Use Dash to Build to Web Apps on Claude Compliance Data

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Claude Compliance, 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 Claude Compliance with the CData Connector and use pandas and Dash to build a simple web app for visualizing Claude Compliance data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Claude Compliance data in Python. When you issue complex SQL queries from Claude Compliance, the driver pushes supported SQL operations, like filters and aggregations, directly to Claude Compliance and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Claude Compliance Data

Connecting to Claude Compliance 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.

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.

After installing the CData Claude Compliance Connector, follow the procedure below to install the other required modules and start accessing Claude Compliance 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 Claude Compliance 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.claudecompliance as mod
import plotly.graph_objs as go

You can now connect with a connection string. Use the connect function for the CData Claude Compliance Connector to create a connection for working with Claude Compliance data.

cnxn = mod.connect("APIKey=your_compliance_access_key;")

Execute SQL to Claude Compliance

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 Id, Name FROM Projects WHERE OrganizationUuid = 'abcdef01-2345-6789-abcd-ef0123456789'", 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-claudecomplianceedataplot'

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 Claude Compliance data and configure the app layout.

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

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='Claude Compliance Projects 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 Claude Compliance data.

python claudecompliance-dash.py

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Claude Compliance to start building Python apps with connectivity to Claude Compliance 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.claudecompliance as mod
import plotly.graph_objs as go

cnxn = mod.connect("APIKey=your_compliance_access_key;")

df = pd.read_sql("SELECT Id, Name FROM Projects WHERE OrganizationUuid = 'abcdef01-2345-6789-abcd-ef0123456789'", cnxn)
app_name = 'dash-claudecompliancedataplot'

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.Id, y=df.Name, name='Id')

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

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