Use Dash to Build Web Apps on Workday 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 Workday-connected web applications for Workday data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing Workday 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.

Getting Started

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Connect to Workday 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 "Workday" from the Add Connection panel

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

   To connect to Workday, users need to find the Tenant and BaseURL and then select their API type.

   Obtaining the BaseURL and Tenant

   To obtain the BaseURL and Tenant properties, log into Workday and search for "View API Clients." On this screen, you'll find the Workday REST API Endpoint, a URL that includes both the BaseURL and Tenant.

   The format of the REST API Endpoint is: https://domain.com/subdirectories/mycompany, where:

   • https://domain.com/subdirectories/ is the BaseURL.
   • mycompany (the portion of the url after the very last slash) is the Tenant.
   For example, in the REST API endpoint https://wd3-impl-services1.workday.com/ccx/api/v1/mycompany, the BaseURL is https://wd3-impl-services1.workday.com and the Tenant is mycompany.

   Using ConnectionType to Select the API

   The value you use for the ConnectionType property determines which Workday API you use. See our Community Article for more information on Workday connectivity options and best practices.

   API	ConnectionType Value
   WQL	WQL
   Reports as a Service	Reports
   REST	REST
   SOAP	SOAP

   
   

   Authentication

   Your method of authentication depends on which API you are using.

   • WQL, Reports as a Service, REST: Use OAuth authentication.
   • SOAP: Use Basic or OAuth authentication.

   See the Help documentation for more information on configuring OAuth with Workday.

   
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 Workday 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 Workday data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, Workday1).

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 Worker_Reference_WID, Legal_Name_Last_Name "
    "FROM [Workday1].[Workday].[Workers] "
    "WHERE Legal_Name_Last_Name = 'Morgan'",
    conn,
)

conn.close()

Configure the App and Layout

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

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

trace = go.Bar(x=df['Worker_Reference_WID'], y=df['Legal_Name_Last_Name'], name='Worker_Reference_WID')

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='Workday Workers 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 Workday data.

python workday-dash.py

More Information and Free Trial

Now you can build interactive Dash web apps on live Workday data using the CData Connect AI Python SDK. For more information on connecting to Workday (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live Workday 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 Worker_Reference_WID, Legal_Name_Last_Name "
    "FROM [Workday1].[Workday].[Workers] "
    "WHERE Legal_Name_Last_Name = 'Morgan'",
    conn,
)

conn.close()

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

trace = go.Bar(x=df['Worker_Reference_WID'], y=df['Legal_Name_Last_Name'], name='Worker_Reference_WID')

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='Workday Workers Data', barmode='stack'),
            },
        ),
    ],
    className="container",
)

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