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Python Connector Libraries for Workday Data Connectivity. Integrate Workday with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

Use Dash to Build to Web Apps on Workday Data



Create Python applications that use pandas and Dash to build Workday-connected web apps.

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

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

Connecting to Workday Data

Connecting to Workday 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.

To connect, there are three pieces of information required: Authentication, API URL, and WSDL URL.

Authentication

To authenticate, specify your User and Password. Note that you must append your Tenant to your User separated by an '@' character. For instance, if you normally log in with 'geraldg' and your Tenant is 'mycompany_mc1', then your User should be specified as 'geraldg@mycompany_mc1'.

API URL

The API URL may be specified either directly via APIURL, or it may be constructed from the Tenant, Service, and Host. The APIURL is constructed in the following format: <Host>/ccx/service/<Tenant>/<Service>.

WSDL URL

The WSDLURL may be specified in its entirety, or may be constructed from the Service and WSDLVersion connection properties. The WSDLURL is constructed in the following format: https://community.workday.com/sites/default/files/file-hosting/productionapi/<Service>/<WSDLVersion>/<Service>.wsdl

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

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

cnxn = mod.connect("User=myuser;Password=mypassword;Tenant=mycompany_gm1;Host=https://wd3-impl-services1.workday.com")

Execute SQL to Workday

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 Worker_Reference_WID, Legal_Name_Last_Name FROM Workers WHERE Legal_Name_Last_Name = 'Morgan'", 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-workdayedataplot'

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 Workday data and configure the app layout.

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 Extension + 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, 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 Workday data.

python workday-dash.py

Free Trial & More Information

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

cnxn = mod.connect("User=myuser;Password=mypassword;Tenant=mycompany_gm1;Host=https://wd3-impl-services1.workday.com")

df = pd.read_sql("SELECT Worker_Reference_WID, Legal_Name_Last_Name FROM Workers WHERE Legal_Name_Last_Name = 'Morgan'", cnxn)
app_name = 'dash-workdaydataplot'

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.Worker_Reference_WID, y=df.Legal_Name_Last_Name, name='Worker_Reference_WID')

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

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