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

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Build interactive Dash web apps on live Epicor Kinetic data using pandas and the CData Connect AI Python SDK.

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 Epicor Kinetic-connected web applications for Epicor Kinetic data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing Epicor Kinetic 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 Epicor Kinetic 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. Adding a Connection
  3. Select "Epicor Kinetic" from the Add Connection panel
  4. Selecting a data source
  5. Enter the necessary authentication properties to connect to Epicor Kinetic.

    To successfully connect to your ERP instance, you must specify the following connection properties:

    • Url:the URL of the server hosting your ERP instance. For example, https://myserver.EpicorSaaS.com
    • ERPInstance: the name of your ERP instance.
    • User: the username of your account.
    • Password: the password of your account.
    • Service: the service you want to retrieve data from. For example, BaqSvc.

    In addition, you may also set the optional connection properties:

    • ApiKey: An optional key that may be required for connection to some services depending on your account configuration.
    • ApiVersion: Defaults to v1. May be set to v2 to use the newer Epicor API.
    • Company: Required if you set the ApiVersion to v2.
    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update the user-based permissions. Updating 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. Creating a new PAT
  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 Epicor Kinetic 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 Epicor Kinetic data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, EpicorERP1).

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 CustNum, Company "
    "FROM [EpicorERP1].[EpicorERP].[Customers] "
    "WHERE CompanyName = 'CompanyName'",
    conn,
)

conn.close()

Configure the App and Layout

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

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

trace = go.Bar(x=df['CustNum'], y=df['Company'], name='CustNum')

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='Epicor Kinetic Customers 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 Epicor Kinetic data.

python epicorerp-dash.py
The Dash web app running in a browser (Salesforce is shown)

More Information and Free Trial

Now you can build interactive Dash web apps on live Epicor Kinetic data using the CData Connect AI Python SDK. For more information on connecting to Epicor Kinetic (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live Epicor Kinetic 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 CustNum, Company "
    "FROM [EpicorERP1].[EpicorERP].[Customers] "
    "WHERE CompanyName = 'CompanyName'",
    conn,
)

conn.close()

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

trace = go.Bar(x=df['CustNum'], y=df['Company'], name='CustNum')

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='Epicor Kinetic Customers Data', barmode='stack'),
            },
        ),
    ],
    className="container",
)

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

Ready to get started?

Learn more about CData Connect AI or sign up for free trial access:

Free Trial