite SuiteAnalytics data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing NetSuite SuiteAnalytics 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 NetSuite SuiteAnalytics 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 "NetSuite SuiteAnalytics" from the Add Connection panel

3. Enter the necessary authentication properties to connect to NetSuite SuiteAnalytics.

   Prerequisites

   Before you can connect to NetSuite SuiteAnalytics, you must set up SuiteAnalytics Connect in your NetSuite account:

   1. Enable the Connect Service feature.

      1. Ensure that your Account Administrator has enabled your Account and Role with the Connect Service feature.

      2. Navigate to Setup > Company > Enable Features.

      3. Click the Analytics tab and check the SuiteAnalytics Connect box.

   2. Add the SuiteAnalytics Connect permission to an existing Role, and note the Role ID for later.

   3. Find the Settings portlet on your home page and click Set Up SuiteAnalytics Connect, then click Your Configuration to view your service host and account ID. These settings map directly to the Server and Account Id properties.

   Add the NetSuite SuiteAnalytics Connection

   1. Open the Sources page of the Connect Cloud dashboard.

   2. Click Add Connection and select NetSuite SuiteAnalytics from the list of connectors.

   3. Enter a Connection Name of your choice.

   Authenticate to NetSuite SuiteAnalytics

   Set the following required properties:

   • Server: The Service Host value you found when setting up SuiteAnalytics Connect.

   • Account Id: The Account ID value you found when setting up SuiteAnalytics Connect.

   • Role Id: The internal ID of the login role you granted the SuiteAnalytics Connect permission.

   Next, choose one of the supported authentication methods:

   Basic authentication

   • User: The username you use to authenticate to your NetSuite account.

   • Password: The password associated with that account.

   Token-based authentication

   • Consumer Key and Consumer Secret: Generated when you create your integration record in NetSuite.

   • Token Key and Token Secret: The access token and secret generated for that integration.

   After you enter your credentials, click Save & Test to validate the connection.

   
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 NetSuite SuiteAnalytics 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 NetSuite SuiteAnalytics data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, SuiteAnalytics1).

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 AnnualRevenue, NumberOfEmployees "
    "FROM [SuiteAnalytics1].[SuiteAnalytics].[Account] "
    "WHERE Industry = 'Life Sciences'",
    conn,
)

conn.close()

Configure the App and Layout

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

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

trace = go.Bar(x=df['AnnualRevenue'], y=df['NumberOfEmployees'], name='AnnualRevenue')

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='NetSuite SuiteAnalytics Account 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 NetSuite SuiteAnalytics data.

python suiteanalytics-dash.py

More Information and Free Trial

Now you can build interactive Dash web apps on live NetSuite SuiteAnalytics data using the CData Connect AI Python SDK. For more information on connecting to NetSuite SuiteAnalytics (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live NetSuite SuiteAnalytics 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 AnnualRevenue, NumberOfEmployees "
    "FROM [SuiteAnalytics1].[SuiteAnalytics].[Account] "
    "WHERE Industry = 'Life Sciences'",
    conn,
)

conn.close()

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

trace = go.Bar(x=df['AnnualRevenue'], y=df['NumberOfEmployees'], name='AnnualRevenue')

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='NetSuite SuiteAnalytics Account Data', barmode='stack'),
            },
        ),
    ],
    className="container",
)

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