Use Dash to Build Web Apps on IBM Cloud Object Storage 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 IBM Cloud Object Storage-connected web applications for IBM Cloud Object Storage data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing IBM Cloud Object Storage 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.
Connect to IBM Cloud Object Storage 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 "IBM Cloud Object Storage" from the Add Connection panel
-
Enter the necessary authentication properties to connect to IBM Cloud Object Storage.
Register a New Instance of Cloud Object Storage
If you do not already have Cloud Object Storage in your IBM Cloud account, follow the procedure below to install an instance of SQL Query in your account:
- Log in to your IBM Cloud account.
- Navigate to the page, choose a name for your instance and click Create. You will be redirected to the instance of Cloud Object Storage you just created.
Connecting using OAuth Authentication
There are certain connection properties you need to set before you can connect. You can obtain these as follows:
API Key
To connect with IBM Cloud Object Storage, you need an API Key. You can obtain this as follows:
- Log in to your IBM Cloud account.
- Navigate to the Platform API Keys page.
- On the middle-right corner click "Create an IBM Cloud API Key" to create a new API Key.
- In the pop-up window, specify the API Key name and click "Create". Note the API Key as you can never access it again from the dashboard.
Cloud Object Storage CRN
If you have multiple accounts, specify the CloudObjectStorageCRN explicitly. To find the appropriate value, you can:
- Query the Services view. This will list your IBM Cloud Object Storage instances along with the CRN for each.
- Locate the CRN directly in IBM Cloud. To do so, navigate to your IBM Cloud Dashboard. In the Resource List, Under Storage, select your Cloud Object Storage resource to get its CRN.
Connecting to Data
You can now set the following to connect to data:
- InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
- ApiKey: Set this to your API key which was noted during setup.
- CloudObjectStorageCRN (Optional): Set this to the cloud object storage CRN you want to work with. While the connector attempts to retrieve this automatically, specifying this explicitly is recommended if you have more than Cloud Object Storage account.
When you connect, the connector completes the OAuth process.
- Extracts the access token and authenticates requests.
- Saves OAuth values in OAuthSettingsLocation to be persisted across connections.
- 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 IBM Cloud Object Storage 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 IBM Cloud Object Storage data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, IBMCloudObjectStorage1).
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 Key, Etag "
"FROM [IBMCloudObjectStorage1].[IBMCloudObjectStorage].[Objects] "
"WHERE Bucket = 'someBucket'",
conn,
)
conn.close()
Configure the App and Layout
With the query results stored in a DataFrame, build a bar graph from the IBM Cloud Object Storage data and configure the app layout.
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['Key'], y=df['Etag'], name='Key')
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='IBM Cloud Object Storage Objects 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 IBM Cloud Object Storage data.
python ibmcloudobjectstorage-dash.py
More Information and Free Trial
Now you can build interactive Dash web apps on live IBM Cloud Object Storage data using the CData Connect AI Python SDK. For more information on connecting to IBM Cloud Object Storage (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live IBM Cloud Object Storage 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 Key, Etag "
"FROM [IBMCloudObjectStorage1].[IBMCloudObjectStorage].[Objects] "
"WHERE Bucket = 'someBucket'",
conn,
)
conn.close()
app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'
trace = go.Bar(x=df['Key'], y=df['Etag'], name='Key')
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='IBM Cloud Object Storage Objects Data', barmode='stack'),
},
),
],
className="container",
)
if __name__ == '__main__':
app.run(debug=True)