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Get the Report →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).
About Workday Data Integration
CData provides the easiest way to access and integrate live data from Workday. Customers use CData connectivity to:
- Access the tables and datasets you create in Prism Analytics Data Catalog, working with the native Workday data hub without compromising the fidelity of your Workday system.
- Access Workday Reports-as-a-Service to surface data from departmental datasets not available from Prism and datasets larger than Prism allows.
- Access base data objects with WQL, REST, or SOAP, getting more granular, detailed access but with the potential need for Workday admins or IT to help craft queries.
Users frequently integrate Workday with analytics tools such as Tableau, Power BI, and Excel, and leverage our tools to replicate Workday data to databases or data warehouses. Access is secured at the user level, based on the authenticated user's identity and role.
For more information on configuring Workday to work with CData, refer to our Knowledge Base articles: Comprehensive Workday Connectivity through Workday WQL and Reports-as-a-Service & Workday + CData: Connection & Integration Best Practices.
Getting Started
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 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.
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.
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;BaseURL=https://wd3-impl-services1.workday.com;ConnectionType=WQL;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt")")
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;BaseURL=https://wd3-impl-services1.workday.com;ConnectionType=WQL;InitiateOAuth=GETANDREFRESH;OAuthSettingsLocation=/PATH/TO/OAuthSettings.txt") 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)