Use Dash to Build Web Apps on Claude Compliance Data via CData Connect AI

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Build interactive Dash web apps on live Claude Compliance data using pandas and the CData Connect AI Python SDK.

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 Claude Compliance-connected web applications for Claude Compliance data. This article shows how to connect to Connect AI and use pandas and Dash to build a simple web app for visualizing Claude Compliance 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 Claude Compliance in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a Connection
  3. Select "Claude Compliance" from the Add Connection panel
  4. Selecting a data source
  5. Enter the necessary authentication properties to connect to Claude Compliance.

    The driver connects to Claude Compliance using a Compliance Access Key, the only supported authentication method. Set the following connection property:

    • APIKey: The Compliance Access Key you created.

    Creating a Compliance Access Key

    1. Enable the Compliance API for your organization.
    2. Sign in to claude.ai as a primary owner or organization owner and open Organization settings > API > Keys.
    3. Select Create Key and assign only the scopes your integration needs:
      • read:compliance_activities for Activities and the typed activity views.
      • read:compliance_org_data for organizations, roles, groups, and settings.
      • read:compliance_user_data for users, chats, files, projects, and downloads.
      • delete:compliance_user_data for the explicit Delete stored procedures.
    4. Create the key and copy it when it appears. The key starts with sk-ant-api01- and is shown only once.

    Optionally, set OrganizationUUID to limit organization-scoped views (such as OrganizationUsers and ComplianceRoles) to a single linked organization. If it is left empty, those views default to the first available organization and do not include data from all linked organizations.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update the user-based permissions. Updating 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.

  1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
  2. On the Settings page, go to the Access Tokens section and click Create PAT.
  3. Give the PAT a name and click Create. Creating a new PAT
  4. 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 Claude Compliance 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 Claude Compliance data into a DataFrame. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, ClaudeCompliance1).

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 Id, Name "
    "FROM [ClaudeCompliance1].[ClaudeCompliance].[Projects] "
    "WHERE OrganizationUuid = 'abcdef01-2345-6789-abcd-ef0123456789'",
    conn,
)

conn.close()

Configure the App and Layout

With the query results stored in a DataFrame, build a bar graph from the Claude Compliance data and configure the app layout.

app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'

trace = go.Bar(x=df['Id'], y=df['Name'], name='Id')

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='Claude Compliance Projects 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 Claude Compliance data.

python claudecompliance-dash.py
The Dash web app running in a browser (Salesforce is shown)

More Information and Free Trial

Now you can build interactive Dash web apps on live Claude Compliance data using the CData Connect AI Python SDK. For more information on connecting to Claude Compliance (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start building web apps on live Claude Compliance 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 Id, Name "
    "FROM [ClaudeCompliance1].[ClaudeCompliance].[Projects] "
    "WHERE OrganizationUuid = 'abcdef01-2345-6789-abcd-ef0123456789'",
    conn,
)

conn.close()

app = dash.Dash(__name__)
app.title = 'CData Connect AI + Dash'

trace = go.Bar(x=df['Id'], y=df['Name'], name='Id')

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='Claude Compliance Projects Data', barmode='stack'),
            },
        ),
    ],
    className="container",
)

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

Ready to get started?

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