Use Dash to Build Web Apps on OData Services 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 OData-connected web applications for OData services. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing OData services.
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.
About OData Data Integration
CData simplifies access and integration of live OData services data. Our customers leverage CData connectivity to:
- Access OData versions 2.0, 3.0, and 4.0, working with legacy services and the latest features and capabilities.
- Leverage advanced query options, including $filter, $select, and $expand, enhancing data retrieval from 3rd party tools.
- Use Server-side execution of aggregation and grouping to minimize data transfer and boost performance.
- Authenticate securely using a variety of schemes, including Azure AD, digest, negotiate, NTLM, OAuth, and more means secure authentication with every connection.
- Use SQL stored procedures to manage OData service entities - listing, creating, and removing associations between entities.
Customers use CData's solutions to regularly integrate their OData services with preferred tools, such as Power BI, MicroStrategy, or Tableau, and to replicate data from OData services to their databases or data warehouses.
Getting Started
Connect to OData in Connect AI
CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "OData" from the Add Connection panel
-
Enter the necessary authentication properties to connect to OData.
The User and Password properties, under the Authentication section, must be set to valid OData user credentials. In addition, specify a URL to a valid OData server organization root or OData services file.
- Click Save & Test
- 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.
- Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
- Give the PAT a name and click Create.

- 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 OData Services 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 OData services into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, OData1).
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 OrderName, Freight "
"FROM [OData1].[OData].[Orders] "
"WHERE ShipCity = 'New York'",
conn,
)
conn.close()
Configure the App and Layout
With the query results stored in a DataFrame, build a bar graph from the OData services and configure the app layout.
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['OrderName'], y=df['Freight'], name='OrderName')
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='OData Orders 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 OData services.
python odata-dash.py
More Information and Free Trial
Now you can build interactive Dash web apps on live OData services using the CData Connect AI Python SDK. For more information on connecting to OData (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live OData services 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 OrderName, Freight "
"FROM [OData1].[OData].[Orders] "
"WHERE ShipCity = 'New York'",
conn,
)
conn.close()
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['OrderName'], y=df['Freight'], name='OrderName')
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='OData Orders Data', barmode='stack'),
},
),
],
className="container",
)
if __name__ == '__main__':
app.run(debug=True)