Use Dash to Build Web Apps on Smartsheet 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 Smartsheet-connected web applications for Smartsheet data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing Smartsheet 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.
About Smartsheet Data Integration
CData provides the easiest way to access and integrate live data from Smartsheet. Customers use CData connectivity to:
- Read and write attachments, columns, comments and discussions.
- View the data in individuals cells, report on cell history, and more.
- Perform Smartsheet-specific actions like deleting or downloading attachments, creating, copying, deleting, or moving sheets, and moving or copying rows to another sheet.
Users frequently integrate Smartsheet with analytics tools such as Tableau, Crystal Reports, and Excel. Others leverage our tools to replicate Smartsheet data to databases or data warehouses.
Getting Started
Connect to Smartsheet 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 "Smartsheet" from the Add Connection panel
-
Enter the necessary authentication properties to connect to Smartsheet.
Smartsheet uses the OAuth authentication standard. To authenticate using OAuth, register an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties.
However, for testing purposes you can instead use the Personal Access Token you get when you create an application; set this to the OAuthAccessToken connection property.
- 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 Smartsheet 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 Smartsheet data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, Smartsheet1).
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 TaskName, Progress "
"FROM [Smartsheet1].[Smartsheet].[Sheet_Event_Plan_Budget] "
"WHERE Assigned = 'Ana Trujilo'",
conn,
)
conn.close()
Configure the App and Layout
With the query results stored in a DataFrame, build a bar graph from the Smartsheet data and configure the app layout.
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['TaskName'], y=df['Progress'], name='TaskName')
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='Smartsheet Sheet_Event_Plan_Budget 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 Smartsheet data.
python smartsheet-dash.py
More Information and Free Trial
Now you can build interactive Dash web apps on live Smartsheet data using the CData Connect AI Python SDK. For more information on connecting to Smartsheet (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live Smartsheet 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 TaskName, Progress "
"FROM [Smartsheet1].[Smartsheet].[Sheet_Event_Plan_Budget] "
"WHERE Assigned = 'Ana Trujilo'",
conn,
)
conn.close()
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['TaskName'], y=df['Progress'], name='TaskName')
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='Smartsheet Sheet_Event_Plan_Budget Data', barmode='stack'),
},
),
],
className="container",
)
if __name__ == '__main__':
app.run(debug=True)